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')]