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.
Changed in version 3.4.0: Supports Spark Connect.
- Parameters
- pathstr or list
- Other Parameters
- Extra options
For the extra options, refer to Data Source Option for the version you use.
Examples
Write a DataFrame into a ORC file and read it back.
>>> import tempfile >>> with tempfile.TemporaryDirectory() as d: ... # Write a DataFrame into a ORC file ... spark.createDataFrame( ... [{"age": 100, "name": "Hyukjin Kwon"}] ... ).write.mode("overwrite").format("orc").save(d) ... ... # Read the Parquet file as a DataFrame. ... spark.read.orc(d).show() +---+------------+ |age| name| +---+------------+ |100|Hyukjin Kwon| +---+------------+