pyspark.sql.DataFrameReader.orc¶
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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¶ Loads ORC files, returning the result as a
DataFrame.- 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')]