pyspark.sql.DataFrameReader.orc¶

DataFrameReader.orc(path: Union[str, List[str]], mergeSchema: Optional[bool] = None, pathGlobFilter: Union[bool, str, None] = None, recursiveFileLookup: Union[bool, str, None] = None, modifiedBefore: Union[bool, str, None] = None, modifiedAfter: Union[bool, str, None] = None) → DataFrame[source]¶

Loads ORC files, returning the result as a DataFrame.

New in version 1.5.0.

Parameters

pathstr or list

Other Parameters

Extra options: For the extra options, refer to Data Source Option in the version you use.

Examples

>>> df = spark.read.orc('python/test_support/sql/orc_partitioned')
>>> df.dtypes
[('a', 'bigint'), ('b', 'int'), ('c', 'int')]

pyspark.sql.DataFrameReader.options pyspark.sql.DataFrameReader.parquet