functions (Spark 3.0.2 JavaDoc)

Object
- org.apache.spark.sql.functions

```
public class functions
extends Object
```
Commonly used functions available for DataFrame operations. Using functions defined here provides a little bit more compile-time safety to make sure the function exists.
Spark also includes more built-in functions that are less common and are not defined here. You can still access them (and all the functions defined here) using the functions.expr() API and calling them through a SQL expression string. You can find the entire list of functions at SQL API documentation.
As an example, isnan is a function that is defined here. You can use isnan(col("myCol")) to invoke the isnan function. This way the programming language's compiler ensures isnan exists and is of the proper form. You can also use expr("isnan(myCol)") function to invoke the same function. In this case, Spark itself will ensure isnan exists when it analyzes the query.
regr_count is an example of a function that is built-in but not defined here, because it is less commonly used. To invoke it, use expr("regr_count(yCol, xCol)").
This function APIs usually have methods with Column signature only because it can support not only Column but also other types such as a native string. The other variants currently exist for historical reasons.

Since:

1.3.0

Constructor Summary

Constructors
Constructor and Description

functions()

Constructors
Constructor and Description
`functions()`

Method Summary

All Methods Static Methods Concrete Methods Deprecated Methods
Modifier and Type	Method and Description
`static Column`	`abs(Column e)` Computes the absolute value of a numeric value.
`static Column`	`acos(Column e)`
`static Column`	`acos(String columnName)`
`static Column`	`add_months(Column startDate, Column numMonths)` Returns the date that is `numMonths` after `startDate`.
`static Column`	`add_months(Column startDate, int numMonths)` Returns the date that is `numMonths` after `startDate`.
`static Column`	`aggregate(Column expr, Column initialValue, scala.Function2<Column,Column,Column> merge)` Applies a binary operator to an initial state and all elements in the array, and reduces this to a single state.
`static Column`	`aggregate(Column expr, Column initialValue, scala.Function2<Column,Column,Column> merge, scala.Function1<Column,Column> finish)` Applies a binary operator to an initial state and all elements in the array, and reduces this to a single state.
`static Column`	`approx_count_distinct(Column e)` Aggregate function: returns the approximate number of distinct items in a group.
`static Column`	`approx_count_distinct(Column e, double rsd)` Aggregate function: returns the approximate number of distinct items in a group.
`static Column`	`approx_count_distinct(String columnName)` Aggregate function: returns the approximate number of distinct items in a group.
`static Column`	`approx_count_distinct(String columnName, double rsd)` Aggregate function: returns the approximate number of distinct items in a group.
`static Column`	`approxCountDistinct(Column e)` Deprecated. Use approx_count_distinct. Since 2.1.0.
`static Column`	`approxCountDistinct(Column e, double rsd)` Deprecated. Use approx_count_distinct. Since 2.1.0.
`static Column`	`approxCountDistinct(String columnName)` Deprecated. Use approx_count_distinct. Since 2.1.0.
`static Column`	`approxCountDistinct(String columnName, double rsd)` Deprecated. Use approx_count_distinct. Since 2.1.0.
`static Column`	`array_contains(Column column, Object value)` Returns null if the array is null, true if the array contains `value`, and false otherwise.
`static Column`	`array_distinct(Column e)` Removes duplicate values from the array.
`static Column`	`array_except(Column col1, Column col2)` Returns an array of the elements in the first array but not in the second array, without duplicates.
`static Column`	`array_intersect(Column col1, Column col2)` Returns an array of the elements in the intersection of the given two arrays, without duplicates.
`static Column`	`array_join(Column column, String delimiter)` Concatenates the elements of `column` using the `delimiter`.
`static Column`	`array_join(Column column, String delimiter, String nullReplacement)` Concatenates the elements of `column` using the `delimiter`.
`static Column`	`array_max(Column e)` Returns the maximum value in the array.
`static Column`	`array_min(Column e)` Returns the minimum value in the array.
`static Column`	`array_position(Column column, Object value)` Locates the position of the first occurrence of the value in the given array as long.
`static Column`	`array_remove(Column column, Object element)` Remove all elements that equal to element from the given array.
`static Column`	`array_repeat(Column left, Column right)` Creates an array containing the left argument repeated the number of times given by the right argument.
`static Column`	`array_repeat(Column e, int count)` Creates an array containing the left argument repeated the number of times given by the right argument.
`static Column`	`array_sort(Column e)` Sorts the input array in ascending order.
`static Column`	`array_union(Column col1, Column col2)` Returns an array of the elements in the union of the given two arrays, without duplicates.
`static Column`	`array(Column... cols)` Creates a new array column.
`static Column`	`array(scala.collection.Seq<Column> cols)` Creates a new array column.
`static Column`	`array(String colName, scala.collection.Seq<String> colNames)` Creates a new array column.
`static Column`	`array(String colName, String... colNames)` Creates a new array column.
`static Column`	`arrays_overlap(Column a1, Column a2)` Returns `true` if `a1` and `a2` have at least one non-null element in common.
`static Column`	`arrays_zip(Column... e)` Returns a merged array of structs in which the N-th struct contains all N-th values of input arrays.
`static Column`	`arrays_zip(scala.collection.Seq<Column> e)` Returns a merged array of structs in which the N-th struct contains all N-th values of input arrays.
`static Column`	`asc_nulls_first(String columnName)` Returns a sort expression based on ascending order of the column, and null values return before non-null values.
`static Column`	`asc_nulls_last(String columnName)` Returns a sort expression based on ascending order of the column, and null values appear after non-null values.
`static Column`	`asc(String columnName)` Returns a sort expression based on ascending order of the column.
`static Column`	`ascii(Column e)` Computes the numeric value of the first character of the string column, and returns the result as an int column.
`static Column`	`asin(Column e)`
`static Column`	`asin(String columnName)`
`static Column`	`atan(Column e)`
`static Column`	`atan(String columnName)`
`static Column`	`atan2(Column y, Column x)`
`static Column`	`atan2(Column y, double xValue)`
`static Column`	`atan2(Column y, String xName)`
`static Column`	`atan2(double yValue, Column x)`
`static Column`	`atan2(double yValue, String xName)`
`static Column`	`atan2(String yName, Column x)`
`static Column`	`atan2(String yName, double xValue)`
`static Column`	`atan2(String yName, String xName)`
`static Column`	`avg(Column e)` Aggregate function: returns the average of the values in a group.
`static Column`	`avg(String columnName)` Aggregate function: returns the average of the values in a group.
`static Column`	`base64(Column e)` Computes the BASE64 encoding of a binary column and returns it as a string column.
`static Column`	`bin(Column e)` An expression that returns the string representation of the binary value of the given long column.
`static Column`	`bin(String columnName)` An expression that returns the string representation of the binary value of the given long column.
`static Column`	`bitwiseNOT(Column e)` Computes bitwise NOT (~) of a number.
`static <T> Dataset<T>`	`broadcast(Dataset<T> df)` Marks a DataFrame as small enough for use in broadcast joins.
`static Column`	`bround(Column e)` Returns the value of the column `e` rounded to 0 decimal places with HALF_EVEN round mode.
`static Column`	`bround(Column e, int scale)` Round the value of `e` to `scale` decimal places with HALF_EVEN round mode if `scale` is greater than or equal to 0 or at integral part when `scale` is less than 0.
`static Column`	`bucket(Column numBuckets, Column e)` A transform for any type that partitions by a hash of the input column.
`static Column`	`bucket(int numBuckets, Column e)` A transform for any type that partitions by a hash of the input column.
`static Column`	`callUDF(String udfName, Column... cols)` Call an user-defined function.
`static Column`	`callUDF(String udfName, scala.collection.Seq<Column> cols)` Call an user-defined function.
`static Column`	`cbrt(Column e)` Computes the cube-root of the given value.
`static Column`	`cbrt(String columnName)` Computes the cube-root of the given column.
`static Column`	`ceil(Column e)` Computes the ceiling of the given value.
`static Column`	`ceil(String columnName)` Computes the ceiling of the given column.
`static Column`	`coalesce(Column... e)` Returns the first column that is not null, or null if all inputs are null.
`static Column`	`coalesce(scala.collection.Seq<Column> e)` Returns the first column that is not null, or null if all inputs are null.
`static Column`	`col(String colName)` Returns a `Column` based on the given column name.
`static Column`	`collect_list(Column e)` Aggregate function: returns a list of objects with duplicates.
`static Column`	`collect_list(String columnName)` Aggregate function: returns a list of objects with duplicates.
`static Column`	`collect_set(Column e)` Aggregate function: returns a set of objects with duplicate elements eliminated.
`static Column`	`collect_set(String columnName)` Aggregate function: returns a set of objects with duplicate elements eliminated.
`static Column`	`column(String colName)` Returns a `Column` based on the given column name.
`static Column`	`concat_ws(String sep, Column... exprs)` Concatenates multiple input string columns together into a single string column, using the given separator.
`static Column`	`concat_ws(String sep, scala.collection.Seq<Column> exprs)` Concatenates multiple input string columns together into a single string column, using the given separator.
`static Column`	`concat(Column... exprs)` Concatenates multiple input columns together into a single column.
`static Column`	`concat(scala.collection.Seq<Column> exprs)` Concatenates multiple input columns together into a single column.
`static Column`	`conv(Column num, int fromBase, int toBase)` Convert a number in a string column from one base to another.
`static Column`	`corr(Column column1, Column column2)` Aggregate function: returns the Pearson Correlation Coefficient for two columns.
`static Column`	`corr(String columnName1, String columnName2)` Aggregate function: returns the Pearson Correlation Coefficient for two columns.
`static Column`	`cos(Column e)`
`static Column`	`cos(String columnName)`
`static Column`	`cosh(Column e)`
`static Column`	`cosh(String columnName)`
`static Column`	`count(Column e)` Aggregate function: returns the number of items in a group.
`static TypedColumn<Object,Object>`	`count(String columnName)` Aggregate function: returns the number of items in a group.
`static Column`	`countDistinct(Column expr, Column... exprs)` Aggregate function: returns the number of distinct items in a group.
`static Column`	`countDistinct(Column expr, scala.collection.Seq<Column> exprs)` Aggregate function: returns the number of distinct items in a group.
`static Column`	`countDistinct(String columnName, scala.collection.Seq<String> columnNames)` Aggregate function: returns the number of distinct items in a group.
`static Column`	`countDistinct(String columnName, String... columnNames)` Aggregate function: returns the number of distinct items in a group.
`static Column`	`covar_pop(Column column1, Column column2)` Aggregate function: returns the population covariance for two columns.
`static Column`	`covar_pop(String columnName1, String columnName2)` Aggregate function: returns the population covariance for two columns.
`static Column`	`covar_samp(Column column1, Column column2)` Aggregate function: returns the sample covariance for two columns.
`static Column`	`covar_samp(String columnName1, String columnName2)` Aggregate function: returns the sample covariance for two columns.
`static Column`	`crc32(Column e)` Calculates the cyclic redundancy check value (CRC32) of a binary column and returns the value as a bigint.
`static Column`	`cume_dist()` Window function: returns the cumulative distribution of values within a window partition, i.e.
`static Column`	`current_date()` Returns the current date at the start of query evaluation as a date column.
`static Column`	`current_timestamp()` Returns the current timestamp at the start of query evaluation as a timestamp column.
`static Column`	`date_add(Column start, Column days)` Returns the date that is `days` days after `start`
`static Column`	`date_add(Column start, int days)` Returns the date that is `days` days after `start`
`static Column`	`date_format(Column dateExpr, String format)` Converts a date/timestamp/string to a value of string in the format specified by the date format given by the second argument.
`static Column`	`date_sub(Column start, Column days)` Returns the date that is `days` days before `start`
`static Column`	`date_sub(Column start, int days)` Returns the date that is `days` days before `start`
`static Column`	`date_trunc(String format, Column timestamp)` Returns timestamp truncated to the unit specified by the format.
`static Column`	`datediff(Column end, Column start)` Returns the number of days from `start` to `end`.
`static Column`	`dayofmonth(Column e)` Extracts the day of the month as an integer from a given date/timestamp/string.
`static Column`	`dayofweek(Column e)` Extracts the day of the week as an integer from a given date/timestamp/string.
`static Column`	`dayofyear(Column e)` Extracts the day of the year as an integer from a given date/timestamp/string.
`static Column`	`days(Column e)` A transform for timestamps and dates to partition data into days.
`static Column`	`decode(Column value, String charset)` Computes the first argument into a string from a binary using the provided character set (one of 'US-ASCII', 'ISO-8859-1', 'UTF-8', 'UTF-16BE', 'UTF-16LE', 'UTF-16').
`static Column`	`degrees(Column e)` Converts an angle measured in radians to an approximately equivalent angle measured in degrees.
`static Column`	`degrees(String columnName)` Converts an angle measured in radians to an approximately equivalent angle measured in degrees.
`static Column`	`dense_rank()` Window function: returns the rank of rows within a window partition, without any gaps.
`static Column`	`desc_nulls_first(String columnName)` Returns a sort expression based on the descending order of the column, and null values appear before non-null values.
`static Column`	`desc_nulls_last(String columnName)` Returns a sort expression based on the descending order of the column, and null values appear after non-null values.
`static Column`	`desc(String columnName)` Returns a sort expression based on the descending order of the column.
`static Column`	`element_at(Column column, Object value)` Returns element of array at given index in value if column is array.
`static Column`	`encode(Column value, String charset)` Computes the first argument into a binary from a string using the provided character set (one of 'US-ASCII', 'ISO-8859-1', 'UTF-8', 'UTF-16BE', 'UTF-16LE', 'UTF-16').
`static Column`	`exists(Column column, scala.Function1<Column,Column> f)` Returns whether a predicate holds for one or more elements in the array.
`static Column`	`exp(Column e)` Computes the exponential of the given value.
`static Column`	`exp(String columnName)` Computes the exponential of the given column.
`static Column`	`explode_outer(Column e)` Creates a new row for each element in the given array or map column.
`static Column`	`explode(Column e)` Creates a new row for each element in the given array or map column.
`static Column`	`expm1(Column e)` Computes the exponential of the given value minus one.
`static Column`	`expm1(String columnName)` Computes the exponential of the given column minus one.
`static Column`	`expr(String expr)` Parses the expression string into the column that it represents, similar to `Dataset.selectExpr(java.lang.String...)`.
`static Column`	`factorial(Column e)` Computes the factorial of the given value.
`static Column`	`filter(Column column, scala.Function1<Column,Column> f)` Returns an array of elements for which a predicate holds in a given array.
`static Column`	`filter(Column column, scala.Function2<Column,Column,Column> f)` Returns an array of elements for which a predicate holds in a given array.
`static Column`	`first(Column e)` Aggregate function: returns the first value in a group.
`static Column`	`first(Column e, boolean ignoreNulls)` Aggregate function: returns the first value in a group.
`static Column`	`first(String columnName)` Aggregate function: returns the first value of a column in a group.
`static Column`	`first(String columnName, boolean ignoreNulls)` Aggregate function: returns the first value of a column in a group.
`static Column`	`flatten(Column e)` Creates a single array from an array of arrays.
`static Column`	`floor(Column e)` Computes the floor of the given value.
`static Column`	`floor(String columnName)` Computes the floor of the given column.
`static Column`	`forall(Column column, scala.Function1<Column,Column> f)` Returns whether a predicate holds for every element in the array.
`static Column`	`format_number(Column x, int d)` Formats numeric column x to a format like '#,###,###.##', rounded to d decimal places with HALF_EVEN round mode, and returns the result as a string column.
`static Column`	`format_string(String format, Column... arguments)` Formats the arguments in printf-style and returns the result as a string column.
`static Column`	`format_string(String format, scala.collection.Seq<Column> arguments)` Formats the arguments in printf-style and returns the result as a string column.
`static Column`	`from_csv(Column e, Column schema, java.util.Map<String,String> options)` (Java-specific) Parses a column containing a CSV string into a `StructType` with the specified schema.
`static Column`	`from_csv(Column e, StructType schema, scala.collection.immutable.Map<String,String> options)` Parses a column containing a CSV string into a `StructType` with the specified schema.
`static Column`	`from_json(Column e, Column schema)` (Scala-specific) Parses a column containing a JSON string into a `MapType` with `StringType` as keys type, `StructType` or `ArrayType` of `StructType`s with the specified schema.
`static Column`	`from_json(Column e, Column schema, java.util.Map<String,String> options)` (Java-specific) Parses a column containing a JSON string into a `MapType` with `StringType` as keys type, `StructType` or `ArrayType` of `StructType`s with the specified schema.
`static Column`	`from_json(Column e, DataType schema)` Parses a column containing a JSON string into a `MapType` with `StringType` as keys type, `StructType` or `ArrayType` with the specified schema.
`static Column`	`from_json(Column e, DataType schema, scala.collection.immutable.Map<String,String> options)` (Scala-specific) Parses a column containing a JSON string into a `MapType` with `StringType` as keys type, `StructType` or `ArrayType` with the specified schema.
`static Column`	`from_json(Column e, DataType schema, java.util.Map<String,String> options)` (Java-specific) Parses a column containing a JSON string into a `MapType` with `StringType` as keys type, `StructType` or `ArrayType` with the specified schema.
`static Column`	`from_json(Column e, String schema, java.util.Map<String,String> options)` (Java-specific) Parses a column containing a JSON string into a `MapType` with `StringType` as keys type, `StructType` or `ArrayType` with the specified schema.
`static Column`	`from_json(Column e, String schema, scala.collection.immutable.Map<String,String> options)` (Scala-specific) Parses a column containing a JSON string into a `MapType` with `StringType` as keys type, `StructType` or `ArrayType` with the specified schema.
`static Column`	`from_json(Column e, StructType schema)` Parses a column containing a JSON string into a `StructType` with the specified schema.
`static Column`	`from_json(Column e, StructType schema, scala.collection.immutable.Map<String,String> options)` (Scala-specific) Parses a column containing a JSON string into a `StructType` with the specified schema.
`static Column`	`from_json(Column e, StructType schema, java.util.Map<String,String> options)` (Java-specific) Parses a column containing a JSON string into a `StructType` with the specified schema.
`static Column`	`from_unixtime(Column ut)` Converts the number of seconds from unix epoch (1970-01-01 00:00:00 UTC) to a string representing the timestamp of that moment in the current system time zone in the yyyy-MM-dd HH:mm:ss format.
`static Column`	`from_unixtime(Column ut, String f)` Converts the number of seconds from unix epoch (1970-01-01 00:00:00 UTC) to a string representing the timestamp of that moment in the current system time zone in the given format.
`static Column`	`from_utc_timestamp(Column ts, Column tz)` Given a timestamp like '2017-07-14 02:40:00.0', interprets it as a time in UTC, and renders that time as a timestamp in the given time zone.
`static Column`	`from_utc_timestamp(Column ts, String tz)` Given a timestamp like '2017-07-14 02:40:00.0', interprets it as a time in UTC, and renders that time as a timestamp in the given time zone.
`static Column`	`get_json_object(Column e, String path)` Extracts json object from a json string based on json path specified, and returns json string of the extracted json object.
`static Column`	`greatest(Column... exprs)` Returns the greatest value of the list of values, skipping null values.
`static Column`	`greatest(scala.collection.Seq<Column> exprs)` Returns the greatest value of the list of values, skipping null values.
`static Column`	`greatest(String columnName, scala.collection.Seq<String> columnNames)` Returns the greatest value of the list of column names, skipping null values.
`static Column`	`greatest(String columnName, String... columnNames)` Returns the greatest value of the list of column names, skipping null values.
`static Column`	`grouping_id(scala.collection.Seq<Column> cols)` Aggregate function: returns the level of grouping, equals to
`static Column`	`grouping_id(String colName, scala.collection.Seq<String> colNames)` Aggregate function: returns the level of grouping, equals to
`static Column`	`grouping(Column e)` Aggregate function: indicates whether a specified column in a GROUP BY list is aggregated or not, returns 1 for aggregated or 0 for not aggregated in the result set.
`static Column`	`grouping(String columnName)` Aggregate function: indicates whether a specified column in a GROUP BY list is aggregated or not, returns 1 for aggregated or 0 for not aggregated in the result set.
`static Column`	`hash(Column... cols)` Calculates the hash code of given columns, and returns the result as an int column.
`static Column`	`hash(scala.collection.Seq<Column> cols)` Calculates the hash code of given columns, and returns the result as an int column.
`static Column`	`hex(Column column)` Computes hex value of the given column.
`static Column`	`hour(Column e)` Extracts the hours as an integer from a given date/timestamp/string.
`static Column`	`hours(Column e)` A transform for timestamps to partition data into hours.
`static Column`	`hypot(Column l, Column r)` Computes `sqrt(a^2^ + b^2^)` without intermediate overflow or underflow.
`static Column`	`hypot(Column l, double r)` Computes `sqrt(a^2^ + b^2^)` without intermediate overflow or underflow.
`static Column`	`hypot(Column l, String rightName)` Computes `sqrt(a^2^ + b^2^)` without intermediate overflow or underflow.
`static Column`	`hypot(double l, Column r)` Computes `sqrt(a^2^ + b^2^)` without intermediate overflow or underflow.
`static Column`	`hypot(double l, String rightName)` Computes `sqrt(a^2^ + b^2^)` without intermediate overflow or underflow.
`static Column`	`hypot(String leftName, Column r)` Computes `sqrt(a^2^ + b^2^)` without intermediate overflow or underflow.
`static Column`	`hypot(String leftName, double r)` Computes `sqrt(a^2^ + b^2^)` without intermediate overflow or underflow.
`static Column`	`hypot(String leftName, String rightName)` Computes `sqrt(a^2^ + b^2^)` without intermediate overflow or underflow.
`static Column`	`initcap(Column e)` Returns a new string column by converting the first letter of each word to uppercase.
`static Column`	`input_file_name()` Creates a string column for the file name of the current Spark task.
`static Column`	`instr(Column str, String substring)` Locate the position of the first occurrence of substr column in the given string.
`static Column`	`isnan(Column e)` Return true iff the column is NaN.
`static Column`	`isnull(Column e)` Return true iff the column is null.
`static Column`	`json_tuple(Column json, scala.collection.Seq<String> fields)` Creates a new row for a json column according to the given field names.
`static Column`	`json_tuple(Column json, String... fields)` Creates a new row for a json column according to the given field names.
`static Column`	`kurtosis(Column e)` Aggregate function: returns the kurtosis of the values in a group.
`static Column`	`kurtosis(String columnName)` Aggregate function: returns the kurtosis of the values in a group.
`static Column`	`lag(Column e, int offset)` Window function: returns the value that is `offset` rows before the current row, and `null` if there is less than `offset` rows before the current row.
`static Column`	`lag(Column e, int offset, Object defaultValue)` Window function: returns the value that is `offset` rows before the current row, and `defaultValue` if there is less than `offset` rows before the current row.
`static Column`	`lag(String columnName, int offset)` Window function: returns the value that is `offset` rows before the current row, and `null` if there is less than `offset` rows before the current row.
`static Column`	`lag(String columnName, int offset, Object defaultValue)` Window function: returns the value that is `offset` rows before the current row, and `defaultValue` if there is less than `offset` rows before the current row.
`static Column`	`last_day(Column e)` Returns the last day of the month which the given date belongs to.
`static Column`	`last(Column e)` Aggregate function: returns the last value in a group.
`static Column`	`last(Column e, boolean ignoreNulls)` Aggregate function: returns the last value in a group.
`static Column`	`last(String columnName)` Aggregate function: returns the last value of the column in a group.
`static Column`	`last(String columnName, boolean ignoreNulls)` Aggregate function: returns the last value of the column in a group.
`static Column`	`lead(Column e, int offset)` Window function: returns the value that is `offset` rows after the current row, and `null` if there is less than `offset` rows after the current row.
`static Column`	`lead(Column e, int offset, Object defaultValue)` Window function: returns the value that is `offset` rows after the current row, and `defaultValue` if there is less than `offset` rows after the current row.
`static Column`	`lead(String columnName, int offset)` Window function: returns the value that is `offset` rows after the current row, and `null` if there is less than `offset` rows after the current row.
`static Column`	`lead(String columnName, int offset, Object defaultValue)` Window function: returns the value that is `offset` rows after the current row, and `defaultValue` if there is less than `offset` rows after the current row.
`static Column`	`least(Column... exprs)` Returns the least value of the list of values, skipping null values.
`static Column`	`least(scala.collection.Seq<Column> exprs)` Returns the least value of the list of values, skipping null values.
`static Column`	`least(String columnName, scala.collection.Seq<String> columnNames)` Returns the least value of the list of column names, skipping null values.
`static Column`	`least(String columnName, String... columnNames)` Returns the least value of the list of column names, skipping null values.
`static Column`	`length(Column e)` Computes the character length of a given string or number of bytes of a binary string.
`static Column`	`levenshtein(Column l, Column r)` Computes the Levenshtein distance of the two given string columns.
`static Column`	`lit(Object literal)` Creates a `Column` of literal value.
`static Column`	`locate(String substr, Column str)` Locate the position of the first occurrence of substr.
`static Column`	`locate(String substr, Column str, int pos)` Locate the position of the first occurrence of substr in a string column, after position pos.
`static Column`	`log(Column e)` Computes the natural logarithm of the given value.
`static Column`	`log(double base, Column a)` Returns the first argument-base logarithm of the second argument.
`static Column`	`log(double base, String columnName)` Returns the first argument-base logarithm of the second argument.
`static Column`	`log(String columnName)` Computes the natural logarithm of the given column.
`static Column`	`log10(Column e)` Computes the logarithm of the given value in base 10.
`static Column`	`log10(String columnName)` Computes the logarithm of the given value in base 10.
`static Column`	`log1p(Column e)` Computes the natural logarithm of the given value plus one.
`static Column`	`log1p(String columnName)` Computes the natural logarithm of the given column plus one.
`static Column`	`log2(Column expr)` Computes the logarithm of the given column in base 2.
`static Column`	`log2(String columnName)` Computes the logarithm of the given value in base 2.
`static Column`	`lower(Column e)` Converts a string column to lower case.
`static Column`	`lpad(Column str, int len, String pad)` Left-pad the string column with pad to a length of len.
`static Column`	`ltrim(Column e)` Trim the spaces from left end for the specified string value.
`static Column`	`ltrim(Column e, String trimString)` Trim the specified character string from left end for the specified string column.
`static Column`	`map_concat(Column... cols)` Returns the union of all the given maps.
`static Column`	`map_concat(scala.collection.Seq<Column> cols)` Returns the union of all the given maps.
`static Column`	`map_entries(Column e)` Returns an unordered array of all entries in the given map.
`static Column`	`map_filter(Column expr, scala.Function2<Column,Column,Column> f)` Returns a map whose key-value pairs satisfy a predicate.
`static Column`	`map_from_arrays(Column keys, Column values)` Creates a new map column.
`static Column`	`map_from_entries(Column e)` Returns a map created from the given array of entries.
`static Column`	`map_keys(Column e)` Returns an unordered array containing the keys of the map.
`static Column`	`map_values(Column e)` Returns an unordered array containing the values of the map.
`static Column`	`map_zip_with(Column left, Column right, scala.Function3<Column,Column,Column,Column> f)` Merge two given maps, key-wise into a single map using a function.
`static Column`	`map(Column... cols)` Creates a new map column.
`static Column`	`map(scala.collection.Seq<Column> cols)` Creates a new map column.
`static Column`	`max(Column e)` Aggregate function: returns the maximum value of the expression in a group.
`static Column`	`max(String columnName)` Aggregate function: returns the maximum value of the column in a group.
`static Column`	`md5(Column e)` Calculates the MD5 digest of a binary column and returns the value as a 32 character hex string.
`static Column`	`mean(Column e)` Aggregate function: returns the average of the values in a group.
`static Column`	`mean(String columnName)` Aggregate function: returns the average of the values in a group.
`static Column`	`min(Column e)` Aggregate function: returns the minimum value of the expression in a group.
`static Column`	`min(String columnName)` Aggregate function: returns the minimum value of the column in a group.
`static Column`	`minute(Column e)` Extracts the minutes as an integer from a given date/timestamp/string.
`static Column`	`monotonically_increasing_id()` A column expression that generates monotonically increasing 64-bit integers.
`static Column`	`monotonicallyIncreasingId()` Deprecated. Use monotonically_increasing_id(). Since 2.0.0.
`static Column`	`month(Column e)` Extracts the month as an integer from a given date/timestamp/string.
`static Column`	`months_between(Column end, Column start)` Returns number of months between dates `start` and `end`.
`static Column`	`months_between(Column end, Column start, boolean roundOff)` Returns number of months between dates `end` and `start`.
`static Column`	`months(Column e)` A transform for timestamps and dates to partition data into months.
`static Column`	`nanvl(Column col1, Column col2)` Returns col1 if it is not NaN, or col2 if col1 is NaN.
`static Column`	`negate(Column e)` Unary minus, i.e.
`static Column`	`next_day(Column date, String dayOfWeek)` Returns the first date which is later than the value of the `date` column that is on the specified day of the week.
`static Column`	`not(Column e)` Inversion of boolean expression, i.e.
`static Column`	`ntile(int n)` Window function: returns the ntile group id (from 1 to `n` inclusive) in an ordered window partition.
`static Column`	`overlay(Column src, Column replace, Column pos)` Overlay the specified portion of `src` with `replace`, starting from byte position `pos` of `src`.
`static Column`	`overlay(Column src, Column replace, Column pos, Column len)` Overlay the specified portion of `src` with `replace`, starting from byte position `pos` of `src` and proceeding for `len` bytes.
`static Column`	`percent_rank()` Window function: returns the relative rank (i.e.
`static Column`	`pmod(Column dividend, Column divisor)` Returns the positive value of dividend mod divisor.
`static Column`	`posexplode_outer(Column e)` Creates a new row for each element with position in the given array or map column.
`static Column`	`posexplode(Column e)` Creates a new row for each element with position in the given array or map column.
`static Column`	`pow(Column l, Column r)` Returns the value of the first argument raised to the power of the second argument.
`static Column`	`pow(Column l, double r)` Returns the value of the first argument raised to the power of the second argument.
`static Column`	`pow(Column l, String rightName)` Returns the value of the first argument raised to the power of the second argument.
`static Column`	`pow(double l, Column r)` Returns the value of the first argument raised to the power of the second argument.
`static Column`	`pow(double l, String rightName)` Returns the value of the first argument raised to the power of the second argument.
`static Column`	`pow(String leftName, Column r)` Returns the value of the first argument raised to the power of the second argument.
`static Column`	`pow(String leftName, double r)` Returns the value of the first argument raised to the power of the second argument.
`static Column`	`pow(String leftName, String rightName)` Returns the value of the first argument raised to the power of the second argument.
`static Column`	`quarter(Column e)` Extracts the quarter as an integer from a given date/timestamp/string.
`static Column`	`radians(Column e)` Converts an angle measured in degrees to an approximately equivalent angle measured in radians.
`static Column`	`radians(String columnName)` Converts an angle measured in degrees to an approximately equivalent angle measured in radians.
`static Column`	`rand()` Generate a random column with independent and identically distributed (i.i.d.) samples uniformly distributed in [0.0, 1.0).
`static Column`	`rand(long seed)` Generate a random column with independent and identically distributed (i.i.d.) samples uniformly distributed in [0.0, 1.0).
`static Column`	`randn()` Generate a column with independent and identically distributed (i.i.d.) samples from the standard normal distribution.
`static Column`	`randn(long seed)` Generate a column with independent and identically distributed (i.i.d.) samples from the standard normal distribution.
`static Column`	`rank()` Window function: returns the rank of rows within a window partition.
`static Column`	`regexp_extract(Column e, String exp, int groupIdx)` Extract a specific group matched by a Java regex, from the specified string column.
`static Column`	`regexp_replace(Column e, Column pattern, Column replacement)` Replace all substrings of the specified string value that match regexp with rep.
`static Column`	`regexp_replace(Column e, String pattern, String replacement)` Replace all substrings of the specified string value that match regexp with rep.
`static Column`	`repeat(Column str, int n)` Repeats a string column n times, and returns it as a new string column.
`static Column`	`reverse(Column e)` Returns a reversed string or an array with reverse order of elements.
`static Column`	`rint(Column e)` Returns the double value that is closest in value to the argument and is equal to a mathematical integer.
`static Column`	`rint(String columnName)` Returns the double value that is closest in value to the argument and is equal to a mathematical integer.
`static Column`	`round(Column e)` Returns the value of the column `e` rounded to 0 decimal places with HALF_UP round mode.
`static Column`	`round(Column e, int scale)` Round the value of `e` to `scale` decimal places with HALF_UP round mode if `scale` is greater than or equal to 0 or at integral part when `scale` is less than 0.
`static Column`	`row_number()` Window function: returns a sequential number starting at 1 within a window partition.
`static Column`	`rpad(Column str, int len, String pad)` Right-pad the string column with pad to a length of len.
`static Column`	`rtrim(Column e)` Trim the spaces from right end for the specified string value.
`static Column`	`rtrim(Column e, String trimString)` Trim the specified character string from right end for the specified string column.
`static Column`	`schema_of_csv(Column csv)` Parses a CSV string and infers its schema in DDL format.
`static Column`	`schema_of_csv(Column csv, java.util.Map<String,String> options)` Parses a CSV string and infers its schema in DDL format using options.
`static Column`	`schema_of_csv(String csv)` Parses a CSV string and infers its schema in DDL format.
`static Column`	`schema_of_json(Column json)` Parses a JSON string and infers its schema in DDL format.
`static Column`	`schema_of_json(Column json, java.util.Map<String,String> options)` Parses a JSON string and infers its schema in DDL format using options.
`static Column`	`schema_of_json(String json)` Parses a JSON string and infers its schema in DDL format.
`static Column`	`second(Column e)` Extracts the seconds as an integer from a given date/timestamp/string.
`static Column`	`sequence(Column start, Column stop)` Generate a sequence of integers from start to stop, incrementing by 1 if start is less than or equal to stop, otherwise -1.
`static Column`	`sequence(Column start, Column stop, Column step)` Generate a sequence of integers from start to stop, incrementing by step.
`static Column`	`sha1(Column e)` Calculates the SHA-1 digest of a binary column and returns the value as a 40 character hex string.
`static Column`	`sha2(Column e, int numBits)` Calculates the SHA-2 family of hash functions of a binary column and returns the value as a hex string.
`static Column`	`shiftLeft(Column e, int numBits)` Shift the given value numBits left.
`static Column`	`shiftRight(Column e, int numBits)` (Signed) shift the given value numBits right.
`static Column`	`shiftRightUnsigned(Column e, int numBits)` Unsigned shift the given value numBits right.
`static Column`	`shuffle(Column e)` Returns a random permutation of the given array.
`static Column`	`signum(Column e)` Computes the signum of the given value.
`static Column`	`signum(String columnName)` Computes the signum of the given column.
`static Column`	`sin(Column e)`
`static Column`	`sin(String columnName)`
`static Column`	`sinh(Column e)`
`static Column`	`sinh(String columnName)`
`static Column`	`size(Column e)` Returns length of array or map.
`static Column`	`skewness(Column e)` Aggregate function: returns the skewness of the values in a group.
`static Column`	`skewness(String columnName)` Aggregate function: returns the skewness of the values in a group.
`static Column`	`slice(Column x, int start, int length)` Returns an array containing all the elements in `x` from index `start` (or starting from the end if `start` is negative) with the specified `length`.
`static Column`	`sort_array(Column e)` Sorts the input array for the given column in ascending order, according to the natural ordering of the array elements.
`static Column`	`sort_array(Column e, boolean asc)` Sorts the input array for the given column in ascending or descending order, according to the natural ordering of the array elements.
`static Column`	`soundex(Column e)` Returns the soundex code for the specified expression.
`static Column`	`spark_partition_id()` Partition ID.
`static Column`	`split(Column str, String pattern)` Splits str around matches of the given pattern.
`static Column`	`split(Column str, String pattern, int limit)` Splits str around matches of the given pattern.
`static Column`	`sqrt(Column e)` Computes the square root of the specified float value.
`static Column`	`sqrt(String colName)` Computes the square root of the specified float value.
`static Column`	`stddev_pop(Column e)` Aggregate function: returns the population standard deviation of the expression in a group.
`static Column`	`stddev_pop(String columnName)` Aggregate function: returns the population standard deviation of the expression in a group.
`static Column`	`stddev_samp(Column e)` Aggregate function: returns the sample standard deviation of the expression in a group.
`static Column`	`stddev_samp(String columnName)` Aggregate function: returns the sample standard deviation of the expression in a group.
`static Column`	`stddev(Column e)` Aggregate function: alias for `stddev_samp`.
`static Column`	`stddev(String columnName)` Aggregate function: alias for `stddev_samp`.
`static Column`	`struct(Column... cols)` Creates a new struct column.
`static Column`	`struct(scala.collection.Seq<Column> cols)` Creates a new struct column.
`static Column`	`struct(String colName, scala.collection.Seq<String> colNames)` Creates a new struct column that composes multiple input columns.
`static Column`	`struct(String colName, String... colNames)` Creates a new struct column that composes multiple input columns.
`static Column`	`substring_index(Column str, String delim, int count)` Returns the substring from string str before count occurrences of the delimiter delim.
`static Column`	`substring(Column str, int pos, int len)` Substring starts at `pos` and is of length `len` when str is String type or returns the slice of byte array that starts at `pos` in byte and is of length `len` when str is Binary type
`static Column`	`sum(Column e)` Aggregate function: returns the sum of all values in the expression.
`static Column`	`sum(String columnName)` Aggregate function: returns the sum of all values in the given column.
`static Column`	`sumDistinct(Column e)` Aggregate function: returns the sum of distinct values in the expression.
`static Column`	`sumDistinct(String columnName)` Aggregate function: returns the sum of distinct values in the expression.
`static Column`	`tan(Column e)`
`static Column`	`tan(String columnName)`
`static Column`	`tanh(Column e)`
`static Column`	`tanh(String columnName)`
`static Column`	`to_csv(Column e)` Converts a column containing a `StructType` into a CSV string with the specified schema.
`static Column`	`to_csv(Column e, java.util.Map<String,String> options)` (Java-specific) Converts a column containing a `StructType` into a CSV string with the specified schema.
`static Column`	`to_date(Column e)` Converts the column into `DateType` by casting rules to `DateType`.
`static Column`	`to_date(Column e, String fmt)` Converts the column into a `DateType` with a specified format
`static Column`	`to_json(Column e)` Converts a column containing a `StructType`, `ArrayType` or a `MapType` into a JSON string with the specified schema.
`static Column`	`to_json(Column e, scala.collection.immutable.Map<String,String> options)` (Scala-specific) Converts a column containing a `StructType`, `ArrayType` or a `MapType` into a JSON string with the specified schema.
`static Column`	`to_json(Column e, java.util.Map<String,String> options)` (Java-specific) Converts a column containing a `StructType`, `ArrayType` or a `MapType` into a JSON string with the specified schema.
`static Column`	`to_timestamp(Column s)` Converts to a timestamp by casting rules to `TimestampType`.
`static Column`	`to_timestamp(Column s, String fmt)` Converts time string with the given pattern to timestamp.
`static Column`	`to_utc_timestamp(Column ts, Column tz)` Given a timestamp like '2017-07-14 02:40:00.0', interprets it as a time in the given time zone, and renders that time as a timestamp in UTC.
`static Column`	`to_utc_timestamp(Column ts, String tz)` Given a timestamp like '2017-07-14 02:40:00.0', interprets it as a time in the given time zone, and renders that time as a timestamp in UTC.
`static Column`	`toDegrees(Column e)` Deprecated. Use degrees. Since 2.1.0.
`static Column`	`toDegrees(String columnName)` Deprecated. Use degrees. Since 2.1.0.
`static Column`	`toRadians(Column e)` Deprecated. Use radians. Since 2.1.0.
`static Column`	`toRadians(String columnName)` Deprecated. Use radians. Since 2.1.0.
`static Column`	`transform_keys(Column expr, scala.Function2<Column,Column,Column> f)` Applies a function to every key-value pair in a map and returns a map with the results of those applications as the new keys for the pairs.
`static Column`	`transform_values(Column expr, scala.Function2<Column,Column,Column> f)` Applies a function to every key-value pair in a map and returns a map with the results of those applications as the new values for the pairs.
`static Column`	`transform(Column column, scala.Function1<Column,Column> f)` Returns an array of elements after applying a transformation to each element in the input array.
`static Column`	`transform(Column column, scala.Function2<Column,Column,Column> f)` Returns an array of elements after applying a transformation to each element in the input array.
`static Column`	`translate(Column src, String matchingString, String replaceString)` Translate any character in the src by a character in replaceString.
`static Column`	`trim(Column e)` Trim the spaces from both ends for the specified string column.
`static Column`	`trim(Column e, String trimString)` Trim the specified character from both ends for the specified string column.
`static Column`	`trunc(Column date, String format)` Returns date truncated to the unit specified by the format.
`static <T> Column`	`typedLit(T literal, scala.reflect.api.TypeTags.TypeTag<T> evidence$1)` Creates a `Column` of literal value.
`static <IN,BUF,OUT> UserDefinedFunction`	`udaf(Aggregator<IN,BUF,OUT> agg, Encoder<IN> inputEncoder)` Obtains a `UserDefinedFunction` that wraps the given `Aggregator` so that it may be used with untyped Data Frames.
`static <IN,BUF,OUT> UserDefinedFunction`	`udaf(Aggregator<IN,BUF,OUT> agg, scala.reflect.api.TypeTags.TypeTag<IN> evidence$2)` Obtains a `UserDefinedFunction` that wraps the given `Aggregator` so that it may be used with untyped Data Frames.
`static <RT> UserDefinedFunction`	`udf(scala.Function0<RT> f, scala.reflect.api.TypeTags.TypeTag<RT> evidence$3)` Defines a Scala closure of 0 arguments as user-defined function (UDF).
`static <RT,A1> UserDefinedFunction`	`udf(scala.Function1<A1,RT> f, scala.reflect.api.TypeTags.TypeTag<RT> evidence$4, scala.reflect.api.TypeTags.TypeTag<A1> evidence$5)` Defines a Scala closure of 1 arguments as user-defined function (UDF).
`static <RT,A1,A2,A3,A4,A5,A6,A7,A8,A9,A10> UserDefinedFunction`	udf(scala.Function10<A1,A2,A3,A4,A5,A6,A7,A8,A9,A10,RT> f, scala.reflect.api.TypeTags.TypeTag<RT> evidence$58, scala.reflect.api.TypeTags.TypeTag<A1> evidence$59, scala.reflect.api.TypeTags.TypeTag<A2> evidence$60, scala.reflect.api.TypeTags.TypeTag<A3> evidence$61, scala.reflect.api.TypeTags.TypeTag<A4> evidence$62, scala.reflect.api.TypeTags.TypeTag<A5> evidence$63, scala.reflect.api.TypeTags.TypeTag<A6> evidence$64, scala.reflect.api.TypeTags.TypeTag<A7> evidence$65, scala.reflect.api.TypeTags.TypeTag<A8> evidence$66, scala.reflect.api.TypeTags.TypeTag<A9> evidence$67, scala.reflect.api.TypeTags.TypeTag<A10> evidence$68) Defines a Scala closure of 10 arguments as user-defined function (UDF).
`static <RT,A1,A2> UserDefinedFunction`	`udf(scala.Function2<A1,A2,RT> f, scala.reflect.api.TypeTags.TypeTag<RT> evidence$6, scala.reflect.api.TypeTags.TypeTag<A1> evidence$7, scala.reflect.api.TypeTags.TypeTag<A2> evidence$8)` Defines a Scala closure of 2 arguments as user-defined function (UDF).
`static <RT,A1,A2,A3> UserDefinedFunction`	`udf(scala.Function3<A1,A2,A3,RT> f, scala.reflect.api.TypeTags.TypeTag<RT> evidence$9, scala.reflect.api.TypeTags.TypeTag<A1> evidence$10, scala.reflect.api.TypeTags.TypeTag<A2> evidence$11, scala.reflect.api.TypeTags.TypeTag<A3> evidence$12)` Defines a Scala closure of 3 arguments as user-defined function (UDF).
`static <RT,A1,A2,A3,A4> UserDefinedFunction`	`udf(scala.Function4<A1,A2,A3,A4,RT> f, scala.reflect.api.TypeTags.TypeTag<RT> evidence$13, scala.reflect.api.TypeTags.TypeTag<A1> evidence$14, scala.reflect.api.TypeTags.TypeTag<A2> evidence$15, scala.reflect.api.TypeTags.TypeTag<A3> evidence$16, scala.reflect.api.TypeTags.TypeTag<A4> evidence$17)` Defines a Scala closure of 4 arguments as user-defined function (UDF).
`static <RT,A1,A2,A3,A4,A5> UserDefinedFunction`	`udf(scala.Function5<A1,A2,A3,A4,A5,RT> f, scala.reflect.api.TypeTags.TypeTag<RT> evidence$18, scala.reflect.api.TypeTags.TypeTag<A1> evidence$19, scala.reflect.api.TypeTags.TypeTag<A2> evidence$20, scala.reflect.api.TypeTags.TypeTag<A3> evidence$21, scala.reflect.api.TypeTags.TypeTag<A4> evidence$22, scala.reflect.api.TypeTags.TypeTag<A5> evidence$23)` Defines a Scala closure of 5 arguments as user-defined function (UDF).
`static <RT,A1,A2,A3,A4,A5,A6> UserDefinedFunction`	`udf(scala.Function6<A1,A2,A3,A4,A5,A6,RT> f, scala.reflect.api.TypeTags.TypeTag<RT> evidence$24, scala.reflect.api.TypeTags.TypeTag<A1> evidence$25, scala.reflect.api.TypeTags.TypeTag<A2> evidence$26, scala.reflect.api.TypeTags.TypeTag<A3> evidence$27, scala.reflect.api.TypeTags.TypeTag<A4> evidence$28, scala.reflect.api.TypeTags.TypeTag<A5> evidence$29, scala.reflect.api.TypeTags.TypeTag<A6> evidence$30)` Defines a Scala closure of 6 arguments as user-defined function (UDF).
`static <RT,A1,A2,A3,A4,A5,A6,A7> UserDefinedFunction`	`udf(scala.Function7<A1,A2,A3,A4,A5,A6,A7,RT> f, scala.reflect.api.TypeTags.TypeTag<RT> evidence$31, scala.reflect.api.TypeTags.TypeTag<A1> evidence$32, scala.reflect.api.TypeTags.TypeTag<A2> evidence$33, scala.reflect.api.TypeTags.TypeTag<A3> evidence$34, scala.reflect.api.TypeTags.TypeTag<A4> evidence$35, scala.reflect.api.TypeTags.TypeTag<A5> evidence$36, scala.reflect.api.TypeTags.TypeTag<A6> evidence$37, scala.reflect.api.TypeTags.TypeTag<A7> evidence$38)` Defines a Scala closure of 7 arguments as user-defined function (UDF).
`static <RT,A1,A2,A3,A4,A5,A6,A7,A8> UserDefinedFunction`	udf(scala.Function8<A1,A2,A3,A4,A5,A6,A7,A8,RT> f, scala.reflect.api.TypeTags.TypeTag<RT> evidence$39, scala.reflect.api.TypeTags.TypeTag<A1> evidence$40, scala.reflect.api.TypeTags.TypeTag<A2> evidence$41, scala.reflect.api.TypeTags.TypeTag<A3> evidence$42, scala.reflect.api.TypeTags.TypeTag<A4> evidence$43, scala.reflect.api.TypeTags.TypeTag<A5> evidence$44, scala.reflect.api.TypeTags.TypeTag<A6> evidence$45, scala.reflect.api.TypeTags.TypeTag<A7> evidence$46, scala.reflect.api.TypeTags.TypeTag<A8> evidence$47) Defines a Scala closure of 8 arguments as user-defined function (UDF).
`static <RT,A1,A2,A3,A4,A5,A6,A7,A8,A9> UserDefinedFunction`	udf(scala.Function9<A1,A2,A3,A4,A5,A6,A7,A8,A9,RT> f, scala.reflect.api.TypeTags.TypeTag<RT> evidence$48, scala.reflect.api.TypeTags.TypeTag<A1> evidence$49, scala.reflect.api.TypeTags.TypeTag<A2> evidence$50, scala.reflect.api.TypeTags.TypeTag<A3> evidence$51, scala.reflect.api.TypeTags.TypeTag<A4> evidence$52, scala.reflect.api.TypeTags.TypeTag<A5> evidence$53, scala.reflect.api.TypeTags.TypeTag<A6> evidence$54, scala.reflect.api.TypeTags.TypeTag<A7> evidence$55, scala.reflect.api.TypeTags.TypeTag<A8> evidence$56, scala.reflect.api.TypeTags.TypeTag<A9> evidence$57) Defines a Scala closure of 9 arguments as user-defined function (UDF).
`static UserDefinedFunction`	`udf(Object f, DataType dataType)` Deprecated. Scala `udf` method with return type parameter is deprecated. Please use Scala `udf` method without return type parameter. Since 3.0.0.
`static UserDefinedFunction`	`udf(UDF0<?> f, DataType returnType)` Defines a Java UDF0 instance as user-defined function (UDF).
`static UserDefinedFunction`	`udf(UDF1<?,?> f, DataType returnType)` Defines a Java UDF1 instance as user-defined function (UDF).
`static UserDefinedFunction`	`udf(UDF10<?,?,?,?,?,?,?,?,?,?,?> f, DataType returnType)` Defines a Java UDF10 instance as user-defined function (UDF).
`static UserDefinedFunction`	`udf(UDF2<?,?,?> f, DataType returnType)` Defines a Java UDF2 instance as user-defined function (UDF).
`static UserDefinedFunction`	`udf(UDF3<?,?,?,?> f, DataType returnType)` Defines a Java UDF3 instance as user-defined function (UDF).
`static UserDefinedFunction`	`udf(UDF4<?,?,?,?,?> f, DataType returnType)` Defines a Java UDF4 instance as user-defined function (UDF).
`static UserDefinedFunction`	`udf(UDF5<?,?,?,?,?,?> f, DataType returnType)` Defines a Java UDF5 instance as user-defined function (UDF).
`static UserDefinedFunction`	`udf(UDF6<?,?,?,?,?,?,?> f, DataType returnType)` Defines a Java UDF6 instance as user-defined function (UDF).
`static UserDefinedFunction`	`udf(UDF7<?,?,?,?,?,?,?,?> f, DataType returnType)` Defines a Java UDF7 instance as user-defined function (UDF).
`static UserDefinedFunction`	`udf(UDF8<?,?,?,?,?,?,?,?,?> f, DataType returnType)` Defines a Java UDF8 instance as user-defined function (UDF).
`static UserDefinedFunction`	`udf(UDF9<?,?,?,?,?,?,?,?,?,?> f, DataType returnType)` Defines a Java UDF9 instance as user-defined function (UDF).
`static Column`	`unbase64(Column e)` Decodes a BASE64 encoded string column and returns it as a binary column.
`static Column`	`unhex(Column column)` Inverse of hex.
`static Column`	`unix_timestamp()` Returns the current Unix timestamp (in seconds) as a long.
`static Column`	`unix_timestamp(Column s)` Converts time string in format yyyy-MM-dd HH:mm:ss to Unix timestamp (in seconds), using the default timezone and the default locale.
`static Column`	`unix_timestamp(Column s, String p)` Converts time string with given pattern to Unix timestamp (in seconds).
`static Column`	`upper(Column e)` Converts a string column to upper case.
`static Column`	`var_pop(Column e)` Aggregate function: returns the population variance of the values in a group.
`static Column`	`var_pop(String columnName)` Aggregate function: returns the population variance of the values in a group.
`static Column`	`var_samp(Column e)` Aggregate function: returns the unbiased variance of the values in a group.
`static Column`	`var_samp(String columnName)` Aggregate function: returns the unbiased variance of the values in a group.
`static Column`	`variance(Column e)` Aggregate function: alias for `var_samp`.
`static Column`	`variance(String columnName)` Aggregate function: alias for `var_samp`.
`static Column`	`weekofyear(Column e)` Extracts the week number as an integer from a given date/timestamp/string.
`static Column`	`when(Column condition, Object value)` Evaluates a list of conditions and returns one of multiple possible result expressions.
`static Column`	`window(Column timeColumn, String windowDuration)` Generates tumbling time windows given a timestamp specifying column.
`static Column`	`window(Column timeColumn, String windowDuration, String slideDuration)` Bucketize rows into one or more time windows given a timestamp specifying column.
`static Column`	`window(Column timeColumn, String windowDuration, String slideDuration, String startTime)` Bucketize rows into one or more time windows given a timestamp specifying column.
`static Column`	`xxhash64(Column... cols)` Calculates the hash code of given columns using the 64-bit variant of the xxHash algorithm, and returns the result as a long column.
`static Column`	`xxhash64(scala.collection.Seq<Column> cols)` Calculates the hash code of given columns using the 64-bit variant of the xxHash algorithm, and returns the result as a long column.
`static Column`	`year(Column e)` Extracts the year as an integer from a given date/timestamp/string.
`static Column`	`years(Column e)` A transform for timestamps and dates to partition data into years.
`static Column`	`zip_with(Column left, Column right, scala.Function2<Column,Column,Column> f)` Merge two given arrays, element-wise, into a single array using a function.

Methods inherited from class Object
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Constructor Detail
  - functions
```
public functions()
```
- Method Detail
  - countDistinct
```
public static Column countDistinct(Column expr,
                                   Column... exprs)
```
    Aggregate function: returns the number of distinct items in a group.
    
    Parameters:
    
    expr - (undocumented)
    
    exprs - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.3.0
  - countDistinct
```
public static Column countDistinct(String columnName,
                                   String... columnNames)
```
    Aggregate function: returns the number of distinct items in a group.
    
    Parameters:
    
    columnName - (undocumented)
    
    columnNames - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.3.0
  - array
```
public static Column array(Column... cols)
```
    Creates a new array column. The input columns must all have the same data type.
    
    Parameters:
    
    cols - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - array
```
public static Column array(String colName,
                           String... colNames)
```
    Creates a new array column. The input columns must all have the same data type.
    
    Parameters:
    
    colName - (undocumented)
    
    colNames - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - map
```
public static Column map(Column... cols)
```
    Creates a new map column. The input columns must be grouped as key-value pairs, e.g. (key1, value1, key2, value2, ...). The key columns must all have the same data type, and can't be null. The value columns must all have the same data type.
    
    Parameters:
    
    cols - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.0
  - coalesce
```
public static Column coalesce(Column... e)
```
    Returns the first column that is not null, or null if all inputs are null.
    For example, coalesce(a, b, c) will return a if a is not null, or b if a is null and b is not null, or c if both a and b are null but c is not null.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.3.0
  - struct
```
public static Column struct(Column... cols)
```
    Creates a new struct column. If the input column is a column in a DataFrame, or a derived column expression that is named (i.e. aliased), its name would be retained as the StructField's name, otherwise, the newly generated StructField's name would be auto generated as col with a suffix index + 1, i.e. col1, col2, col3, ...
    
    Parameters:
    
    cols - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - struct
```
public static Column struct(String colName,
                            String... colNames)
```
    Creates a new struct column that composes multiple input columns.
    
    Parameters:
    
    colName - (undocumented)
    
    colNames - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - greatest
```
public static Column greatest(Column... exprs)
```
    Returns the greatest value of the list of values, skipping null values. This function takes at least 2 parameters. It will return null iff all parameters are null.
    
    Parameters:
    
    exprs - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - greatest
```
public static Column greatest(String columnName,
                              String... columnNames)
```
    Returns the greatest value of the list of column names, skipping null values. This function takes at least 2 parameters. It will return null iff all parameters are null.
    
    Parameters:
    
    columnName - (undocumented)
    
    columnNames - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - least
```
public static Column least(Column... exprs)
```
    Returns the least value of the list of values, skipping null values. This function takes at least 2 parameters. It will return null iff all parameters are null.
    
    Parameters:
    
    exprs - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - least
```
public static Column least(String columnName,
                           String... columnNames)
```
    Returns the least value of the list of column names, skipping null values. This function takes at least 2 parameters. It will return null iff all parameters are null.
    
    Parameters:
    
    columnName - (undocumented)
    
    columnNames - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - hash
```
public static Column hash(Column... cols)
```
    Calculates the hash code of given columns, and returns the result as an int column.
    
    Parameters:
    
    cols - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.0.0
  - xxhash64
```
public static Column xxhash64(Column... cols)
```
    Calculates the hash code of given columns using the 64-bit variant of the xxHash algorithm, and returns the result as a long column.
    
    Parameters:
    
    cols - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    3.0.0
  - concat_ws
```
public static Column concat_ws(String sep,
                               Column... exprs)
```
    Concatenates multiple input string columns together into a single string column, using the given separator.
    
    Parameters:
    
    sep - (undocumented)
    
    exprs - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - format_string
```
public static Column format_string(String format,
                                   Column... arguments)
```
    Formats the arguments in printf-style and returns the result as a string column.
    
    Parameters:
    
    format - (undocumented)
    
    arguments - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - concat
```
public static Column concat(Column... exprs)
```
    Concatenates multiple input columns together into a single column. The function works with strings, binary and compatible array columns.
    
    Parameters:
    
    exprs - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - json_tuple
```
public static Column json_tuple(Column json,
                                String... fields)
```
    Creates a new row for a json column according to the given field names.
    
    Parameters:
    
    json - (undocumented)
    
    fields - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.6.0
  - arrays_zip
```
public static Column arrays_zip(Column... e)
```
    Returns a merged array of structs in which the N-th struct contains all N-th values of input arrays.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.4.0
  - map_concat
```
public static Column map_concat(Column... cols)
```
    Returns the union of all the given maps.
    
    Parameters:
    
    cols - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.4.0
  - callUDF
```
public static Column callUDF(String udfName,
                             Column... cols)
```
    Call an user-defined function. Example:
```
  import org.apache.spark.sql._

  val df = Seq(("id1", 1), ("id2", 4), ("id3", 5)).toDF("id", "value")
  val spark = df.sparkSession
  spark.udf.register("simpleUDF", (v: Int) => v * v)
  df.select($"id", callUDF("simpleUDF", $"value"))
 
```
    Parameters:
    
    udfName - (undocumented)
    
    cols - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - col
```
public static Column col(String colName)
```
    Returns a Column based on the given column name.
    
    Parameters:
    
    colName - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.3.0
  - column
```
public static Column column(String colName)
```
    Returns a Column based on the given column name. Alias of col.
    
    Parameters:
    
    colName - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.3.0
  - lit
```
public static Column lit(Object literal)
```
    Creates a Column of literal value.
    The passed in object is returned directly if it is already a Column. If the object is a Scala Symbol, it is converted into a Column also. Otherwise, a new Column is created to represent the literal value.
    
    Parameters:
    
    literal - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.3.0
  - typedLit
```
public static <T> Column typedLit(T literal,
                                  scala.reflect.api.TypeTags.TypeTag<T> evidence$1)
```
    Creates a Column of literal value.
    The passed in object is returned directly if it is already a Column. If the object is a Scala Symbol, it is converted into a Column also. Otherwise, a new Column is created to represent the literal value. The difference between this function and lit is that this function can handle parameterized scala types e.g.: List, Seq and Map.
    
    Parameters:
    
    literal - (undocumented)
    
    evidence$1 - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.2.0
  - asc
```
public static Column asc(String columnName)
```
    Returns a sort expression based on ascending order of the column.
```
   df.sort(asc("dept"), desc("age"))
 
```
    Parameters:
    
    columnName - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.3.0
  - asc_nulls_first
```
public static Column asc_nulls_first(String columnName)
```
    Returns a sort expression based on ascending order of the column, and null values return before non-null values.
```
   df.sort(asc_nulls_first("dept"), desc("age"))
 
```
    Parameters:
    
    columnName - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.1.0
  - asc_nulls_last
```
public static Column asc_nulls_last(String columnName)
```
    Returns a sort expression based on ascending order of the column, and null values appear after non-null values.
```
   df.sort(asc_nulls_last("dept"), desc("age"))
 
```
    Parameters:
    
    columnName - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.1.0
  - desc
```
public static Column desc(String columnName)
```
    Returns a sort expression based on the descending order of the column.
```
   df.sort(asc("dept"), desc("age"))
 
```
    Parameters:
    
    columnName - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.3.0
  - desc_nulls_first
```
public static Column desc_nulls_first(String columnName)
```
    Returns a sort expression based on the descending order of the column, and null values appear before non-null values.
```
   df.sort(asc("dept"), desc_nulls_first("age"))
 
```
    Parameters:
    
    columnName - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.1.0
  - desc_nulls_last
```
public static Column desc_nulls_last(String columnName)
```
    Returns a sort expression based on the descending order of the column, and null values appear after non-null values.
```
   df.sort(asc("dept"), desc_nulls_last("age"))
 
```
    Parameters:
    
    columnName - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.1.0
  - approxCountDistinct
```
public static Column approxCountDistinct(Column e)
```
    Deprecated. Use approx_count_distinct. Since 2.1.0.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.3.0
  - approxCountDistinct
```
public static Column approxCountDistinct(String columnName)
```
    Deprecated. Use approx_count_distinct. Since 2.1.0.
    
    Parameters:
    
    columnName - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.3.0
  - approxCountDistinct
```
public static Column approxCountDistinct(Column e,
                                         double rsd)
```
    Deprecated. Use approx_count_distinct. Since 2.1.0.
    
    Parameters:
    
    e - (undocumented)
    
    rsd - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.3.0
  - approxCountDistinct
```
public static Column approxCountDistinct(String columnName,
                                         double rsd)
```
    Deprecated. Use approx_count_distinct. Since 2.1.0.
    
    Parameters:
    
    columnName - (undocumented)
    
    rsd - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.3.0
  - approx_count_distinct
```
public static Column approx_count_distinct(Column e)
```
    Aggregate function: returns the approximate number of distinct items in a group.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.1.0
  - approx_count_distinct
```
public static Column approx_count_distinct(String columnName)
```
    Aggregate function: returns the approximate number of distinct items in a group.
    
    Parameters:
    
    columnName - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.1.0
  - approx_count_distinct
```
public static Column approx_count_distinct(Column e,
                                           double rsd)
```
    Aggregate function: returns the approximate number of distinct items in a group.
    
    Parameters:
    
    rsd - maximum relative standard deviation allowed (default = 0.05)
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.1.0
  - approx_count_distinct
```
public static Column approx_count_distinct(String columnName,
                                           double rsd)
```
    Aggregate function: returns the approximate number of distinct items in a group.
    
    Parameters:
    
    rsd - maximum relative standard deviation allowed (default = 0.05)
    
    columnName - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.1.0
  - avg
```
public static Column avg(Column e)
```
    Aggregate function: returns the average of the values in a group.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.3.0
  - avg
```
public static Column avg(String columnName)
```
    Aggregate function: returns the average of the values in a group.
    
    Parameters:
    
    columnName - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.3.0
  - collect_list
```
public static Column collect_list(Column e)
```
    Aggregate function: returns a list of objects with duplicates.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.6.0
    
    Note:
    
    The function is non-deterministic because the order of collected results depends on the order of the rows which may be non-deterministic after a shuffle.
  - collect_list
```
public static Column collect_list(String columnName)
```
    Aggregate function: returns a list of objects with duplicates.
    
    Parameters:
    
    columnName - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.6.0
    
    Note:
    
    The function is non-deterministic because the order of collected results depends on the order of the rows which may be non-deterministic after a shuffle.
  - collect_set
```
public static Column collect_set(Column e)
```
    Aggregate function: returns a set of objects with duplicate elements eliminated.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.6.0
    
    Note:
    
    The function is non-deterministic because the order of collected results depends on the order of the rows which may be non-deterministic after a shuffle.
  - collect_set
```
public static Column collect_set(String columnName)
```
    Aggregate function: returns a set of objects with duplicate elements eliminated.
    
    Parameters:
    
    columnName - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.6.0
    
    Note:
    
    The function is non-deterministic because the order of collected results depends on the order of the rows which may be non-deterministic after a shuffle.
  - corr
```
public static Column corr(Column column1,
                          Column column2)
```
    Aggregate function: returns the Pearson Correlation Coefficient for two columns.
    
    Parameters:
    
    column1 - (undocumented)
    
    column2 - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.6.0
  - corr
```
public static Column corr(String columnName1,
                          String columnName2)
```
    Aggregate function: returns the Pearson Correlation Coefficient for two columns.
    
    Parameters:
    
    columnName1 - (undocumented)
    
    columnName2 - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.6.0
  - count
```
public static Column count(Column e)
```
    Aggregate function: returns the number of items in a group.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.3.0
  - count
```
public static TypedColumn<Object,Object> count(String columnName)
```
    Aggregate function: returns the number of items in a group.
    
    Parameters:
    
    columnName - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.3.0
  - countDistinct
```
public static Column countDistinct(Column expr,
                                   scala.collection.Seq<Column> exprs)
```
    Aggregate function: returns the number of distinct items in a group.
    
    Parameters:
    
    expr - (undocumented)
    
    exprs - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.3.0
  - countDistinct
```
public static Column countDistinct(String columnName,
                                   scala.collection.Seq<String> columnNames)
```
    Aggregate function: returns the number of distinct items in a group.
    
    Parameters:
    
    columnName - (undocumented)
    
    columnNames - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.3.0
  - covar_pop
```
public static Column covar_pop(Column column1,
                               Column column2)
```
    Aggregate function: returns the population covariance for two columns.
    
    Parameters:
    
    column1 - (undocumented)
    
    column2 - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.0.0
  - covar_pop
```
public static Column covar_pop(String columnName1,
                               String columnName2)
```
    Aggregate function: returns the population covariance for two columns.
    
    Parameters:
    
    columnName1 - (undocumented)
    
    columnName2 - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.0.0
  - covar_samp
```
public static Column covar_samp(Column column1,
                                Column column2)
```
    Aggregate function: returns the sample covariance for two columns.
    
    Parameters:
    
    column1 - (undocumented)
    
    column2 - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.0.0
  - covar_samp
```
public static Column covar_samp(String columnName1,
                                String columnName2)
```
    Aggregate function: returns the sample covariance for two columns.
    
    Parameters:
    
    columnName1 - (undocumented)
    
    columnName2 - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.0.0
  - first
```
public static Column first(Column e,
                           boolean ignoreNulls)
```
    Aggregate function: returns the first value in a group.
    The function by default returns the first values it sees. It will return the first non-null value it sees when ignoreNulls is set to true. If all values are null, then null is returned.
    
    Parameters:
    
    e - (undocumented)
    
    ignoreNulls - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.0.0
    
    Note:
    
    The function is non-deterministic because its results depends on the order of the rows which may be non-deterministic after a shuffle.
  - first
```
public static Column first(String columnName,
                           boolean ignoreNulls)
```
    Aggregate function: returns the first value of a column in a group.
    The function by default returns the first values it sees. It will return the first non-null value it sees when ignoreNulls is set to true. If all values are null, then null is returned.
    
    Parameters:
    
    columnName - (undocumented)
    
    ignoreNulls - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.0.0
    
    Note:
    
    The function is non-deterministic because its results depends on the order of the rows which may be non-deterministic after a shuffle.
  - first
```
public static Column first(Column e)
```
    Aggregate function: returns the first value in a group.
    The function by default returns the first values it sees. It will return the first non-null value it sees when ignoreNulls is set to true. If all values are null, then null is returned.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.3.0
    
    Note:
    
    The function is non-deterministic because its results depends on the order of the rows which may be non-deterministic after a shuffle.
  - first
```
public static Column first(String columnName)
```
    Aggregate function: returns the first value of a column in a group.
    The function by default returns the first values it sees. It will return the first non-null value it sees when ignoreNulls is set to true. If all values are null, then null is returned.
    
    Parameters:
    
    columnName - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.3.0
    
    Note:
    
    The function is non-deterministic because its results depends on the order of the rows which may be non-deterministic after a shuffle.
  - grouping
```
public static Column grouping(Column e)
```
    Aggregate function: indicates whether a specified column in a GROUP BY list is aggregated or not, returns 1 for aggregated or 0 for not aggregated in the result set.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.0.0
  - grouping
```
public static Column grouping(String columnName)
```
    Aggregate function: indicates whether a specified column in a GROUP BY list is aggregated or not, returns 1 for aggregated or 0 for not aggregated in the result set.
    
    Parameters:
    
    columnName - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.0.0
  - grouping_id
```
public static Column grouping_id(scala.collection.Seq<Column> cols)
```
    Aggregate function: returns the level of grouping, equals to
```
   (grouping(c1) <<; (n-1)) + (grouping(c2) <<; (n-2)) + ... + grouping(cn)
 
```
    Parameters:
    
    cols - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.0.0
    
    Note:
    
    The list of columns should match with grouping columns exactly, or empty (means all the grouping columns).
  - grouping_id
```
public static Column grouping_id(String colName,
                                 scala.collection.Seq<String> colNames)
```
    Aggregate function: returns the level of grouping, equals to
```
   (grouping(c1) <<; (n-1)) + (grouping(c2) <<; (n-2)) + ... + grouping(cn)
 
```
    Parameters:
    
    colName - (undocumented)
    
    colNames - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.0.0
    
    Note:
    
    The list of columns should match with grouping columns exactly.
  - kurtosis
```
public static Column kurtosis(Column e)
```
    Aggregate function: returns the kurtosis of the values in a group.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.6.0
  - kurtosis
```
public static Column kurtosis(String columnName)
```
    Aggregate function: returns the kurtosis of the values in a group.
    
    Parameters:
    
    columnName - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.6.0
  - last
```
public static Column last(Column e,
                          boolean ignoreNulls)
```
    Aggregate function: returns the last value in a group.
    The function by default returns the last values it sees. It will return the last non-null value it sees when ignoreNulls is set to true. If all values are null, then null is returned.
    
    Parameters:
    
    e - (undocumented)
    
    ignoreNulls - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.0.0
    
    Note:
    
    The function is non-deterministic because its results depends on the order of the rows which may be non-deterministic after a shuffle.
  - last
```
public static Column last(String columnName,
                          boolean ignoreNulls)
```
    Aggregate function: returns the last value of the column in a group.
    The function by default returns the last values it sees. It will return the last non-null value it sees when ignoreNulls is set to true. If all values are null, then null is returned.
    
    Parameters:
    
    columnName - (undocumented)
    
    ignoreNulls - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.0.0
    
    Note:
    
    The function is non-deterministic because its results depends on the order of the rows which may be non-deterministic after a shuffle.
  - last
```
public static Column last(Column e)
```
    Aggregate function: returns the last value in a group.
    The function by default returns the last values it sees. It will return the last non-null value it sees when ignoreNulls is set to true. If all values are null, then null is returned.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.3.0
    
    Note:
    
    The function is non-deterministic because its results depends on the order of the rows which may be non-deterministic after a shuffle.
  - last
```
public static Column last(String columnName)
```
    Aggregate function: returns the last value of the column in a group.
    The function by default returns the last values it sees. It will return the last non-null value it sees when ignoreNulls is set to true. If all values are null, then null is returned.
    
    Parameters:
    
    columnName - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.3.0
    
    Note:
    
    The function is non-deterministic because its results depends on the order of the rows which may be non-deterministic after a shuffle.
  - max
```
public static Column max(Column e)
```
    Aggregate function: returns the maximum value of the expression in a group.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.3.0
  - max
```
public static Column max(String columnName)
```
    Aggregate function: returns the maximum value of the column in a group.
    
    Parameters:
    
    columnName - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.3.0
  - mean
```
public static Column mean(Column e)
```
    Aggregate function: returns the average of the values in a group. Alias for avg.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - mean
```
public static Column mean(String columnName)
```
    Aggregate function: returns the average of the values in a group. Alias for avg.
    
    Parameters:
    
    columnName - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - min
```
public static Column min(Column e)
```
    Aggregate function: returns the minimum value of the expression in a group.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.3.0
  - min
```
public static Column min(String columnName)
```
    Aggregate function: returns the minimum value of the column in a group.
    
    Parameters:
    
    columnName - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.3.0
  - skewness
```
public static Column skewness(Column e)
```
    Aggregate function: returns the skewness of the values in a group.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.6.0
  - skewness
```
public static Column skewness(String columnName)
```
    Aggregate function: returns the skewness of the values in a group.
    
    Parameters:
    
    columnName - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.6.0
  - stddev
```
public static Column stddev(Column e)
```
    Aggregate function: alias for stddev_samp.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.6.0
  - stddev
```
public static Column stddev(String columnName)
```
    Aggregate function: alias for stddev_samp.
    
    Parameters:
    
    columnName - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.6.0
  - stddev_samp
```
public static Column stddev_samp(Column e)
```
    Aggregate function: returns the sample standard deviation of the expression in a group.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.6.0
  - stddev_samp
```
public static Column stddev_samp(String columnName)
```
    Aggregate function: returns the sample standard deviation of the expression in a group.
    
    Parameters:
    
    columnName - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.6.0
  - stddev_pop
```
public static Column stddev_pop(Column e)
```
    Aggregate function: returns the population standard deviation of the expression in a group.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.6.0
  - stddev_pop
```
public static Column stddev_pop(String columnName)
```
    Aggregate function: returns the population standard deviation of the expression in a group.
    
    Parameters:
    
    columnName - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.6.0
  - sum
```
public static Column sum(Column e)
```
    Aggregate function: returns the sum of all values in the expression.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.3.0
  - sum
```
public static Column sum(String columnName)
```
    Aggregate function: returns the sum of all values in the given column.
    
    Parameters:
    
    columnName - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.3.0
  - sumDistinct
```
public static Column sumDistinct(Column e)
```
    Aggregate function: returns the sum of distinct values in the expression.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.3.0
  - sumDistinct
```
public static Column sumDistinct(String columnName)
```
    Aggregate function: returns the sum of distinct values in the expression.
    
    Parameters:
    
    columnName - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.3.0
  - variance
```
public static Column variance(Column e)
```
    Aggregate function: alias for var_samp.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.6.0
  - variance
```
public static Column variance(String columnName)
```
    Aggregate function: alias for var_samp.
    
    Parameters:
    
    columnName - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.6.0
  - var_samp
```
public static Column var_samp(Column e)
```
    Aggregate function: returns the unbiased variance of the values in a group.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.6.0
  - var_samp
```
public static Column var_samp(String columnName)
```
    Aggregate function: returns the unbiased variance of the values in a group.
    
    Parameters:
    
    columnName - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.6.0
  - var_pop
```
public static Column var_pop(Column e)
```
    Aggregate function: returns the population variance of the values in a group.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.6.0
  - var_pop
```
public static Column var_pop(String columnName)
```
    Aggregate function: returns the population variance of the values in a group.
    
    Parameters:
    
    columnName - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.6.0
  - cume_dist
```
public static Column cume_dist()
```
    Window function: returns the cumulative distribution of values within a window partition, i.e. the fraction of rows that are below the current row.
```
   N = total number of rows in the partition
   cumeDist(x) = number of values before (and including) x / N
 
```
    Returns:
    
    (undocumented)
    
    Since:
    
    1.6.0
  - dense_rank
```
public static Column dense_rank()
```
    Window function: returns the rank of rows within a window partition, without any gaps.
    The difference between rank and dense_rank is that denseRank leaves no gaps in ranking sequence when there are ties. That is, if you were ranking a competition using dense_rank and had three people tie for second place, you would say that all three were in second place and that the next person came in third. Rank would give me sequential numbers, making the person that came in third place (after the ties) would register as coming in fifth.
    This is equivalent to the DENSE_RANK function in SQL.
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.6.0
  - lag
```
public static Column lag(Column e,
                         int offset)
```
    Window function: returns the value that is offset rows before the current row, and null if there is less than offset rows before the current row. For example, an offset of one will return the previous row at any given point in the window partition.
    This is equivalent to the LAG function in SQL.
    
    Parameters:
    
    e - (undocumented)
    
    offset - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - lag
```
public static Column lag(String columnName,
                         int offset)
```
    Window function: returns the value that is offset rows before the current row, and null if there is less than offset rows before the current row. For example, an offset of one will return the previous row at any given point in the window partition.
    This is equivalent to the LAG function in SQL.
    
    Parameters:
    
    columnName - (undocumented)
    
    offset - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - lag
```
public static Column lag(String columnName,
                         int offset,
                         Object defaultValue)
```
    Window function: returns the value that is offset rows before the current row, and defaultValue if there is less than offset rows before the current row. For example, an offset of one will return the previous row at any given point in the window partition.
    This is equivalent to the LAG function in SQL.
    
    Parameters:
    
    columnName - (undocumented)
    
    offset - (undocumented)
    
    defaultValue - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - lag
```
public static Column lag(Column e,
                         int offset,
                         Object defaultValue)
```
    Window function: returns the value that is offset rows before the current row, and defaultValue if there is less than offset rows before the current row. For example, an offset of one will return the previous row at any given point in the window partition.
    This is equivalent to the LAG function in SQL.
    
    Parameters:
    
    e - (undocumented)
    
    offset - (undocumented)
    
    defaultValue - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - lead
```
public static Column lead(String columnName,
                          int offset)
```
    Window function: returns the value that is offset rows after the current row, and null if there is less than offset rows after the current row. For example, an offset of one will return the next row at any given point in the window partition.
    This is equivalent to the LEAD function in SQL.
    
    Parameters:
    
    columnName - (undocumented)
    
    offset - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - lead
```
public static Column lead(Column e,
                          int offset)
```
    Window function: returns the value that is offset rows after the current row, and null if there is less than offset rows after the current row. For example, an offset of one will return the next row at any given point in the window partition.
    This is equivalent to the LEAD function in SQL.
    
    Parameters:
    
    e - (undocumented)
    
    offset - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - lead
```
public static Column lead(String columnName,
                          int offset,
                          Object defaultValue)
```
    Window function: returns the value that is offset rows after the current row, and defaultValue if there is less than offset rows after the current row. For example, an offset of one will return the next row at any given point in the window partition.
    This is equivalent to the LEAD function in SQL.
    
    Parameters:
    
    columnName - (undocumented)
    
    offset - (undocumented)
    
    defaultValue - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - lead
```
public static Column lead(Column e,
                          int offset,
                          Object defaultValue)
```
    Window function: returns the value that is offset rows after the current row, and defaultValue if there is less than offset rows after the current row. For example, an offset of one will return the next row at any given point in the window partition.
    This is equivalent to the LEAD function in SQL.
    
    Parameters:
    
    e - (undocumented)
    
    offset - (undocumented)
    
    defaultValue - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - ntile
```
public static Column ntile(int n)
```
    Window function: returns the ntile group id (from 1 to n inclusive) in an ordered window partition. For example, if n is 4, the first quarter of the rows will get value 1, the second quarter will get 2, the third quarter will get 3, and the last quarter will get 4.
    This is equivalent to the NTILE function in SQL.
    
    Parameters:
    
    n - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - percent_rank
```
public static Column percent_rank()
```
    Window function: returns the relative rank (i.e. percentile) of rows within a window partition.
    This is computed by:
```
   (rank of row in its partition - 1) / (number of rows in the partition - 1)
 
```
    This is equivalent to the PERCENT_RANK function in SQL.
    Returns:
    
    (undocumented)
    
    Since:
    
    1.6.0
  - rank
```
public static Column rank()
```
    Window function: returns the rank of rows within a window partition.
    The difference between rank and dense_rank is that dense_rank leaves no gaps in ranking sequence when there are ties. That is, if you were ranking a competition using dense_rank and had three people tie for second place, you would say that all three were in second place and that the next person came in third. Rank would give me sequential numbers, making the person that came in third place (after the ties) would register as coming in fifth.
    This is equivalent to the RANK function in SQL.
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - row_number
```
public static Column row_number()
```
    Window function: returns a sequential number starting at 1 within a window partition.
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.6.0
  - array
```
public static Column array(scala.collection.Seq<Column> cols)
```
    Creates a new array column. The input columns must all have the same data type.
    
    Parameters:
    
    cols - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - array
```
public static Column array(String colName,
                           scala.collection.Seq<String> colNames)
```
    Creates a new array column. The input columns must all have the same data type.
    
    Parameters:
    
    colName - (undocumented)
    
    colNames - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - map
```
public static Column map(scala.collection.Seq<Column> cols)
```
    Creates a new map column. The input columns must be grouped as key-value pairs, e.g. (key1, value1, key2, value2, ...). The key columns must all have the same data type, and can't be null. The value columns must all have the same data type.
    
    Parameters:
    
    cols - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.0
  - map_from_arrays
```
public static Column map_from_arrays(Column keys,
                                     Column values)
```
    Creates a new map column. The array in the first column is used for keys. The array in the second column is used for values. All elements in the array for key should not be null.
    
    Parameters:
    
    keys - (undocumented)
    
    values - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.4
  - broadcast
```
public static <T> Dataset<T> broadcast(Dataset<T> df)
```
    Marks a DataFrame as small enough for use in broadcast joins.
    The following example marks the right DataFrame for broadcast hash join using joinKey.
```
   // left and right are DataFrames
   left.join(broadcast(right), "joinKey")
 
```
    Parameters:
    
    df - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - coalesce
```
public static Column coalesce(scala.collection.Seq<Column> e)
```
    Returns the first column that is not null, or null if all inputs are null.
    For example, coalesce(a, b, c) will return a if a is not null, or b if a is null and b is not null, or c if both a and b are null but c is not null.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.3.0
  - input_file_name
```
public static Column input_file_name()
```
    Creates a string column for the file name of the current Spark task.
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.6.0
  - isnan
```
public static Column isnan(Column e)
```
    Return true iff the column is NaN.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.6.0
  - isnull
```
public static Column isnull(Column e)
```
    Return true iff the column is null.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.6.0
  - monotonicallyIncreasingId
```
public static Column monotonicallyIncreasingId()
```
    Deprecated. Use monotonically_increasing_id(). Since 2.0.0.
    A column expression that generates monotonically increasing 64-bit integers.
    The generated ID is guaranteed to be monotonically increasing and unique, but not consecutive. The current implementation puts the partition ID in the upper 31 bits, and the record number within each partition in the lower 33 bits. The assumption is that the data frame has less than 1 billion partitions, and each partition has less than 8 billion records.
    As an example, consider a DataFrame with two partitions, each with 3 records. This expression would return the following IDs:
```
 0, 1, 2, 8589934592 (1L << 33), 8589934593, 8589934594.
 
```
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - monotonically_increasing_id
```
public static Column monotonically_increasing_id()
```
    A column expression that generates monotonically increasing 64-bit integers.
    The generated ID is guaranteed to be monotonically increasing and unique, but not consecutive. The current implementation puts the partition ID in the upper 31 bits, and the record number within each partition in the lower 33 bits. The assumption is that the data frame has less than 1 billion partitions, and each partition has less than 8 billion records.
    As an example, consider a DataFrame with two partitions, each with 3 records. This expression would return the following IDs:
```
 0, 1, 2, 8589934592 (1L << 33), 8589934593, 8589934594.
 
```
    Returns:
    
    (undocumented)
    
    Since:
    
    1.6.0
  - nanvl
```
public static Column nanvl(Column col1,
                           Column col2)
```
    Returns col1 if it is not NaN, or col2 if col1 is NaN.
    Both inputs should be floating point columns (DoubleType or FloatType).
    
    Parameters:
    
    col1 - (undocumented)
    
    col2 - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - negate
```
public static Column negate(Column e)
```
    Unary minus, i.e. negate the expression.
```
   // Select the amount column and negates all values.
   // Scala:
   df.select( -df("amount") )

   // Java:
   df.select( negate(df.col("amount")) );
 
```
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.3.0
  - not
```
public static Column not(Column e)
```
    Inversion of boolean expression, i.e. NOT.
```
   // Scala: select rows that are not active (isActive === false)
   df.filter( !df("isActive") )

   // Java:
   df.filter( not(df.col("isActive")) );
 
```
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.3.0
  - rand
```
public static Column rand(long seed)
```
    Generate a random column with independent and identically distributed (i.i.d.) samples uniformly distributed in [0.0, 1.0).
    
    Parameters:
    
    seed - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
    
    Note:
    
    The function is non-deterministic in general case.
  - rand
```
public static Column rand()
```
    Generate a random column with independent and identically distributed (i.i.d.) samples uniformly distributed in [0.0, 1.0).
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
    
    Note:
    
    The function is non-deterministic in general case.
  - randn
```
public static Column randn(long seed)
```
    Generate a column with independent and identically distributed (i.i.d.) samples from the standard normal distribution.
    
    Parameters:
    
    seed - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
    
    Note:
    
    The function is non-deterministic in general case.
  - randn
```
public static Column randn()
```
    Generate a column with independent and identically distributed (i.i.d.) samples from the standard normal distribution.
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
    
    Note:
    
    The function is non-deterministic in general case.
  - spark_partition_id
```
public static Column spark_partition_id()
```
    Partition ID.
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.6.0
    
    Note:
    
    This is non-deterministic because it depends on data partitioning and task scheduling.
  - sqrt
```
public static Column sqrt(Column e)
```
    Computes the square root of the specified float value.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.3.0
  - sqrt
```
public static Column sqrt(String colName)
```
    Computes the square root of the specified float value.
    
    Parameters:
    
    colName - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - struct
```
public static Column struct(scala.collection.Seq<Column> cols)
```
    Creates a new struct column. If the input column is a column in a DataFrame, or a derived column expression that is named (i.e. aliased), its name would be retained as the StructField's name, otherwise, the newly generated StructField's name would be auto generated as col with a suffix index + 1, i.e. col1, col2, col3, ...
    
    Parameters:
    
    cols - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - struct
```
public static Column struct(String colName,
                            scala.collection.Seq<String> colNames)
```
    Creates a new struct column that composes multiple input columns.
    
    Parameters:
    
    colName - (undocumented)
    
    colNames - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - when
```
public static Column when(Column condition,
                          Object value)
```
    Evaluates a list of conditions and returns one of multiple possible result expressions. If otherwise is not defined at the end, null is returned for unmatched conditions.
```
   // Example: encoding gender string column into integer.

   // Scala:
   people.select(when(people("gender") === "male", 0)
     .when(people("gender") === "female", 1)
     .otherwise(2))

   // Java:
   people.select(when(col("gender").equalTo("male"), 0)
     .when(col("gender").equalTo("female"), 1)
     .otherwise(2))
 
```
    Parameters:
    
    condition - (undocumented)
    
    value - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - bitwiseNOT
```
public static Column bitwiseNOT(Column e)
```
    Computes bitwise NOT (~) of a number.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - expr
```
public static Column expr(String expr)
```
    Parses the expression string into the column that it represents, similar to Dataset.selectExpr(java.lang.String...).
```
   // get the number of words of each length
   df.groupBy(expr("length(word)")).count()
 
```
    Parameters:
    
    expr - (undocumented)
    
    Returns:
    
    (undocumented)
  - abs
```
public static Column abs(Column e)
```
    Computes the absolute value of a numeric value.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.3.0
  - acos
```
public static Column acos(Column e)
```
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    inverse cosine of e in radians, as if computed by java.lang.Math.acos
    
    Since:
    
    1.4.0
  - acos
```
public static Column acos(String columnName)
```
    Parameters:
    
    columnName - (undocumented)
    
    Returns:
    
    inverse cosine of columnName, as if computed by java.lang.Math.acos
    
    Since:
    
    1.4.0
  - asin
```
public static Column asin(Column e)
```
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    inverse sine of e in radians, as if computed by java.lang.Math.asin
    
    Since:
    
    1.4.0
  - asin
```
public static Column asin(String columnName)
```
    Parameters:
    
    columnName - (undocumented)
    
    Returns:
    
    inverse sine of columnName, as if computed by java.lang.Math.asin
    
    Since:
    
    1.4.0
  - atan
```
public static Column atan(Column e)
```
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    inverse tangent of e, as if computed by java.lang.Math.atan
    
    Since:
    
    1.4.0
  - atan
```
public static Column atan(String columnName)
```
    Parameters:
    
    columnName - (undocumented)
    
    Returns:
    
    inverse tangent of columnName, as if computed by java.lang.Math.atan
    
    Since:
    
    1.4.0
  - atan2
```
public static Column atan2(Column y,
                           Column x)
```
    Parameters:
    
    y - coordinate on y-axis
    
    x - coordinate on x-axis
    
    Returns:
    
    the theta component of the point (r, theta) in polar coordinates that corresponds to the point (x, y) in Cartesian coordinates, as if computed by java.lang.Math.atan2
    
    Since:
    
    1.4.0
  - atan2
```
public static Column atan2(Column y,
                           String xName)
```
    Parameters:
    
    y - coordinate on y-axis
    
    xName - coordinate on x-axis
    
    Returns:
    
    the theta component of the point (r, theta) in polar coordinates that corresponds to the point (x, y) in Cartesian coordinates, as if computed by java.lang.Math.atan2
    
    Since:
    
    1.4.0
  - atan2
```
public static Column atan2(String yName,
                           Column x)
```
    Parameters:
    
    yName - coordinate on y-axis
    
    x - coordinate on x-axis
    
    Returns:
    
    the theta component of the point (r, theta) in polar coordinates that corresponds to the point (x, y) in Cartesian coordinates, as if computed by java.lang.Math.atan2
    
    Since:
    
    1.4.0
  - atan2
```
public static Column atan2(String yName,
                           String xName)
```
    Parameters:
    
    yName - coordinate on y-axis
    
    xName - coordinate on x-axis
    
    Returns:
    
    the theta component of the point (r, theta) in polar coordinates that corresponds to the point (x, y) in Cartesian coordinates, as if computed by java.lang.Math.atan2
    
    Since:
    
    1.4.0
  - atan2
```
public static Column atan2(Column y,
                           double xValue)
```
    Parameters:
    
    y - coordinate on y-axis
    
    xValue - coordinate on x-axis
    
    Returns:
    
    the theta component of the point (r, theta) in polar coordinates that corresponds to the point (x, y) in Cartesian coordinates, as if computed by java.lang.Math.atan2
    
    Since:
    
    1.4.0
  - atan2
```
public static Column atan2(String yName,
                           double xValue)
```
    Parameters:
    
    yName - coordinate on y-axis
    
    xValue - coordinate on x-axis
    
    Returns:
    
    the theta component of the point (r, theta) in polar coordinates that corresponds to the point (x, y) in Cartesian coordinates, as if computed by java.lang.Math.atan2
    
    Since:
    
    1.4.0
  - atan2
```
public static Column atan2(double yValue,
                           Column x)
```
    Parameters:
    
    yValue - coordinate on y-axis
    
    x - coordinate on x-axis
    
    Returns:
    
    the theta component of the point (r, theta) in polar coordinates that corresponds to the point (x, y) in Cartesian coordinates, as if computed by java.lang.Math.atan2
    
    Since:
    
    1.4.0
  - atan2
```
public static Column atan2(double yValue,
                           String xName)
```
    Parameters:
    
    yValue - coordinate on y-axis
    
    xName - coordinate on x-axis
    
    Returns:
    
    the theta component of the point (r, theta) in polar coordinates that corresponds to the point (x, y) in Cartesian coordinates, as if computed by java.lang.Math.atan2
    
    Since:
    
    1.4.0
  - bin
```
public static Column bin(Column e)
```
    An expression that returns the string representation of the binary value of the given long column. For example, bin("12") returns "1100".
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - bin
```
public static Column bin(String columnName)
```
    An expression that returns the string representation of the binary value of the given long column. For example, bin("12") returns "1100".
    
    Parameters:
    
    columnName - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - cbrt
```
public static Column cbrt(Column e)
```
    Computes the cube-root of the given value.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - cbrt
```
public static Column cbrt(String columnName)
```
    Computes the cube-root of the given column.
    
    Parameters:
    
    columnName - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - ceil
```
public static Column ceil(Column e)
```
    Computes the ceiling of the given value.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - ceil
```
public static Column ceil(String columnName)
```
    Computes the ceiling of the given column.
    
    Parameters:
    
    columnName - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - conv
```
public static Column conv(Column num,
                          int fromBase,
                          int toBase)
```
    Convert a number in a string column from one base to another.
    
    Parameters:
    
    num - (undocumented)
    
    fromBase - (undocumented)
    
    toBase - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - cos
```
public static Column cos(Column e)
```
    Parameters:
    
    e - angle in radians
    
    Returns:
    
    cosine of the angle, as if computed by java.lang.Math.cos
    
    Since:
    
    1.4.0
  - cos
```
public static Column cos(String columnName)
```
    Parameters:
    
    columnName - angle in radians
    
    Returns:
    
    cosine of the angle, as if computed by java.lang.Math.cos
    
    Since:
    
    1.4.0
  - cosh
```
public static Column cosh(Column e)
```
    Parameters:
    
    e - hyperbolic angle
    
    Returns:
    
    hyperbolic cosine of the angle, as if computed by java.lang.Math.cosh
    
    Since:
    
    1.4.0
  - cosh
```
public static Column cosh(String columnName)
```
    Parameters:
    
    columnName - hyperbolic angle
    
    Returns:
    
    hyperbolic cosine of the angle, as if computed by java.lang.Math.cosh
    
    Since:
    
    1.4.0
  - exp
```
public static Column exp(Column e)
```
    Computes the exponential of the given value.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - exp
```
public static Column exp(String columnName)
```
    Computes the exponential of the given column.
    
    Parameters:
    
    columnName - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - expm1
```
public static Column expm1(Column e)
```
    Computes the exponential of the given value minus one.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - expm1
```
public static Column expm1(String columnName)
```
    Computes the exponential of the given column minus one.
    
    Parameters:
    
    columnName - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - factorial
```
public static Column factorial(Column e)
```
    Computes the factorial of the given value.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - floor
```
public static Column floor(Column e)
```
    Computes the floor of the given value.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - floor
```
public static Column floor(String columnName)
```
    Computes the floor of the given column.
    
    Parameters:
    
    columnName - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - greatest
```
public static Column greatest(scala.collection.Seq<Column> exprs)
```
    Returns the greatest value of the list of values, skipping null values. This function takes at least 2 parameters. It will return null iff all parameters are null.
    
    Parameters:
    
    exprs - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - greatest
```
public static Column greatest(String columnName,
                              scala.collection.Seq<String> columnNames)
```
    Returns the greatest value of the list of column names, skipping null values. This function takes at least 2 parameters. It will return null iff all parameters are null.
    
    Parameters:
    
    columnName - (undocumented)
    
    columnNames - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - hex
```
public static Column hex(Column column)
```
    Computes hex value of the given column.
    
    Parameters:
    
    column - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - unhex
```
public static Column unhex(Column column)
```
    Inverse of hex. Interprets each pair of characters as a hexadecimal number and converts to the byte representation of number.
    
    Parameters:
    
    column - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - hypot
```
public static Column hypot(Column l,
                           Column r)
```
    Computes sqrt(a^2^ + b^2^) without intermediate overflow or underflow.
    
    Parameters:
    
    l - (undocumented)
    
    r - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - hypot
```
public static Column hypot(Column l,
                           String rightName)
```
    Computes sqrt(a^2^ + b^2^) without intermediate overflow or underflow.
    
    Parameters:
    
    l - (undocumented)
    
    rightName - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - hypot
```
public static Column hypot(String leftName,
                           Column r)
```
    Computes sqrt(a^2^ + b^2^) without intermediate overflow or underflow.
    
    Parameters:
    
    leftName - (undocumented)
    
    r - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - hypot
```
public static Column hypot(String leftName,
                           String rightName)
```
    Computes sqrt(a^2^ + b^2^) without intermediate overflow or underflow.
    
    Parameters:
    
    leftName - (undocumented)
    
    rightName - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - hypot
```
public static Column hypot(Column l,
                           double r)
```
    Computes sqrt(a^2^ + b^2^) without intermediate overflow or underflow.
    
    Parameters:
    
    l - (undocumented)
    
    r - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - hypot
```
public static Column hypot(String leftName,
                           double r)
```
    Computes sqrt(a^2^ + b^2^) without intermediate overflow or underflow.
    
    Parameters:
    
    leftName - (undocumented)
    
    r - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - hypot
```
public static Column hypot(double l,
                           Column r)
```
    Computes sqrt(a^2^ + b^2^) without intermediate overflow or underflow.
    
    Parameters:
    
    l - (undocumented)
    
    r - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - hypot
```
public static Column hypot(double l,
                           String rightName)
```
    Computes sqrt(a^2^ + b^2^) without intermediate overflow or underflow.
    
    Parameters:
    
    l - (undocumented)
    
    rightName - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - least
```
public static Column least(scala.collection.Seq<Column> exprs)
```
    Returns the least value of the list of values, skipping null values. This function takes at least 2 parameters. It will return null iff all parameters are null.
    
    Parameters:
    
    exprs - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - least
```
public static Column least(String columnName,
                           scala.collection.Seq<String> columnNames)
```
    Returns the least value of the list of column names, skipping null values. This function takes at least 2 parameters. It will return null iff all parameters are null.
    
    Parameters:
    
    columnName - (undocumented)
    
    columnNames - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - log
```
public static Column log(Column e)
```
    Computes the natural logarithm of the given value.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - log
```
public static Column log(String columnName)
```
    Computes the natural logarithm of the given column.
    
    Parameters:
    
    columnName - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - log
```
public static Column log(double base,
                         Column a)
```
    Returns the first argument-base logarithm of the second argument.
    
    Parameters:
    
    base - (undocumented)
    
    a - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - log
```
public static Column log(double base,
                         String columnName)
```
    Returns the first argument-base logarithm of the second argument.
    
    Parameters:
    
    base - (undocumented)
    
    columnName - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - log10
```
public static Column log10(Column e)
```
    Computes the logarithm of the given value in base 10.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - log10
```
public static Column log10(String columnName)
```
    Computes the logarithm of the given value in base 10.
    
    Parameters:
    
    columnName - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - log1p
```
public static Column log1p(Column e)
```
    Computes the natural logarithm of the given value plus one.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - log1p
```
public static Column log1p(String columnName)
```
    Computes the natural logarithm of the given column plus one.
    
    Parameters:
    
    columnName - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - log2
```
public static Column log2(Column expr)
```
    Computes the logarithm of the given column in base 2.
    
    Parameters:
    
    expr - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - log2
```
public static Column log2(String columnName)
```
    Computes the logarithm of the given value in base 2.
    
    Parameters:
    
    columnName - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - pow
```
public static Column pow(Column l,
                         Column r)
```
    Returns the value of the first argument raised to the power of the second argument.
    
    Parameters:
    
    l - (undocumented)
    
    r - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - pow
```
public static Column pow(Column l,
                         String rightName)
```
    Returns the value of the first argument raised to the power of the second argument.
    
    Parameters:
    
    l - (undocumented)
    
    rightName - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - pow
```
public static Column pow(String leftName,
                         Column r)
```
    Returns the value of the first argument raised to the power of the second argument.
    
    Parameters:
    
    leftName - (undocumented)
    
    r - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - pow
```
public static Column pow(String leftName,
                         String rightName)
```
    Returns the value of the first argument raised to the power of the second argument.
    
    Parameters:
    
    leftName - (undocumented)
    
    rightName - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - pow
```
public static Column pow(Column l,
                         double r)
```
    Returns the value of the first argument raised to the power of the second argument.
    
    Parameters:
    
    l - (undocumented)
    
    r - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - pow
```
public static Column pow(String leftName,
                         double r)
```
    Returns the value of the first argument raised to the power of the second argument.
    
    Parameters:
    
    leftName - (undocumented)
    
    r - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - pow
```
public static Column pow(double l,
                         Column r)
```
    Returns the value of the first argument raised to the power of the second argument.
    
    Parameters:
    
    l - (undocumented)
    
    r - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - pow
```
public static Column pow(double l,
                         String rightName)
```
    Returns the value of the first argument raised to the power of the second argument.
    
    Parameters:
    
    l - (undocumented)
    
    rightName - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - pmod
```
public static Column pmod(Column dividend,
                          Column divisor)
```
    Returns the positive value of dividend mod divisor.
    
    Parameters:
    
    dividend - (undocumented)
    
    divisor - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - rint
```
public static Column rint(Column e)
```
    Returns the double value that is closest in value to the argument and is equal to a mathematical integer.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - rint
```
public static Column rint(String columnName)
```
    Returns the double value that is closest in value to the argument and is equal to a mathematical integer.
    
    Parameters:
    
    columnName - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - round
```
public static Column round(Column e)
```
    Returns the value of the column e rounded to 0 decimal places with HALF_UP round mode.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - round
```
public static Column round(Column e,
                           int scale)
```
    Round the value of e to scale decimal places with HALF_UP round mode if scale is greater than or equal to 0 or at integral part when scale is less than 0.
    
    Parameters:
    
    e - (undocumented)
    
    scale - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - bround
```
public static Column bround(Column e)
```
    Returns the value of the column e rounded to 0 decimal places with HALF_EVEN round mode.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.0.0
  - bround
```
public static Column bround(Column e,
                            int scale)
```
    Round the value of e to scale decimal places with HALF_EVEN round mode if scale is greater than or equal to 0 or at integral part when scale is less than 0.
    
    Parameters:
    
    e - (undocumented)
    
    scale - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.0.0
  - shiftLeft
```
public static Column shiftLeft(Column e,
                               int numBits)
```
    Shift the given value numBits left. If the given value is a long value, this function will return a long value else it will return an integer value.
    
    Parameters:
    
    e - (undocumented)
    
    numBits - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - shiftRight
```
public static Column shiftRight(Column e,
                                int numBits)
```
    (Signed) shift the given value numBits right. If the given value is a long value, it will return a long value else it will return an integer value.
    
    Parameters:
    
    e - (undocumented)
    
    numBits - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - shiftRightUnsigned
```
public static Column shiftRightUnsigned(Column e,
                                        int numBits)
```
    Unsigned shift the given value numBits right. If the given value is a long value, it will return a long value else it will return an integer value.
    
    Parameters:
    
    e - (undocumented)
    
    numBits - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - signum
```
public static Column signum(Column e)
```
    Computes the signum of the given value.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - signum
```
public static Column signum(String columnName)
```
    Computes the signum of the given column.
    
    Parameters:
    
    columnName - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - sin
```
public static Column sin(Column e)
```
    Parameters:
    
    e - angle in radians
    
    Returns:
    
    sine of the angle, as if computed by java.lang.Math.sin
    
    Since:
    
    1.4.0
  - sin
```
public static Column sin(String columnName)
```
    Parameters:
    
    columnName - angle in radians
    
    Returns:
    
    sine of the angle, as if computed by java.lang.Math.sin
    
    Since:
    
    1.4.0
  - sinh
```
public static Column sinh(Column e)
```
    Parameters:
    
    e - hyperbolic angle
    
    Returns:
    
    hyperbolic sine of the given value, as if computed by java.lang.Math.sinh
    
    Since:
    
    1.4.0
  - sinh
```
public static Column sinh(String columnName)
```
    Parameters:
    
    columnName - hyperbolic angle
    
    Returns:
    
    hyperbolic sine of the given value, as if computed by java.lang.Math.sinh
    
    Since:
    
    1.4.0
  - tan
```
public static Column tan(Column e)
```
    Parameters:
    
    e - angle in radians
    
    Returns:
    
    tangent of the given value, as if computed by java.lang.Math.tan
    
    Since:
    
    1.4.0
  - tan
```
public static Column tan(String columnName)
```
    Parameters:
    
    columnName - angle in radians
    
    Returns:
    
    tangent of the given value, as if computed by java.lang.Math.tan
    
    Since:
    
    1.4.0
  - tanh
```
public static Column tanh(Column e)
```
    Parameters:
    
    e - hyperbolic angle
    
    Returns:
    
    hyperbolic tangent of the given value, as if computed by java.lang.Math.tanh
    
    Since:
    
    1.4.0
  - tanh
```
public static Column tanh(String columnName)
```
    Parameters:
    
    columnName - hyperbolic angle
    
    Returns:
    
    hyperbolic tangent of the given value, as if computed by java.lang.Math.tanh
    
    Since:
    
    1.4.0
  - toDegrees
```
public static Column toDegrees(Column e)
```
    Deprecated. Use degrees. Since 2.1.0.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - toDegrees
```
public static Column toDegrees(String columnName)
```
    Deprecated. Use degrees. Since 2.1.0.
    
    Parameters:
    
    columnName - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - degrees
```
public static Column degrees(Column e)
```
    Converts an angle measured in radians to an approximately equivalent angle measured in degrees.
    
    Parameters:
    
    e - angle in radians
    
    Returns:
    
    angle in degrees, as if computed by java.lang.Math.toDegrees
    
    Since:
    
    2.1.0
  - degrees
```
public static Column degrees(String columnName)
```
    Converts an angle measured in radians to an approximately equivalent angle measured in degrees.
    
    Parameters:
    
    columnName - angle in radians
    
    Returns:
    
    angle in degrees, as if computed by java.lang.Math.toDegrees
    
    Since:
    
    2.1.0
  - toRadians
```
public static Column toRadians(Column e)
```
    Deprecated. Use radians. Since 2.1.0.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - toRadians
```
public static Column toRadians(String columnName)
```
    Deprecated. Use radians. Since 2.1.0.
    
    Parameters:
    
    columnName - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.4.0
  - radians
```
public static Column radians(Column e)
```
    Converts an angle measured in degrees to an approximately equivalent angle measured in radians.
    
    Parameters:
    
    e - angle in degrees
    
    Returns:
    
    angle in radians, as if computed by java.lang.Math.toRadians
    
    Since:
    
    2.1.0
  - radians
```
public static Column radians(String columnName)
```
    Converts an angle measured in degrees to an approximately equivalent angle measured in radians.
    
    Parameters:
    
    columnName - angle in degrees
    
    Returns:
    
    angle in radians, as if computed by java.lang.Math.toRadians
    
    Since:
    
    2.1.0
  - md5
```
public static Column md5(Column e)
```
    Calculates the MD5 digest of a binary column and returns the value as a 32 character hex string.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - sha1
```
public static Column sha1(Column e)
```
    Calculates the SHA-1 digest of a binary column and returns the value as a 40 character hex string.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - sha2
```
public static Column sha2(Column e,
                          int numBits)
```
    Calculates the SHA-2 family of hash functions of a binary column and returns the value as a hex string.
    
    Parameters:
    
    e - column to compute SHA-2 on.
    
    numBits - one of 224, 256, 384, or 512.
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - crc32
```
public static Column crc32(Column e)
```
    Calculates the cyclic redundancy check value (CRC32) of a binary column and returns the value as a bigint.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - hash
```
public static Column hash(scala.collection.Seq<Column> cols)
```
    Calculates the hash code of given columns, and returns the result as an int column.
    
    Parameters:
    
    cols - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.0.0
  - xxhash64
```
public static Column xxhash64(scala.collection.Seq<Column> cols)
```
    Calculates the hash code of given columns using the 64-bit variant of the xxHash algorithm, and returns the result as a long column.
    
    Parameters:
    
    cols - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    3.0.0
  - ascii
```
public static Column ascii(Column e)
```
    Computes the numeric value of the first character of the string column, and returns the result as an int column.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - base64
```
public static Column base64(Column e)
```
    Computes the BASE64 encoding of a binary column and returns it as a string column. This is the reverse of unbase64.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - concat_ws
```
public static Column concat_ws(String sep,
                               scala.collection.Seq<Column> exprs)
```
    Concatenates multiple input string columns together into a single string column, using the given separator.
    
    Parameters:
    
    sep - (undocumented)
    
    exprs - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - decode
```
public static Column decode(Column value,
                            String charset)
```
    Computes the first argument into a string from a binary using the provided character set (one of 'US-ASCII', 'ISO-8859-1', 'UTF-8', 'UTF-16BE', 'UTF-16LE', 'UTF-16'). If either argument is null, the result will also be null.
    
    Parameters:
    
    value - (undocumented)
    
    charset - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - encode
```
public static Column encode(Column value,
                            String charset)
```
    Computes the first argument into a binary from a string using the provided character set (one of 'US-ASCII', 'ISO-8859-1', 'UTF-8', 'UTF-16BE', 'UTF-16LE', 'UTF-16'). If either argument is null, the result will also be null.
    
    Parameters:
    
    value - (undocumented)
    
    charset - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - format_number
```
public static Column format_number(Column x,
                                   int d)
```
    Formats numeric column x to a format like '#,###,###.##', rounded to d decimal places with HALF_EVEN round mode, and returns the result as a string column.
    If d is 0, the result has no decimal point or fractional part. If d is less than 0, the result will be null.
    
    Parameters:
    
    x - (undocumented)
    
    d - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - format_string
```
public static Column format_string(String format,
                                   scala.collection.Seq<Column> arguments)
```
    Formats the arguments in printf-style and returns the result as a string column.
    
    Parameters:
    
    format - (undocumented)
    
    arguments - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - initcap
```
public static Column initcap(Column e)
```
    Returns a new string column by converting the first letter of each word to uppercase. Words are delimited by whitespace.
    For example, "hello world" will become "Hello World".
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - instr
```
public static Column instr(Column str,
                           String substring)
```
    Locate the position of the first occurrence of substr column in the given string. Returns null if either of the arguments are null.
    
    Parameters:
    
    str - (undocumented)
    
    substring - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
    
    Note:
    
    The position is not zero based, but 1 based index. Returns 0 if substr could not be found in str.
  - length
```
public static Column length(Column e)
```
    Computes the character length of a given string or number of bytes of a binary string. The length of character strings include the trailing spaces. The length of binary strings includes binary zeros.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - lower
```
public static Column lower(Column e)
```
    Converts a string column to lower case.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.3.0
  - levenshtein
```
public static Column levenshtein(Column l,
                                 Column r)
```
    Computes the Levenshtein distance of the two given string columns.
    
    Parameters:
    
    l - (undocumented)
    
    r - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - locate
```
public static Column locate(String substr,
                            Column str)
```
    Locate the position of the first occurrence of substr.
    
    Parameters:
    
    substr - (undocumented)
    
    str - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
    
    Note:
    
    The position is not zero based, but 1 based index. Returns 0 if substr could not be found in str.
  - locate
```
public static Column locate(String substr,
                            Column str,
                            int pos)
```
    Locate the position of the first occurrence of substr in a string column, after position pos.
    
    Parameters:
    
    substr - (undocumented)
    
    str - (undocumented)
    
    pos - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
    
    Note:
    
    The position is not zero based, but 1 based index. returns 0 if substr could not be found in str.
  - lpad
```
public static Column lpad(Column str,
                          int len,
                          String pad)
```
    Left-pad the string column with pad to a length of len. If the string column is longer than len, the return value is shortened to len characters.
    
    Parameters:
    
    str - (undocumented)
    
    len - (undocumented)
    
    pad - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - ltrim
```
public static Column ltrim(Column e)
```
    Trim the spaces from left end for the specified string value.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - ltrim
```
public static Column ltrim(Column e,
                           String trimString)
```
    Trim the specified character string from left end for the specified string column.
    
    Parameters:
    
    e - (undocumented)
    
    trimString - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.3.0
  - regexp_extract
```
public static Column regexp_extract(Column e,
                                    String exp,
                                    int groupIdx)
```
    Extract a specific group matched by a Java regex, from the specified string column. If the regex did not match, or the specified group did not match, an empty string is returned.
    
    Parameters:
    
    e - (undocumented)
    
    exp - (undocumented)
    
    groupIdx - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - regexp_replace
```
public static Column regexp_replace(Column e,
                                    String pattern,
                                    String replacement)
```
    Replace all substrings of the specified string value that match regexp with rep.
    
    Parameters:
    
    e - (undocumented)
    
    pattern - (undocumented)
    
    replacement - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - regexp_replace
```
public static Column regexp_replace(Column e,
                                    Column pattern,
                                    Column replacement)
```
    Replace all substrings of the specified string value that match regexp with rep.
    
    Parameters:
    
    e - (undocumented)
    
    pattern - (undocumented)
    
    replacement - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.1.0
  - unbase64
```
public static Column unbase64(Column e)
```
    Decodes a BASE64 encoded string column and returns it as a binary column. This is the reverse of base64.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - rpad
```
public static Column rpad(Column str,
                          int len,
                          String pad)
```
    Right-pad the string column with pad to a length of len. If the string column is longer than len, the return value is shortened to len characters.
    
    Parameters:
    
    str - (undocumented)
    
    len - (undocumented)
    
    pad - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - repeat
```
public static Column repeat(Column str,
                            int n)
```
    Repeats a string column n times, and returns it as a new string column.
    
    Parameters:
    
    str - (undocumented)
    
    n - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - rtrim
```
public static Column rtrim(Column e)
```
    Trim the spaces from right end for the specified string value.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - rtrim
```
public static Column rtrim(Column e,
                           String trimString)
```
    Trim the specified character string from right end for the specified string column.
    
    Parameters:
    
    e - (undocumented)
    
    trimString - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.3.0
  - soundex
```
public static Column soundex(Column e)
```
    Returns the soundex code for the specified expression.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - split
```
public static Column split(Column str,
                           String pattern)
```
    Splits str around matches of the given pattern.
    
    Parameters:
    
    str - a string expression to split
    
    pattern - a string representing a regular expression. The regex string should be a Java regular expression.
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - split
```
public static Column split(Column str,
                           String pattern,
                           int limit)
```
    Splits str around matches of the given pattern.
    Parameters:
    
    str - a string expression to split
    
    pattern - a string representing a regular expression. The regex string should be a Java regular expression.
    limit - an integer expression which controls the number of times the regex is applied.
    
    limit greater than 0: The resulting array's length will not be more than limit, and the resulting array's last entry will contain all input beyond the last matched regex.
    
    limit less than or equal to 0: regex will be applied as many times as possible, and the resulting array can be of any size.
    Returns:
    
    (undocumented)
    
    Since:
    
    3.0.0
  - substring
```
public static Column substring(Column str,
                               int pos,
                               int len)
```
    Substring starts at pos and is of length len when str is String type or returns the slice of byte array that starts at pos in byte and is of length len when str is Binary type
    
    Parameters:
    
    str - (undocumented)
    
    pos - (undocumented)
    
    len - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
    
    Note:
    
    The position is not zero based, but 1 based index.
  - substring_index
```
public static Column substring_index(Column str,
                                     String delim,
                                     int count)
```
    Returns the substring from string str before count occurrences of the delimiter delim. If count is positive, everything the left of the final delimiter (counting from left) is returned. If count is negative, every to the right of the final delimiter (counting from the right) is returned. substring_index performs a case-sensitive match when searching for delim.
    
    Parameters:
    
    str - (undocumented)
    
    delim - (undocumented)
    
    count - (undocumented)
    
    Returns:
    
    (undocumented)
  - overlay
```
public static Column overlay(Column src,
                             Column replace,
                             Column pos,
                             Column len)
```
    Overlay the specified portion of src with replace, starting from byte position pos of src and proceeding for len bytes.
    
    Parameters:
    
    src - (undocumented)
    
    replace - (undocumented)
    
    pos - (undocumented)
    
    len - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    3.0.0
  - overlay
```
public static Column overlay(Column src,
                             Column replace,
                             Column pos)
```
    Overlay the specified portion of src with replace, starting from byte position pos of src.
    
    Parameters:
    
    src - (undocumented)
    
    replace - (undocumented)
    
    pos - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    3.0.0
  - translate
```
public static Column translate(Column src,
                               String matchingString,
                               String replaceString)
```
    Translate any character in the src by a character in replaceString. The characters in replaceString correspond to the characters in matchingString. The translate will happen when any character in the string matches the character in the matchingString.
    
    Parameters:
    
    src - (undocumented)
    
    matchingString - (undocumented)
    
    replaceString - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - trim
```
public static Column trim(Column e)
```
    Trim the spaces from both ends for the specified string column.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - trim
```
public static Column trim(Column e,
                          String trimString)
```
    Trim the specified character from both ends for the specified string column.
    
    Parameters:
    
    e - (undocumented)
    
    trimString - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.3.0
  - upper
```
public static Column upper(Column e)
```
    Converts a string column to upper case.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.3.0
  - add_months
```
public static Column add_months(Column startDate,
                                int numMonths)
```
    Returns the date that is numMonths after startDate.
    
    Parameters:
    
    startDate - A date, timestamp or string. If a string, the data must be in a format that can be cast to a date, such as yyyy-MM-dd or yyyy-MM-dd HH:mm:ss.SSSS
    
    numMonths - The number of months to add to startDate, can be negative to subtract months
    
    Returns:
    
    A date, or null if startDate was a string that could not be cast to a date
    
    Since:
    
    1.5.0
  - add_months
```
public static Column add_months(Column startDate,
                                Column numMonths)
```
    Returns the date that is numMonths after startDate.
    
    Parameters:
    
    startDate - A date, timestamp or string. If a string, the data must be in a format that can be cast to a date, such as yyyy-MM-dd or yyyy-MM-dd HH:mm:ss.SSSS
    
    numMonths - A column of the number of months to add to startDate, can be negative to subtract months
    
    Returns:
    
    A date, or null if startDate was a string that could not be cast to a date
    
    Since:
    
    3.0.0
  - current_date
```
public static Column current_date()
```
    Returns the current date at the start of query evaluation as a date column. All calls of current_date within the same query return the same value.
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - current_timestamp
```
public static Column current_timestamp()
```
    Returns the current timestamp at the start of query evaluation as a timestamp column. All calls of current_timestamp within the same query return the same value.
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - date_format
```
public static Column date_format(Column dateExpr,
                                 String format)
```
    Converts a date/timestamp/string to a value of string in the format specified by the date format given by the second argument.
    See Datetime Patterns for valid date and time format patterns
    
    Parameters:
    
    dateExpr - A date, timestamp or string. If a string, the data must be in a format that can be cast to a timestamp, such as yyyy-MM-dd or yyyy-MM-dd HH:mm:ss.SSSS
    
    format - A pattern dd.MM.yyyy would return a string like 18.03.1993
    
    Returns:
    
    A string, or null if dateExpr was a string that could not be cast to a timestamp
    
    Throws:
    
    IllegalArgumentException - if the format pattern is invalid
    
    Since:
    
    1.5.0
    
    Note:
    
    Use specialized functions like year whenever possible as they benefit from a specialized implementation.
  - date_add
```
public static Column date_add(Column start,
                              int days)
```
    Returns the date that is days days after start
    
    Parameters:
    
    start - A date, timestamp or string. If a string, the data must be in a format that can be cast to a date, such as yyyy-MM-dd or yyyy-MM-dd HH:mm:ss.SSSS
    
    days - The number of days to add to start, can be negative to subtract days
    
    Returns:
    
    A date, or null if start was a string that could not be cast to a date
    
    Since:
    
    1.5.0
  - date_add
```
public static Column date_add(Column start,
                              Column days)
```
    Returns the date that is days days after start
    
    Parameters:
    
    start - A date, timestamp or string. If a string, the data must be in a format that can be cast to a date, such as yyyy-MM-dd or yyyy-MM-dd HH:mm:ss.SSSS
    
    days - A column of the number of days to add to start, can be negative to subtract days
    
    Returns:
    
    A date, or null if start was a string that could not be cast to a date
    
    Since:
    
    3.0.0
  - date_sub
```
public static Column date_sub(Column start,
                              int days)
```
    Returns the date that is days days before start
    
    Parameters:
    
    start - A date, timestamp or string. If a string, the data must be in a format that can be cast to a date, such as yyyy-MM-dd or yyyy-MM-dd HH:mm:ss.SSSS
    
    days - The number of days to subtract from start, can be negative to add days
    
    Returns:
    
    A date, or null if start was a string that could not be cast to a date
    
    Since:
    
    1.5.0
  - date_sub
```
public static Column date_sub(Column start,
                              Column days)
```
    Returns the date that is days days before start
    
    Parameters:
    
    start - A date, timestamp or string. If a string, the data must be in a format that can be cast to a date, such as yyyy-MM-dd or yyyy-MM-dd HH:mm:ss.SSSS
    
    days - A column of the number of days to subtract from start, can be negative to add days
    
    Returns:
    
    A date, or null if start was a string that could not be cast to a date
    
    Since:
    
    3.0.0
  - datediff
```
public static Column datediff(Column end,
                              Column start)
```
    Returns the number of days from start to end.
    Only considers the date part of the input. For example:
```
 dateddiff("2018-01-10 00:00:00", "2018-01-09 23:59:59")
 // returns 1
 
```
    Parameters:
    
    end - A date, timestamp or string. If a string, the data must be in a format that can be cast to a date, such as yyyy-MM-dd or yyyy-MM-dd HH:mm:ss.SSSS
    
    start - A date, timestamp or string. If a string, the data must be in a format that can be cast to a date, such as yyyy-MM-dd or yyyy-MM-dd HH:mm:ss.SSSS
    
    Returns:
    
    An integer, or null if either end or start were strings that could not be cast to a date. Negative if end is before start
    
    Since:
    
    1.5.0
  - year
```
public static Column year(Column e)
```
    Extracts the year as an integer from a given date/timestamp/string.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    An integer, or null if the input was a string that could not be cast to a date
    
    Since:
    
    1.5.0
  - quarter
```
public static Column quarter(Column e)
```
    Extracts the quarter as an integer from a given date/timestamp/string.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    An integer, or null if the input was a string that could not be cast to a date
    
    Since:
    
    1.5.0
  - month
```
public static Column month(Column e)
```
    Extracts the month as an integer from a given date/timestamp/string.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    An integer, or null if the input was a string that could not be cast to a date
    
    Since:
    
    1.5.0
  - dayofweek
```
public static Column dayofweek(Column e)
```
    Extracts the day of the week as an integer from a given date/timestamp/string. Ranges from 1 for a Sunday through to 7 for a Saturday
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    An integer, or null if the input was a string that could not be cast to a date
    
    Since:
    
    2.3.0
  - dayofmonth
```
public static Column dayofmonth(Column e)
```
    Extracts the day of the month as an integer from a given date/timestamp/string.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    An integer, or null if the input was a string that could not be cast to a date
    
    Since:
    
    1.5.0
  - dayofyear
```
public static Column dayofyear(Column e)
```
    Extracts the day of the year as an integer from a given date/timestamp/string.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    An integer, or null if the input was a string that could not be cast to a date
    
    Since:
    
    1.5.0
  - hour
```
public static Column hour(Column e)
```
    Extracts the hours as an integer from a given date/timestamp/string.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    An integer, or null if the input was a string that could not be cast to a date
    
    Since:
    
    1.5.0
  - last_day
```
public static Column last_day(Column e)
```
    Returns the last day of the month which the given date belongs to. For example, input "2015-07-27" returns "2015-07-31" since July 31 is the last day of the month in July 2015.
    
    Parameters:
    
    e - A date, timestamp or string. If a string, the data must be in a format that can be cast to a date, such as yyyy-MM-dd or yyyy-MM-dd HH:mm:ss.SSSS
    
    Returns:
    
    A date, or null if the input was a string that could not be cast to a date
    
    Since:
    
    1.5.0
  - minute
```
public static Column minute(Column e)
```
    Extracts the minutes as an integer from a given date/timestamp/string.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    An integer, or null if the input was a string that could not be cast to a date
    
    Since:
    
    1.5.0
  - months_between
```
public static Column months_between(Column end,
                                    Column start)
```
    Returns number of months between dates start and end.
    A whole number is returned if both inputs have the same day of month or both are the last day of their respective months. Otherwise, the difference is calculated assuming 31 days per month.
    For example:
```
 months_between("2017-11-14", "2017-07-14")  // returns 4.0
 months_between("2017-01-01", "2017-01-10")  // returns 0.29032258
 months_between("2017-06-01", "2017-06-16 12:00:00")  // returns -0.5
 
```
    Parameters:
    
    end - A date, timestamp or string. If a string, the data must be in a format that can be cast to a timestamp, such as yyyy-MM-dd or yyyy-MM-dd HH:mm:ss.SSSS
    
    start - A date, timestamp or string. If a string, the data must be in a format that can cast to a timestamp, such as yyyy-MM-dd or yyyy-MM-dd HH:mm:ss.SSSS
    
    Returns:
    
    A double, or null if either end or start were strings that could not be cast to a timestamp. Negative if end is before start
    
    Since:
    
    1.5.0
  - months_between
```
public static Column months_between(Column end,
                                    Column start,
                                    boolean roundOff)
```
    Returns number of months between dates end and start. If roundOff is set to true, the result is rounded off to 8 digits; it is not rounded otherwise.
    
    Parameters:
    
    end - (undocumented)
    
    start - (undocumented)
    
    roundOff - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.4.0
  - next_day
```
public static Column next_day(Column date,
                              String dayOfWeek)
```
    Returns the first date which is later than the value of the date column that is on the specified day of the week.
    For example, next_day('2015-07-27', "Sunday") returns 2015-08-02 because that is the first Sunday after 2015-07-27.
    
    Parameters:
    
    date - A date, timestamp or string. If a string, the data must be in a format that can be cast to a date, such as yyyy-MM-dd or yyyy-MM-dd HH:mm:ss.SSSS
    
    dayOfWeek - Case insensitive, and accepts: "Mon", "Tue", "Wed", "Thu", "Fri", "Sat", "Sun"
    
    Returns:
    
    A date, or null if date was a string that could not be cast to a date or if dayOfWeek was an invalid value
    
    Since:
    
    1.5.0
  - second
```
public static Column second(Column e)
```
    Extracts the seconds as an integer from a given date/timestamp/string.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    An integer, or null if the input was a string that could not be cast to a timestamp
    
    Since:
    
    1.5.0
  - weekofyear
```
public static Column weekofyear(Column e)
```
    Extracts the week number as an integer from a given date/timestamp/string.
    A week is considered to start on a Monday and week 1 is the first week with more than 3 days, as defined by ISO 8601
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    An integer, or null if the input was a string that could not be cast to a date
    
    Since:
    
    1.5.0
  - from_unixtime
```
public static Column from_unixtime(Column ut)
```
    Converts the number of seconds from unix epoch (1970-01-01 00:00:00 UTC) to a string representing the timestamp of that moment in the current system time zone in the yyyy-MM-dd HH:mm:ss format.
    
    Parameters:
    
    ut - A number of a type that is castable to a long, such as string or integer. Can be negative for timestamps before the unix epoch
    
    Returns:
    
    A string, or null if the input was a string that could not be cast to a long
    
    Since:
    
    1.5.0
  - from_unixtime
```
public static Column from_unixtime(Column ut,
                                   String f)
```
    Converts the number of seconds from unix epoch (1970-01-01 00:00:00 UTC) to a string representing the timestamp of that moment in the current system time zone in the given format.
    See Datetime Patterns for valid date and time format patterns
    
    Parameters:
    
    ut - A number of a type that is castable to a long, such as string or integer. Can be negative for timestamps before the unix epoch
    
    f - A date time pattern that the input will be formatted to
    
    Returns:
    
    A string, or null if ut was a string that could not be cast to a long or f was an invalid date time pattern
    
    Since:
    
    1.5.0
  - unix_timestamp
```
public static Column unix_timestamp()
```
    Returns the current Unix timestamp (in seconds) as a long.
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
    
    Note:
    
    All calls of unix_timestamp within the same query return the same value (i.e. the current timestamp is calculated at the start of query evaluation).
  - unix_timestamp
```
public static Column unix_timestamp(Column s)
```
    Converts time string in format yyyy-MM-dd HH:mm:ss to Unix timestamp (in seconds), using the default timezone and the default locale.
    
    Parameters:
    
    s - A date, timestamp or string. If a string, the data must be in the yyyy-MM-dd HH:mm:ss format
    
    Returns:
    
    A long, or null if the input was a string not of the correct format
    
    Since:
    
    1.5.0
  - unix_timestamp
```
public static Column unix_timestamp(Column s,
                                    String p)
```
    Converts time string with given pattern to Unix timestamp (in seconds).
    See Datetime Patterns for valid date and time format patterns
    
    Parameters:
    
    s - A date, timestamp or string. If a string, the data must be in a format that can be cast to a date, such as yyyy-MM-dd or yyyy-MM-dd HH:mm:ss.SSSS
    
    p - A date time pattern detailing the format of s when s is a string
    
    Returns:
    
    A long, or null if s was a string that could not be cast to a date or p was an invalid format
    
    Since:
    
    1.5.0
  - to_timestamp
```
public static Column to_timestamp(Column s)
```
    Converts to a timestamp by casting rules to TimestampType.
    
    Parameters:
    
    s - A date, timestamp or string. If a string, the data must be in a format that can be cast to a timestamp, such as yyyy-MM-dd or yyyy-MM-dd HH:mm:ss.SSSS
    
    Returns:
    
    A timestamp, or null if the input was a string that could not be cast to a timestamp
    
    Since:
    
    2.2.0
  - to_timestamp
```
public static Column to_timestamp(Column s,
                                  String fmt)
```
    Converts time string with the given pattern to timestamp.
    See Datetime Patterns for valid date and time format patterns
    
    Parameters:
    
    s - A date, timestamp or string. If a string, the data must be in a format that can be cast to a timestamp, such as yyyy-MM-dd or yyyy-MM-dd HH:mm:ss.SSSS
    
    fmt - A date time pattern detailing the format of s when s is a string
    
    Returns:
    
    A timestamp, or null if s was a string that could not be cast to a timestamp or fmt was an invalid format
    
    Since:
    
    2.2.0
  - to_date
```
public static Column to_date(Column e)
```
    Converts the column into DateType by casting rules to DateType.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - to_date
```
public static Column to_date(Column e,
                             String fmt)
```
    Converts the column into a DateType with a specified format
    See Datetime Patterns for valid date and time format patterns
    
    Parameters:
    
    e - A date, timestamp or string. If a string, the data must be in a format that can be cast to a date, such as yyyy-MM-dd or yyyy-MM-dd HH:mm:ss.SSSS
    
    fmt - A date time pattern detailing the format of e when eis a string
    
    Returns:
    
    A date, or null if e was a string that could not be cast to a date or fmt was an invalid format
    
    Since:
    
    2.2.0
  - trunc
```
public static Column trunc(Column date,
                           String format)
```
    Returns date truncated to the unit specified by the format.
    For example, trunc("2018-11-19 12:01:19", "year") returns 2018-01-01
    
    Parameters:
    
    date - A date, timestamp or string. If a string, the data must be in a format that can be cast to a date, such as yyyy-MM-dd or yyyy-MM-dd HH:mm:ss.SSSS
    
    format: - 'year', 'yyyy', 'yy' to truncate by year, or 'month', 'mon', 'mm' to truncate by month Other options are: 'week', 'quarter'
    
    Returns:
    
    A date, or null if date was a string that could not be cast to a date or format was an invalid value
    
    Since:
    
    1.5.0
  - date_trunc
```
public static Column date_trunc(String format,
                                Column timestamp)
```
    Returns timestamp truncated to the unit specified by the format.
    For example, date_trunc("year", "2018-11-19 12:01:19") returns 2018-01-01 00:00:00
    
    Parameters:
    
    format: - 'year', 'yyyy', 'yy' to truncate by year, 'month', 'mon', 'mm' to truncate by month, 'day', 'dd' to truncate by day, Other options are: 'microsecond', 'millisecond', 'second', 'minute', 'hour', 'week', 'quarter'
    
    timestamp - A date, timestamp or string. If a string, the data must be in a format that can be cast to a timestamp, such as yyyy-MM-dd or yyyy-MM-dd HH:mm:ss.SSSS
    
    Returns:
    
    A timestamp, or null if timestamp was a string that could not be cast to a timestamp or format was an invalid value
    
    Since:
    
    2.3.0
  - from_utc_timestamp
```
public static Column from_utc_timestamp(Column ts,
                                        String tz)
```
    Given a timestamp like '2017-07-14 02:40:00.0', interprets it as a time in UTC, and renders that time as a timestamp in the given time zone. For example, 'GMT+1' would yield '2017-07-14 03:40:00.0'.
    
    Parameters:
    
    ts - A date, timestamp or string. If a string, the data must be in a format that can be cast to a timestamp, such as yyyy-MM-dd or yyyy-MM-dd HH:mm:ss.SSSS
    
    tz - A string detailing the time zone ID that the input should be adjusted to. It should be in the format of either region-based zone IDs or zone offsets. Region IDs must have the form 'area/city', such as 'America/Los_Angeles'. Zone offsets must be in the format '(+|-)HH:mm', for example '-08:00' or '+01:00'. Also 'UTC' and 'Z' are supported as aliases of '+00:00'. Other short names are not recommended to use because they can be ambiguous.
    
    Returns:
    
    A timestamp, or null if ts was a string that could not be cast to a timestamp or tz was an invalid value
    
    Since:
    
    1.5.0
  - from_utc_timestamp
```
public static Column from_utc_timestamp(Column ts,
                                        Column tz)
```
    Given a timestamp like '2017-07-14 02:40:00.0', interprets it as a time in UTC, and renders that time as a timestamp in the given time zone. For example, 'GMT+1' would yield '2017-07-14 03:40:00.0'.
    
    Parameters:
    
    ts - (undocumented)
    
    tz - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.4.0
  - to_utc_timestamp
```
public static Column to_utc_timestamp(Column ts,
                                      String tz)
```
    Given a timestamp like '2017-07-14 02:40:00.0', interprets it as a time in the given time zone, and renders that time as a timestamp in UTC. For example, 'GMT+1' would yield '2017-07-14 01:40:00.0'.
    
    Parameters:
    
    ts - A date, timestamp or string. If a string, the data must be in a format that can be cast to a timestamp, such as yyyy-MM-dd or yyyy-MM-dd HH:mm:ss.SSSS
    
    tz - A string detailing the time zone ID that the input should be adjusted to. It should be in the format of either region-based zone IDs or zone offsets. Region IDs must have the form 'area/city', such as 'America/Los_Angeles'. Zone offsets must be in the format '(+|-)HH:mm', for example '-08:00' or '+01:00'. Also 'UTC' and 'Z' are supported as aliases of '+00:00'. Other short names are not recommended to use because they can be ambiguous.
    
    Returns:
    
    A timestamp, or null if ts was a string that could not be cast to a timestamp or tz was an invalid value
    
    Since:
    
    1.5.0
  - to_utc_timestamp
```
public static Column to_utc_timestamp(Column ts,
                                      Column tz)
```
    Given a timestamp like '2017-07-14 02:40:00.0', interprets it as a time in the given time zone, and renders that time as a timestamp in UTC. For example, 'GMT+1' would yield '2017-07-14 01:40:00.0'.
    
    Parameters:
    
    ts - (undocumented)
    
    tz - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.4.0
  - window
```
public static Column window(Column timeColumn,
                            String windowDuration,
                            String slideDuration,
                            String startTime)
```
    Bucketize rows into one or more time windows given a timestamp specifying column. Window starts are inclusive but the window ends are exclusive, e.g. 12:05 will be in the window [12:05,12:10) but not in [12:00,12:05). Windows can support microsecond precision. Windows in the order of months are not supported. The following example takes the average stock price for a one minute window every 10 seconds starting 5 seconds after the hour:
```
   val df = ... // schema => timestamp: TimestampType, stockId: StringType, price: DoubleType
   df.groupBy(window($"time", "1 minute", "10 seconds", "5 seconds"), $"stockId")
     .agg(mean("price"))
 
```
    The windows will look like:
```
   09:00:05-09:01:05
   09:00:15-09:01:15
   09:00:25-09:01:25 ...
 
```
    For a streaming query, you may use the function current_timestamp to generate windows on processing time.
    Parameters:
    
    timeColumn - The column or the expression to use as the timestamp for windowing by time. The time column must be of TimestampType.
    
    windowDuration - A string specifying the width of the window, e.g. 10 minutes, 1 second. Check org.apache.spark.unsafe.types.CalendarInterval for valid duration identifiers. Note that the duration is a fixed length of time, and does not vary over time according to a calendar. For example, 1 day always means 86,400,000 milliseconds, not a calendar day.
    
    slideDuration - A string specifying the sliding interval of the window, e.g. 1 minute. A new window will be generated every slideDuration. Must be less than or equal to the windowDuration. Check org.apache.spark.unsafe.types.CalendarInterval for valid duration identifiers. This duration is likewise absolute, and does not vary according to a calendar.
    
    startTime - The offset with respect to 1970-01-01 00:00:00 UTC with which to start window intervals. For example, in order to have hourly tumbling windows that start 15 minutes past the hour, e.g. 12:15-13:15, 13:15-14:15... provide startTime as 15 minutes.
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.0.0
  - window
```
public static Column window(Column timeColumn,
                            String windowDuration,
                            String slideDuration)
```
    Bucketize rows into one or more time windows given a timestamp specifying column. Window starts are inclusive but the window ends are exclusive, e.g. 12:05 will be in the window [12:05,12:10) but not in [12:00,12:05). Windows can support microsecond precision. Windows in the order of months are not supported. The windows start beginning at 1970-01-01 00:00:00 UTC. The following example takes the average stock price for a one minute window every 10 seconds:
```
   val df = ... // schema => timestamp: TimestampType, stockId: StringType, price: DoubleType
   df.groupBy(window($"time", "1 minute", "10 seconds"), $"stockId")
     .agg(mean("price"))
 
```
    The windows will look like:
```
   09:00:00-09:01:00
   09:00:10-09:01:10
   09:00:20-09:01:20 ...
 
```
    For a streaming query, you may use the function current_timestamp to generate windows on processing time.
    Parameters:
    
    timeColumn - The column or the expression to use as the timestamp for windowing by time. The time column must be of TimestampType.
    
    windowDuration - A string specifying the width of the window, e.g. 10 minutes, 1 second. Check org.apache.spark.unsafe.types.CalendarInterval for valid duration identifiers. Note that the duration is a fixed length of time, and does not vary over time according to a calendar. For example, 1 day always means 86,400,000 milliseconds, not a calendar day.
    
    slideDuration - A string specifying the sliding interval of the window, e.g. 1 minute. A new window will be generated every slideDuration. Must be less than or equal to the windowDuration. Check org.apache.spark.unsafe.types.CalendarInterval for valid duration identifiers. This duration is likewise absolute, and does not vary according to a calendar.
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.0.0
  - window
```
public static Column window(Column timeColumn,
                            String windowDuration)
```
    Generates tumbling time windows given a timestamp specifying column. Window starts are inclusive but the window ends are exclusive, e.g. 12:05 will be in the window [12:05,12:10) but not in [12:00,12:05). Windows can support microsecond precision. Windows in the order of months are not supported. The windows start beginning at 1970-01-01 00:00:00 UTC. The following example takes the average stock price for a one minute tumbling window:
```
   val df = ... // schema => timestamp: TimestampType, stockId: StringType, price: DoubleType
   df.groupBy(window($"time", "1 minute"), $"stockId")
     .agg(mean("price"))
 
```
    The windows will look like:
```
   09:00:00-09:01:00
   09:01:00-09:02:00
   09:02:00-09:03:00 ...
 
```
    For a streaming query, you may use the function current_timestamp to generate windows on processing time.
    Parameters:
    
    timeColumn - The column or the expression to use as the timestamp for windowing by time. The time column must be of TimestampType.
    
    windowDuration - A string specifying the width of the window, e.g. 10 minutes, 1 second. Check org.apache.spark.unsafe.types.CalendarInterval for valid duration identifiers.
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.0.0
  - array_contains
```
public static Column array_contains(Column column,
                                    Object value)
```
    Returns null if the array is null, true if the array contains value, and false otherwise.
    
    Parameters:
    
    column - (undocumented)
    
    value - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - arrays_overlap
```
public static Column arrays_overlap(Column a1,
                                    Column a2)
```
    Returns true if a1 and a2 have at least one non-null element in common. If not and both the arrays are non-empty and any of them contains a null, it returns null. It returns false otherwise.
    
    Parameters:
    
    a1 - (undocumented)
    
    a2 - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.4.0
  - slice
```
public static Column slice(Column x,
                           int start,
                           int length)
```
    Returns an array containing all the elements in x from index start (or starting from the end if start is negative) with the specified length.
    
    Parameters:
    
    x - the array column to be sliced
    
    start - the starting index
    
    length - the length of the slice
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.4.0
  - array_join
```
public static Column array_join(Column column,
                                String delimiter,
                                String nullReplacement)
```
    Concatenates the elements of column using the delimiter. Null values are replaced with nullReplacement.
    
    Parameters:
    
    column - (undocumented)
    
    delimiter - (undocumented)
    
    nullReplacement - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.4.0
  - array_join
```
public static Column array_join(Column column,
                                String delimiter)
```
    Concatenates the elements of column using the delimiter.
    
    Parameters:
    
    column - (undocumented)
    
    delimiter - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.4.0
  - concat
```
public static Column concat(scala.collection.Seq<Column> exprs)
```
    Concatenates multiple input columns together into a single column. The function works with strings, binary and compatible array columns.
    
    Parameters:
    
    exprs - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - array_position
```
public static Column array_position(Column column,
                                    Object value)
```
    Locates the position of the first occurrence of the value in the given array as long. Returns null if either of the arguments are null.
    
    Parameters:
    
    column - (undocumented)
    
    value - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.4.0
    
    Note:
    
    The position is not zero based, but 1 based index. Returns 0 if value could not be found in array.
  - element_at
```
public static Column element_at(Column column,
                                Object value)
```
    Returns element of array at given index in value if column is array. Returns value for the given key in value if column is map.
    
    Parameters:
    
    column - (undocumented)
    
    value - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.4.0
  - array_sort
```
public static Column array_sort(Column e)
```
    Sorts the input array in ascending order. The elements of the input array must be orderable. Null elements will be placed at the end of the returned array.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.4.0
  - array_remove
```
public static Column array_remove(Column column,
                                  Object element)
```
    Remove all elements that equal to element from the given array.
    
    Parameters:
    
    column - (undocumented)
    
    element - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.4.0
  - array_distinct
```
public static Column array_distinct(Column e)
```
    Removes duplicate values from the array.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.4.0
  - array_intersect
```
public static Column array_intersect(Column col1,
                                     Column col2)
```
    Returns an array of the elements in the intersection of the given two arrays, without duplicates.
    
    Parameters:
    
    col1 - (undocumented)
    
    col2 - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.4.0
  - array_union
```
public static Column array_union(Column col1,
                                 Column col2)
```
    Returns an array of the elements in the union of the given two arrays, without duplicates.
    
    Parameters:
    
    col1 - (undocumented)
    
    col2 - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.4.0
  - array_except
```
public static Column array_except(Column col1,
                                  Column col2)
```
    Returns an array of the elements in the first array but not in the second array, without duplicates. The order of elements in the result is not determined
    
    Parameters:
    
    col1 - (undocumented)
    
    col2 - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.4.0
  - transform
```
public static Column transform(Column column,
                               scala.Function1<Column,Column> f)
```
    Returns an array of elements after applying a transformation to each element in the input array.
```
   df.select(transform(col("i"), x => x + 1))
 
```
    Parameters:
    
    column - the input array column
    
    f - col => transformed_col, the lambda function to transform the input column
    
    Returns:
    
    (undocumented)
    
    Since:
    
    3.0.0
  - transform
```
public static Column transform(Column column,
                               scala.Function2<Column,Column,Column> f)
```
    Returns an array of elements after applying a transformation to each element in the input array.
```
   df.select(transform(col("i"), (x, i) => x + i))
 
```
    Parameters:
    
    column - the input array column
    
    f - (col, index) => transformed_col, the lambda function to filter the input column given the index. Indices start at 0.
    
    Returns:
    
    (undocumented)
    
    Since:
    
    3.0.0
  - exists
```
public static Column exists(Column column,
                            scala.Function1<Column,Column> f)
```
    Returns whether a predicate holds for one or more elements in the array.
```
   df.select(exists(col("i"), _ % 2 === 0))
 
```
    Parameters:
    
    column - the input array column
    
    f - col => predicate, the Boolean predicate to check the input column
    
    Returns:
    
    (undocumented)
    
    Since:
    
    3.0.0
  - forall
```
public static Column forall(Column column,
                            scala.Function1<Column,Column> f)
```
    Returns whether a predicate holds for every element in the array.
```
   df.select(forall(col("i"), x => x % 2 === 0))
 
```
    Parameters:
    
    column - the input array column
    
    f - col => predicate, the Boolean predicate to check the input column
    
    Returns:
    
    (undocumented)
    
    Since:
    
    3.0.0
  - filter
```
public static Column filter(Column column,
                            scala.Function1<Column,Column> f)
```
    Returns an array of elements for which a predicate holds in a given array.
```
   df.select(filter(col("s"), x => x % 2 === 0))
 
```
    Parameters:
    
    column - the input array column
    
    f - col => predicate, the Boolean predicate to filter the input column
    
    Returns:
    
    (undocumented)
    
    Since:
    
    3.0.0
  - filter
```
public static Column filter(Column column,
                            scala.Function2<Column,Column,Column> f)
```
    Returns an array of elements for which a predicate holds in a given array.
```
   df.select(filter(col("s"), (x, i) => i % 2 === 0))
 
```
    Parameters:
    
    column - the input array column
    
    f - (col, index) => predicate, the Boolean predicate to filter the input column given the index. Indices start at 0.
    
    Returns:
    
    (undocumented)
    
    Since:
    
    3.0.0
  - aggregate
```
public static Column aggregate(Column expr,
                               Column initialValue,
                               scala.Function2<Column,Column,Column> merge,
                               scala.Function1<Column,Column> finish)
```
    Applies a binary operator to an initial state and all elements in the array, and reduces this to a single state. The final state is converted into the final result by applying a finish function.
```
   df.select(aggregate(col("i"), lit(0), (acc, x) => acc + x, _ * 10))
 
```
    Parameters:
    
    expr - the input array column
    
    initialValue - the initial value
    
    merge - (combined_value, input_value) => combined_value, the merge function to merge an input value to the combined_value
    
    finish - combined_value => final_value, the lambda function to convert the combined value of all inputs to final result
    
    Returns:
    
    (undocumented)
    
    Since:
    
    3.0.0
  - aggregate
```
public static Column aggregate(Column expr,
                               Column initialValue,
                               scala.Function2<Column,Column,Column> merge)
```
    Applies a binary operator to an initial state and all elements in the array, and reduces this to a single state.
```
   df.select(aggregate(col("i"), lit(0), (acc, x) => acc + x))
 
```
    Parameters:
    
    expr - the input array column
    
    initialValue - the initial value
    
    merge - (combined_value, input_value) => combined_value, the merge function to merge an input value to the combined_value
    
    Returns:
    
    (undocumented)
    
    Since:
    
    3.0.0
  - zip_with
```
public static Column zip_with(Column left,
                              Column right,
                              scala.Function2<Column,Column,Column> f)
```
    Merge two given arrays, element-wise, into a single array using a function. If one array is shorter, nulls are appended at the end to match the length of the longer array, before applying the function.
```
   df.select(zip_with(df1("val1"), df1("val2"), (x, y) => x + y))
 
```
    Parameters:
    
    left - the left input array column
    
    right - the right input array column
    
    f - (lCol, rCol) => col, the lambda function to merge two input columns into one column
    
    Returns:
    
    (undocumented)
    
    Since:
    
    3.0.0
  - transform_keys
```
public static Column transform_keys(Column expr,
                                    scala.Function2<Column,Column,Column> f)
```
    Applies a function to every key-value pair in a map and returns a map with the results of those applications as the new keys for the pairs.
```
   df.select(transform_keys(col("i"), (k, v) => k + v))
 
```
    Parameters:
    
    expr - the input map column
    
    f - (key, value) => new_key, the lambda function to transform the key of input map column
    
    Returns:
    
    (undocumented)
    
    Since:
    
    3.0.0
  - transform_values
```
public static Column transform_values(Column expr,
                                      scala.Function2<Column,Column,Column> f)
```
    Applies a function to every key-value pair in a map and returns a map with the results of those applications as the new values for the pairs.
```
   df.select(transform_values(col("i"), (k, v) => k + v))
 
```
    Parameters:
    
    expr - the input map column
    
    f - (key, value) => new_value, the lambda function to transform the value of input map column
    
    Returns:
    
    (undocumented)
    
    Since:
    
    3.0.0
  - map_filter
```
public static Column map_filter(Column expr,
                                scala.Function2<Column,Column,Column> f)
```
    Returns a map whose key-value pairs satisfy a predicate.
```
   df.select(map_filter(col("m"), (k, v) => k * 10 === v))
 
```
    Parameters:
    
    expr - the input map column
    
    f - (key, value) => predicate, the Boolean predicate to filter the input map column
    
    Returns:
    
    (undocumented)
    
    Since:
    
    3.0.0
  - map_zip_with
```
public static Column map_zip_with(Column left,
                                  Column right,
                                  scala.Function3<Column,Column,Column,Column> f)
```
    Merge two given maps, key-wise into a single map using a function.
```
   df.select(map_zip_with(df("m1"), df("m2"), (k, v1, v2) => k === v1 + v2))
 
```
    Parameters:
    
    left - the left input map column
    
    right - the right input map column
    
    f - (key, value1, value2) => new_value, the lambda function to merge the map values
    
    Returns:
    
    (undocumented)
    
    Since:
    
    3.0.0
  - explode
```
public static Column explode(Column e)
```
    Creates a new row for each element in the given array or map column. Uses the default column name col for elements in the array and key and value for elements in the map unless specified otherwise.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.3.0
  - explode_outer
```
public static Column explode_outer(Column e)
```
    Creates a new row for each element in the given array or map column. Uses the default column name col for elements in the array and key and value for elements in the map unless specified otherwise. Unlike explode, if the array/map is null or empty then null is produced.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.2.0
  - posexplode
```
public static Column posexplode(Column e)
```
    Creates a new row for each element with position in the given array or map column. Uses the default column name pos for position, and col for elements in the array and key and value for elements in the map unless specified otherwise.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.1.0
  - posexplode_outer
```
public static Column posexplode_outer(Column e)
```
    Creates a new row for each element with position in the given array or map column. Uses the default column name pos for position, and col for elements in the array and key and value for elements in the map unless specified otherwise. Unlike posexplode, if the array/map is null or empty then the row (null, null) is produced.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.2.0
  - get_json_object
```
public static Column get_json_object(Column e,
                                     String path)
```
    Extracts json object from a json string based on json path specified, and returns json string of the extracted json object. It will return null if the input json string is invalid.
    
    Parameters:
    
    e - (undocumented)
    
    path - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.6.0
  - json_tuple
```
public static Column json_tuple(Column json,
                                scala.collection.Seq<String> fields)
```
    Creates a new row for a json column according to the given field names.
    
    Parameters:
    
    json - (undocumented)
    
    fields - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.6.0
  - from_json
```
public static Column from_json(Column e,
                               StructType schema,
                               scala.collection.immutable.Map<String,String> options)
```
    (Scala-specific) Parses a column containing a JSON string into a StructType with the specified schema. Returns null, in the case of an unparseable string.
    
    Parameters:
    
    e - a string column containing JSON data.
    
    schema - the schema to use when parsing the json string
    
    options - options to control how the json is parsed. Accepts the same options as the json data source.
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.1.0
  - from_json
```
public static Column from_json(Column e,
                               DataType schema,
                               scala.collection.immutable.Map<String,String> options)
```
    (Scala-specific) Parses a column containing a JSON string into a MapType with StringType as keys type, StructType or ArrayType with the specified schema. Returns null, in the case of an unparseable string.
    
    Parameters:
    
    e - a string column containing JSON data.
    
    schema - the schema to use when parsing the json string
    
    options - options to control how the json is parsed. accepts the same options and the json data source.
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.2.0
  - from_json
```
public static Column from_json(Column e,
                               StructType schema,
                               java.util.Map<String,String> options)
```
    (Java-specific) Parses a column containing a JSON string into a StructType with the specified schema. Returns null, in the case of an unparseable string.
    
    Parameters:
    
    e - a string column containing JSON data.
    
    schema - the schema to use when parsing the json string
    
    options - options to control how the json is parsed. accepts the same options and the json data source.
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.1.0
  - from_json
```
public static Column from_json(Column e,
                               DataType schema,
                               java.util.Map<String,String> options)
```
    (Java-specific) Parses a column containing a JSON string into a MapType with StringType as keys type, StructType or ArrayType with the specified schema. Returns null, in the case of an unparseable string.
    
    Parameters:
    
    e - a string column containing JSON data.
    
    schema - the schema to use when parsing the json string
    
    options - options to control how the json is parsed. accepts the same options and the json data source.
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.2.0
  - from_json
```
public static Column from_json(Column e,
                               StructType schema)
```
    Parses a column containing a JSON string into a StructType with the specified schema. Returns null, in the case of an unparseable string.
    
    Parameters:
    
    e - a string column containing JSON data.
    
    schema - the schema to use when parsing the json string
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.1.0
  - from_json
```
public static Column from_json(Column e,
                               DataType schema)
```
    Parses a column containing a JSON string into a MapType with StringType as keys type, StructType or ArrayType with the specified schema. Returns null, in the case of an unparseable string.
    
    Parameters:
    
    e - a string column containing JSON data.
    
    schema - the schema to use when parsing the json string
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.2.0
  - from_json
```
public static Column from_json(Column e,
                               String schema,
                               java.util.Map<String,String> options)
```
    (Java-specific) Parses a column containing a JSON string into a MapType with StringType as keys type, StructType or ArrayType with the specified schema. Returns null, in the case of an unparseable string.
    
    Parameters:
    
    e - a string column containing JSON data.
    
    schema - the schema to use when parsing the json string as a json string. In Spark 2.1, the user-provided schema has to be in JSON format. Since Spark 2.2, the DDL format is also supported for the schema.
    
    options - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.1.0
  - from_json
```
public static Column from_json(Column e,
                               String schema,
                               scala.collection.immutable.Map<String,String> options)
```
    (Scala-specific) Parses a column containing a JSON string into a MapType with StringType as keys type, StructType or ArrayType with the specified schema. Returns null, in the case of an unparseable string.
    
    Parameters:
    
    e - a string column containing JSON data.
    
    schema - the schema to use when parsing the json string as a json string, it could be a JSON format string or a DDL-formatted string.
    
    options - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.3.0
  - from_json
```
public static Column from_json(Column e,
                               Column schema)
```
    (Scala-specific) Parses a column containing a JSON string into a MapType with StringType as keys type, StructType or ArrayType of StructTypes with the specified schema. Returns null, in the case of an unparseable string.
    
    Parameters:
    
    e - a string column containing JSON data.
    
    schema - the schema to use when parsing the json string
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.4.0
  - from_json
```
public static Column from_json(Column e,
                               Column schema,
                               java.util.Map<String,String> options)
```
    (Java-specific) Parses a column containing a JSON string into a MapType with StringType as keys type, StructType or ArrayType of StructTypes with the specified schema. Returns null, in the case of an unparseable string.
    
    Parameters:
    
    e - a string column containing JSON data.
    
    schema - the schema to use when parsing the json string
    
    options - options to control how the json is parsed. accepts the same options and the json data source.
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.4.0
  - schema_of_json
```
public static Column schema_of_json(String json)
```
    Parses a JSON string and infers its schema in DDL format.
    
    Parameters:
    
    json - a JSON string.
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.4.0
  - schema_of_json
```
public static Column schema_of_json(Column json)
```
    Parses a JSON string and infers its schema in DDL format.
    
    Parameters:
    
    json - a string literal containing a JSON string.
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.4.0
  - schema_of_json
```
public static Column schema_of_json(Column json,
                                    java.util.Map<String,String> options)
```
    Parses a JSON string and infers its schema in DDL format using options.
    
    Parameters:
    
    json - a string column containing JSON data.
    
    options - options to control how the json is parsed. accepts the same options and the json data source. See DataFrameReader.json(java.lang.String...).
    
    Returns:
    
    a column with string literal containing schema in DDL format.
    
    Since:
    
    3.0.0
  - to_json
```
public static Column to_json(Column e,
                             scala.collection.immutable.Map<String,String> options)
```
    (Scala-specific) Converts a column containing a StructType, ArrayType or a MapType into a JSON string with the specified schema. Throws an exception, in the case of an unsupported type.
    
    Parameters:
    
    e - a column containing a struct, an array or a map.
    
    options - options to control how the struct column is converted into a json string. accepts the same options and the json data source. Additionally the function supports the pretty option which enables pretty JSON generation.
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.1.0
  - to_json
```
public static Column to_json(Column e,
                             java.util.Map<String,String> options)
```
    (Java-specific) Converts a column containing a StructType, ArrayType or a MapType into a JSON string with the specified schema. Throws an exception, in the case of an unsupported type.
    
    Parameters:
    
    e - a column containing a struct, an array or a map.
    
    options - options to control how the struct column is converted into a json string. accepts the same options and the json data source. Additionally the function supports the pretty option which enables pretty JSON generation.
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.1.0
  - to_json
```
public static Column to_json(Column e)
```
    Converts a column containing a StructType, ArrayType or a MapType into a JSON string with the specified schema. Throws an exception, in the case of an unsupported type.
    
    Parameters:
    
    e - a column containing a struct, an array or a map.
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.1.0
  - size
```
public static Column size(Column e)
```
    Returns length of array or map.
    The function returns null for null input if spark.sql.legacy.sizeOfNull is set to false or spark.sql.ansi.enabled is set to true. Otherwise, the function returns -1 for null input. With the default settings, the function returns -1 for null input.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - sort_array
```
public static Column sort_array(Column e)
```
    Sorts the input array for the given column in ascending order, according to the natural ordering of the array elements. Null elements will be placed at the beginning of the returned array.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - sort_array
```
public static Column sort_array(Column e,
                                boolean asc)
```
    Sorts the input array for the given column in ascending or descending order, according to the natural ordering of the array elements. Null elements will be placed at the beginning of the returned array in ascending order or at the end of the returned array in descending order.
    
    Parameters:
    
    e - (undocumented)
    
    asc - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - array_min
```
public static Column array_min(Column e)
```
    Returns the minimum value in the array.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.4.0
  - array_max
```
public static Column array_max(Column e)
```
    Returns the maximum value in the array.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.4.0
  - shuffle
```
public static Column shuffle(Column e)
```
    Returns a random permutation of the given array.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.4.0
    
    Note:
    
    The function is non-deterministic.
  - reverse
```
public static Column reverse(Column e)
```
    Returns a reversed string or an array with reverse order of elements.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0
  - flatten
```
public static Column flatten(Column e)
```
    Creates a single array from an array of arrays. If a structure of nested arrays is deeper than two levels, only one level of nesting is removed.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.4.0
  - sequence
```
public static Column sequence(Column start,
                              Column stop,
                              Column step)
```
    Generate a sequence of integers from start to stop, incrementing by step.
    
    Parameters:
    
    start - (undocumented)
    
    stop - (undocumented)
    
    step - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.4.0
  - sequence
```
public static Column sequence(Column start,
                              Column stop)
```
    Generate a sequence of integers from start to stop, incrementing by 1 if start is less than or equal to stop, otherwise -1.
    
    Parameters:
    
    start - (undocumented)
    
    stop - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.4.0
  - array_repeat
```
public static Column array_repeat(Column left,
                                  Column right)
```
    Creates an array containing the left argument repeated the number of times given by the right argument.
    
    Parameters:
    
    left - (undocumented)
    
    right - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.4.0
  - array_repeat
```
public static Column array_repeat(Column e,
                                  int count)
```
    Creates an array containing the left argument repeated the number of times given by the right argument.
    
    Parameters:
    
    e - (undocumented)
    
    count - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.4.0
  - map_keys
```
public static Column map_keys(Column e)
```
    Returns an unordered array containing the keys of the map.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.3.0
  - map_values
```
public static Column map_values(Column e)
```
    Returns an unordered array containing the values of the map.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.3.0
  - map_entries
```
public static Column map_entries(Column e)
```
    Returns an unordered array of all entries in the given map.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    3.0.0
  - map_from_entries
```
public static Column map_from_entries(Column e)
```
    Returns a map created from the given array of entries.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.4.0
  - arrays_zip
```
public static Column arrays_zip(scala.collection.Seq<Column> e)
```
    Returns a merged array of structs in which the N-th struct contains all N-th values of input arrays.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.4.0
  - map_concat
```
public static Column map_concat(scala.collection.Seq<Column> cols)
```
    Returns the union of all the given maps.
    
    Parameters:
    
    cols - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.4.0
  - from_csv
```
public static Column from_csv(Column e,
                              StructType schema,
                              scala.collection.immutable.Map<String,String> options)
```
    Parses a column containing a CSV string into a StructType with the specified schema. Returns null, in the case of an unparseable string.
    
    Parameters:
    
    e - a string column containing CSV data.
    
    schema - the schema to use when parsing the CSV string
    
    options - options to control how the CSV is parsed. accepts the same options and the CSV data source.
    
    Returns:
    
    (undocumented)
    
    Since:
    
    3.0.0
  - from_csv
```
public static Column from_csv(Column e,
                              Column schema,
                              java.util.Map<String,String> options)
```
    (Java-specific) Parses a column containing a CSV string into a StructType with the specified schema. Returns null, in the case of an unparseable string.
    
    Parameters:
    
    e - a string column containing CSV data.
    
    schema - the schema to use when parsing the CSV string
    
    options - options to control how the CSV is parsed. accepts the same options and the CSV data source.
    
    Returns:
    
    (undocumented)
    
    Since:
    
    3.0.0
  - schema_of_csv
```
public static Column schema_of_csv(String csv)
```
    Parses a CSV string and infers its schema in DDL format.
    
    Parameters:
    
    csv - a CSV string.
    
    Returns:
    
    (undocumented)
    
    Since:
    
    3.0.0
  - schema_of_csv
```
public static Column schema_of_csv(Column csv)
```
    Parses a CSV string and infers its schema in DDL format.
    
    Parameters:
    
    csv - a string literal containing a CSV string.
    
    Returns:
    
    (undocumented)
    
    Since:
    
    3.0.0
  - schema_of_csv
```
public static Column schema_of_csv(Column csv,
                                   java.util.Map<String,String> options)
```
    Parses a CSV string and infers its schema in DDL format using options.
    
    Parameters:
    
    csv - a string literal containing a CSV string.
    
    options - options to control how the CSV is parsed. accepts the same options and the json data source. See DataFrameReader.csv(java.lang.String...).
    
    Returns:
    
    a column with string literal containing schema in DDL format.
    
    Since:
    
    3.0.0
  - to_csv
```
public static Column to_csv(Column e,
                            java.util.Map<String,String> options)
```
    (Java-specific) Converts a column containing a StructType into a CSV string with the specified schema. Throws an exception, in the case of an unsupported type.
    
    Parameters:
    
    e - a column containing a struct.
    
    options - options to control how the struct column is converted into a CSV string. It accepts the same options and the json data source.
    
    Returns:
    
    (undocumented)
    
    Since:
    
    3.0.0
  - to_csv
```
public static Column to_csv(Column e)
```
    Converts a column containing a StructType into a CSV string with the specified schema. Throws an exception, in the case of an unsupported type.
    
    Parameters:
    
    e - a column containing a struct.
    
    Returns:
    
    (undocumented)
    
    Since:
    
    3.0.0
  - years
```
public static Column years(Column e)
```
    A transform for timestamps and dates to partition data into years.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    3.0.0
  - months
```
public static Column months(Column e)
```
    A transform for timestamps and dates to partition data into months.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    3.0.0
  - days
```
public static Column days(Column e)
```
    A transform for timestamps and dates to partition data into days.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    3.0.0
  - hours
```
public static Column hours(Column e)
```
    A transform for timestamps to partition data into hours.
    
    Parameters:
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    3.0.0
  - bucket
```
public static Column bucket(Column numBuckets,
                            Column e)
```
    A transform for any type that partitions by a hash of the input column.
    
    Parameters:
    
    numBuckets - (undocumented)
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    3.0.0
  - bucket
```
public static Column bucket(int numBuckets,
                            Column e)
```
    A transform for any type that partitions by a hash of the input column.
    
    Parameters:
    
    numBuckets - (undocumented)
    
    e - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    3.0.0
  - udaf
```
public static <IN,BUF,OUT> UserDefinedFunction udaf(Aggregator<IN,BUF,OUT> agg,
                                                    scala.reflect.api.TypeTags.TypeTag<IN> evidence$2)
```
    Obtains a UserDefinedFunction that wraps the given Aggregator so that it may be used with untyped Data Frames.
```
   val agg = // Aggregator[IN, BUF, OUT]

   // declare a UDF based on agg
   val aggUDF = udaf(agg)
   val aggData = df.agg(aggUDF($"colname"))

   // register agg as a named function
   spark.udf.register("myAggName", udaf(agg))
 
```
    Parameters:
    
    agg - the typed Aggregator
    
    evidence$2 - (undocumented)
    
    Returns:
    
    a UserDefinedFunction that can be used as an aggregating expression.
    
    Note:
    
    The input encoder is inferred from the input type IN.
  - udaf
```
public static <IN,BUF,OUT> UserDefinedFunction udaf(Aggregator<IN,BUF,OUT> agg,
                                                    Encoder<IN> inputEncoder)
```
    Obtains a UserDefinedFunction that wraps the given Aggregator so that it may be used with untyped Data Frames.
```
   Aggregator<IN, BUF, OUT> agg = // custom Aggregator
   Encoder<IN> enc = // input encoder

   // declare a UDF based on agg
   UserDefinedFunction aggUDF = udaf(agg, enc)
   DataFrame aggData = df.agg(aggUDF($"colname"))

   // register agg as a named function
   spark.udf.register("myAggName", udaf(agg, enc))
 
```
    Parameters:
    
    agg - the typed Aggregator
    
    inputEncoder - a specific input encoder to use
    
    Returns:
    
    a UserDefinedFunction that can be used as an aggregating expression
    
    Note:
    
    This overloading takes an explicit input encoder, to support UDAF declarations in Java.
  - udf
```
public static <RT> UserDefinedFunction udf(scala.Function0<RT> f,
                                           scala.reflect.api.TypeTags.TypeTag<RT> evidence$3)
```
    Defines a Scala closure of 0 arguments as user-defined function (UDF). The data types are automatically inferred based on the Scala closure's signature. By default the returned UDF is deterministic. To change it to nondeterministic, call the API UserDefinedFunction.asNondeterministic().
    
    Parameters:
    
    f - (undocumented)
    
    evidence$3 - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.3.0
  - udf
```
public static <RT,A1> UserDefinedFunction udf(scala.Function1<A1,RT> f,
                                              scala.reflect.api.TypeTags.TypeTag<RT> evidence$4,
                                              scala.reflect.api.TypeTags.TypeTag<A1> evidence$5)
```
    Defines a Scala closure of 1 arguments as user-defined function (UDF). The data types are automatically inferred based on the Scala closure's signature. By default the returned UDF is deterministic. To change it to nondeterministic, call the API UserDefinedFunction.asNondeterministic().
    
    Parameters:
    
    f - (undocumented)
    
    evidence$4 - (undocumented)
    
    evidence$5 - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.3.0
  - udf
```
public static <RT,A1,A2> UserDefinedFunction udf(scala.Function2<A1,A2,RT> f,
                                                 scala.reflect.api.TypeTags.TypeTag<RT> evidence$6,
                                                 scala.reflect.api.TypeTags.TypeTag<A1> evidence$7,
                                                 scala.reflect.api.TypeTags.TypeTag<A2> evidence$8)
```
    Defines a Scala closure of 2 arguments as user-defined function (UDF). The data types are automatically inferred based on the Scala closure's signature. By default the returned UDF is deterministic. To change it to nondeterministic, call the API UserDefinedFunction.asNondeterministic().
    
    Parameters:
    
    f - (undocumented)
    
    evidence$6 - (undocumented)
    
    evidence$7 - (undocumented)
    
    evidence$8 - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.3.0
  - udf
```
public static <RT,A1,A2,A3> UserDefinedFunction udf(scala.Function3<A1,A2,A3,RT> f,
                                                    scala.reflect.api.TypeTags.TypeTag<RT> evidence$9,
                                                    scala.reflect.api.TypeTags.TypeTag<A1> evidence$10,
                                                    scala.reflect.api.TypeTags.TypeTag<A2> evidence$11,
                                                    scala.reflect.api.TypeTags.TypeTag<A3> evidence$12)
```
    Defines a Scala closure of 3 arguments as user-defined function (UDF). The data types are automatically inferred based on the Scala closure's signature. By default the returned UDF is deterministic. To change it to nondeterministic, call the API UserDefinedFunction.asNondeterministic().
    
    Parameters:
    
    f - (undocumented)
    
    evidence$9 - (undocumented)
    
    evidence$10 - (undocumented)
    
    evidence$11 - (undocumented)
    
    evidence$12 - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.3.0
  - udf
```
public static <RT,A1,A2,A3,A4> UserDefinedFunction udf(scala.Function4<A1,A2,A3,A4,RT> f,
                                                       scala.reflect.api.TypeTags.TypeTag<RT> evidence$13,
                                                       scala.reflect.api.TypeTags.TypeTag<A1> evidence$14,
                                                       scala.reflect.api.TypeTags.TypeTag<A2> evidence$15,
                                                       scala.reflect.api.TypeTags.TypeTag<A3> evidence$16,
                                                       scala.reflect.api.TypeTags.TypeTag<A4> evidence$17)
```
    Defines a Scala closure of 4 arguments as user-defined function (UDF). The data types are automatically inferred based on the Scala closure's signature. By default the returned UDF is deterministic. To change it to nondeterministic, call the API UserDefinedFunction.asNondeterministic().
    
    Parameters:
    
    f - (undocumented)
    
    evidence$13 - (undocumented)
    
    evidence$14 - (undocumented)
    
    evidence$15 - (undocumented)
    
    evidence$16 - (undocumented)
    
    evidence$17 - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.3.0
  - udf
```
public static <RT,A1,A2,A3,A4,A5> UserDefinedFunction udf(scala.Function5<A1,A2,A3,A4,A5,RT> f,
                                                          scala.reflect.api.TypeTags.TypeTag<RT> evidence$18,
                                                          scala.reflect.api.TypeTags.TypeTag<A1> evidence$19,
                                                          scala.reflect.api.TypeTags.TypeTag<A2> evidence$20,
                                                          scala.reflect.api.TypeTags.TypeTag<A3> evidence$21,
                                                          scala.reflect.api.TypeTags.TypeTag<A4> evidence$22,
                                                          scala.reflect.api.TypeTags.TypeTag<A5> evidence$23)
```
    Defines a Scala closure of 5 arguments as user-defined function (UDF). The data types are automatically inferred based on the Scala closure's signature. By default the returned UDF is deterministic. To change it to nondeterministic, call the API UserDefinedFunction.asNondeterministic().
    
    Parameters:
    
    f - (undocumented)
    
    evidence$18 - (undocumented)
    
    evidence$19 - (undocumented)
    
    evidence$20 - (undocumented)
    
    evidence$21 - (undocumented)
    
    evidence$22 - (undocumented)
    
    evidence$23 - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.3.0
  - udf
```
public static <RT,A1,A2,A3,A4,A5,A6> UserDefinedFunction udf(scala.Function6<A1,A2,A3,A4,A5,A6,RT> f,
                                                             scala.reflect.api.TypeTags.TypeTag<RT> evidence$24,
                                                             scala.reflect.api.TypeTags.TypeTag<A1> evidence$25,
                                                             scala.reflect.api.TypeTags.TypeTag<A2> evidence$26,
                                                             scala.reflect.api.TypeTags.TypeTag<A3> evidence$27,
                                                             scala.reflect.api.TypeTags.TypeTag<A4> evidence$28,
                                                             scala.reflect.api.TypeTags.TypeTag<A5> evidence$29,
                                                             scala.reflect.api.TypeTags.TypeTag<A6> evidence$30)
```
    Defines a Scala closure of 6 arguments as user-defined function (UDF). The data types are automatically inferred based on the Scala closure's signature. By default the returned UDF is deterministic. To change it to nondeterministic, call the API UserDefinedFunction.asNondeterministic().
    
    Parameters:
    
    f - (undocumented)
    
    evidence$24 - (undocumented)
    
    evidence$25 - (undocumented)
    
    evidence$26 - (undocumented)
    
    evidence$27 - (undocumented)
    
    evidence$28 - (undocumented)
    
    evidence$29 - (undocumented)
    
    evidence$30 - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.3.0
  - udf
```
public static <RT,A1,A2,A3,A4,A5,A6,A7> UserDefinedFunction udf(scala.Function7<A1,A2,A3,A4,A5,A6,A7,RT> f,
                                                                scala.reflect.api.TypeTags.TypeTag<RT> evidence$31,
                                                                scala.reflect.api.TypeTags.TypeTag<A1> evidence$32,
                                                                scala.reflect.api.TypeTags.TypeTag<A2> evidence$33,
                                                                scala.reflect.api.TypeTags.TypeTag<A3> evidence$34,
                                                                scala.reflect.api.TypeTags.TypeTag<A4> evidence$35,
                                                                scala.reflect.api.TypeTags.TypeTag<A5> evidence$36,
                                                                scala.reflect.api.TypeTags.TypeTag<A6> evidence$37,
                                                                scala.reflect.api.TypeTags.TypeTag<A7> evidence$38)
```
    Defines a Scala closure of 7 arguments as user-defined function (UDF). The data types are automatically inferred based on the Scala closure's signature. By default the returned UDF is deterministic. To change it to nondeterministic, call the API UserDefinedFunction.asNondeterministic().
    
    Parameters:
    
    f - (undocumented)
    
    evidence$31 - (undocumented)
    
    evidence$32 - (undocumented)
    
    evidence$33 - (undocumented)
    
    evidence$34 - (undocumented)
    
    evidence$35 - (undocumented)
    
    evidence$36 - (undocumented)
    
    evidence$37 - (undocumented)
    
    evidence$38 - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.3.0
  - udf
```
public static <RT,A1,A2,A3,A4,A5,A6,A7,A8> UserDefinedFunction udf(scala.Function8<A1,A2,A3,A4,A5,A6,A7,A8,RT> f,
                                                                   scala.reflect.api.TypeTags.TypeTag<RT> evidence$39,
                                                                   scala.reflect.api.TypeTags.TypeTag<A1> evidence$40,
                                                                   scala.reflect.api.TypeTags.TypeTag<A2> evidence$41,
                                                                   scala.reflect.api.TypeTags.TypeTag<A3> evidence$42,
                                                                   scala.reflect.api.TypeTags.TypeTag<A4> evidence$43,
                                                                   scala.reflect.api.TypeTags.TypeTag<A5> evidence$44,
                                                                   scala.reflect.api.TypeTags.TypeTag<A6> evidence$45,
                                                                   scala.reflect.api.TypeTags.TypeTag<A7> evidence$46,
                                                                   scala.reflect.api.TypeTags.TypeTag<A8> evidence$47)
```
    Defines a Scala closure of 8 arguments as user-defined function (UDF). The data types are automatically inferred based on the Scala closure's signature. By default the returned UDF is deterministic. To change it to nondeterministic, call the API UserDefinedFunction.asNondeterministic().
    
    Parameters:
    
    f - (undocumented)
    
    evidence$39 - (undocumented)
    
    evidence$40 - (undocumented)
    
    evidence$41 - (undocumented)
    
    evidence$42 - (undocumented)
    
    evidence$43 - (undocumented)
    
    evidence$44 - (undocumented)
    
    evidence$45 - (undocumented)
    
    evidence$46 - (undocumented)
    
    evidence$47 - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.3.0
  - udf
```
public static <RT,A1,A2,A3,A4,A5,A6,A7,A8,A9> UserDefinedFunction udf(scala.Function9<A1,A2,A3,A4,A5,A6,A7,A8,A9,RT> f,
                                                                      scala.reflect.api.TypeTags.TypeTag<RT> evidence$48,
                                                                      scala.reflect.api.TypeTags.TypeTag<A1> evidence$49,
                                                                      scala.reflect.api.TypeTags.TypeTag<A2> evidence$50,
                                                                      scala.reflect.api.TypeTags.TypeTag<A3> evidence$51,
                                                                      scala.reflect.api.TypeTags.TypeTag<A4> evidence$52,
                                                                      scala.reflect.api.TypeTags.TypeTag<A5> evidence$53,
                                                                      scala.reflect.api.TypeTags.TypeTag<A6> evidence$54,
                                                                      scala.reflect.api.TypeTags.TypeTag<A7> evidence$55,
                                                                      scala.reflect.api.TypeTags.TypeTag<A8> evidence$56,
                                                                      scala.reflect.api.TypeTags.TypeTag<A9> evidence$57)
```
    Defines a Scala closure of 9 arguments as user-defined function (UDF). The data types are automatically inferred based on the Scala closure's signature. By default the returned UDF is deterministic. To change it to nondeterministic, call the API UserDefinedFunction.asNondeterministic().
    
    Parameters:
    
    f - (undocumented)
    
    evidence$48 - (undocumented)
    
    evidence$49 - (undocumented)
    
    evidence$50 - (undocumented)
    
    evidence$51 - (undocumented)
    
    evidence$52 - (undocumented)
    
    evidence$53 - (undocumented)
    
    evidence$54 - (undocumented)
    
    evidence$55 - (undocumented)
    
    evidence$56 - (undocumented)
    
    evidence$57 - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.3.0
  - udf
```
public static <RT,A1,A2,A3,A4,A5,A6,A7,A8,A9,A10> UserDefinedFunction udf(scala.Function10<A1,A2,A3,A4,A5,A6,A7,A8,A9,A10,RT> f,
                                                                          scala.reflect.api.TypeTags.TypeTag<RT> evidence$58,
                                                                          scala.reflect.api.TypeTags.TypeTag<A1> evidence$59,
                                                                          scala.reflect.api.TypeTags.TypeTag<A2> evidence$60,
                                                                          scala.reflect.api.TypeTags.TypeTag<A3> evidence$61,
                                                                          scala.reflect.api.TypeTags.TypeTag<A4> evidence$62,
                                                                          scala.reflect.api.TypeTags.TypeTag<A5> evidence$63,
                                                                          scala.reflect.api.TypeTags.TypeTag<A6> evidence$64,
                                                                          scala.reflect.api.TypeTags.TypeTag<A7> evidence$65,
                                                                          scala.reflect.api.TypeTags.TypeTag<A8> evidence$66,
                                                                          scala.reflect.api.TypeTags.TypeTag<A9> evidence$67,
                                                                          scala.reflect.api.TypeTags.TypeTag<A10> evidence$68)
```
    Defines a Scala closure of 10 arguments as user-defined function (UDF). The data types are automatically inferred based on the Scala closure's signature. By default the returned UDF is deterministic. To change it to nondeterministic, call the API UserDefinedFunction.asNondeterministic().
    
    Parameters:
    
    f - (undocumented)
    
    evidence$58 - (undocumented)
    
    evidence$59 - (undocumented)
    
    evidence$60 - (undocumented)
    
    evidence$61 - (undocumented)
    
    evidence$62 - (undocumented)
    
    evidence$63 - (undocumented)
    
    evidence$64 - (undocumented)
    
    evidence$65 - (undocumented)
    
    evidence$66 - (undocumented)
    
    evidence$67 - (undocumented)
    
    evidence$68 - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.3.0
  - udf
```
public static UserDefinedFunction udf(UDF0<?> f,
                                      DataType returnType)
```
    Defines a Java UDF0 instance as user-defined function (UDF). The caller must specify the output data type, and there is no automatic input type coercion. By default the returned UDF is deterministic. To change it to nondeterministic, call the API UserDefinedFunction.asNondeterministic().
    
    Parameters:
    
    f - (undocumented)
    
    returnType - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.3.0
  - udf
```
public static UserDefinedFunction udf(UDF1<?,?> f,
                                      DataType returnType)
```
    Defines a Java UDF1 instance as user-defined function (UDF). The caller must specify the output data type, and there is no automatic input type coercion. By default the returned UDF is deterministic. To change it to nondeterministic, call the API UserDefinedFunction.asNondeterministic().
    
    Parameters:
    
    f - (undocumented)
    
    returnType - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.3.0
  - udf
```
public static UserDefinedFunction udf(UDF2<?,?,?> f,
                                      DataType returnType)
```
    Defines a Java UDF2 instance as user-defined function (UDF). The caller must specify the output data type, and there is no automatic input type coercion. By default the returned UDF is deterministic. To change it to nondeterministic, call the API UserDefinedFunction.asNondeterministic().
    
    Parameters:
    
    f - (undocumented)
    
    returnType - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.3.0
  - udf
```
public static UserDefinedFunction udf(UDF3<?,?,?,?> f,
                                      DataType returnType)
```
    Defines a Java UDF3 instance as user-defined function (UDF). The caller must specify the output data type, and there is no automatic input type coercion. By default the returned UDF is deterministic. To change it to nondeterministic, call the API UserDefinedFunction.asNondeterministic().
    
    Parameters:
    
    f - (undocumented)
    
    returnType - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.3.0
  - udf
```
public static UserDefinedFunction udf(UDF4<?,?,?,?,?> f,
                                      DataType returnType)
```
    Defines a Java UDF4 instance as user-defined function (UDF). The caller must specify the output data type, and there is no automatic input type coercion. By default the returned UDF is deterministic. To change it to nondeterministic, call the API UserDefinedFunction.asNondeterministic().
    
    Parameters:
    
    f - (undocumented)
    
    returnType - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.3.0
  - udf
```
public static UserDefinedFunction udf(UDF5<?,?,?,?,?,?> f,
                                      DataType returnType)
```
    Defines a Java UDF5 instance as user-defined function (UDF). The caller must specify the output data type, and there is no automatic input type coercion. By default the returned UDF is deterministic. To change it to nondeterministic, call the API UserDefinedFunction.asNondeterministic().
    
    Parameters:
    
    f - (undocumented)
    
    returnType - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.3.0
  - udf
```
public static UserDefinedFunction udf(UDF6<?,?,?,?,?,?,?> f,
                                      DataType returnType)
```
    Defines a Java UDF6 instance as user-defined function (UDF). The caller must specify the output data type, and there is no automatic input type coercion. By default the returned UDF is deterministic. To change it to nondeterministic, call the API UserDefinedFunction.asNondeterministic().
    
    Parameters:
    
    f - (undocumented)
    
    returnType - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.3.0
  - udf
```
public static UserDefinedFunction udf(UDF7<?,?,?,?,?,?,?,?> f,
                                      DataType returnType)
```
    Defines a Java UDF7 instance as user-defined function (UDF). The caller must specify the output data type, and there is no automatic input type coercion. By default the returned UDF is deterministic. To change it to nondeterministic, call the API UserDefinedFunction.asNondeterministic().
    
    Parameters:
    
    f - (undocumented)
    
    returnType - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.3.0
  - udf
```
public static UserDefinedFunction udf(UDF8<?,?,?,?,?,?,?,?,?> f,
                                      DataType returnType)
```
    Defines a Java UDF8 instance as user-defined function (UDF). The caller must specify the output data type, and there is no automatic input type coercion. By default the returned UDF is deterministic. To change it to nondeterministic, call the API UserDefinedFunction.asNondeterministic().
    
    Parameters:
    
    f - (undocumented)
    
    returnType - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.3.0
  - udf
```
public static UserDefinedFunction udf(UDF9<?,?,?,?,?,?,?,?,?,?> f,
                                      DataType returnType)
```
    Defines a Java UDF9 instance as user-defined function (UDF). The caller must specify the output data type, and there is no automatic input type coercion. By default the returned UDF is deterministic. To change it to nondeterministic, call the API UserDefinedFunction.asNondeterministic().
    
    Parameters:
    
    f - (undocumented)
    
    returnType - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.3.0
  - udf
```
public static UserDefinedFunction udf(UDF10<?,?,?,?,?,?,?,?,?,?,?> f,
                                      DataType returnType)
```
    Defines a Java UDF10 instance as user-defined function (UDF). The caller must specify the output data type, and there is no automatic input type coercion. By default the returned UDF is deterministic. To change it to nondeterministic, call the API UserDefinedFunction.asNondeterministic().
    
    Parameters:
    
    f - (undocumented)
    
    returnType - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.3.0
  - udf
```
public static UserDefinedFunction udf(Object f,
                                      DataType dataType)
```
    Deprecated. Scala `udf` method with return type parameter is deprecated. Please use Scala `udf` method without return type parameter. Since 3.0.0.
    
    Defines a deterministic user-defined function (UDF) using a Scala closure. For this variant, the caller must specify the output data type, and there is no automatic input type coercion. By default the returned UDF is deterministic. To change it to nondeterministic, call the API UserDefinedFunction.asNondeterministic().
    Note that, although the Scala closure can have primitive-type function argument, it doesn't work well with null values. Because the Scala closure is passed in as Any type, there is no type information for the function arguments. Without the type information, Spark may blindly pass null to the Scala closure with primitive-type argument, and the closure will see the default value of the Java type for the null argument, e.g. udf((x: Int) => x, IntegerType), the result is 0 for null input.
    
    Parameters:
    
    f - A closure in Scala
    
    dataType - The output data type of the UDF
    
    Returns:
    
    (undocumented)
    
    Since:
    
    2.0.0
  - callUDF
```
public static Column callUDF(String udfName,
                             scala.collection.Seq<Column> cols)
```
    Call an user-defined function. Example:
```
  import org.apache.spark.sql._

  val df = Seq(("id1", 1), ("id2", 4), ("id3", 5)).toDF("id", "value")
  val spark = df.sparkSession
  spark.udf.register("simpleUDF", (v: Int) => v * v)
  df.select($"id", callUDF("simpleUDF", $"value"))
 
```
    Parameters:
    
    udfName - (undocumented)
    
    cols - (undocumented)
    
    Returns:
    
    (undocumented)
    
    Since:
    
    1.5.0

Class functions

Constructor Summary

Method Summary

Methods inherited from class Object

Constructor Detail

functions

Method Detail

countDistinct

countDistinct

array

array

map

coalesce

struct

struct

greatest

greatest

least

least

hash

xxhash64

concat_ws

format_string

concat

json_tuple

arrays_zip

map_concat

callUDF

col

column

lit

typedLit

asc

asc_nulls_first

asc_nulls_last

desc

desc_nulls_first

desc_nulls_last

approxCountDistinct

approxCountDistinct

approxCountDistinct

approxCountDistinct

approx_count_distinct

approx_count_distinct

approx_count_distinct

approx_count_distinct

avg

avg

collect_list

collect_list

collect_set

collect_set

corr

corr

count

count

countDistinct

countDistinct

covar_pop

covar_pop

covar_samp

covar_samp

first

first

first

first

grouping

grouping

grouping_id

grouping_id

kurtosis

kurtosis

last

last

last

last

max

max

mean

mean