pyspark.sql.DataFrameWriter.parquet¶

DataFrameWriter.parquet(path: str, mode: Optional[str] = None, partitionBy: Union[str, List[str], None] = None, compression: Optional[str] = None) → None[source]¶

Saves the content of the DataFrame in Parquet format at the specified path.

New in version 1.4.0.

Changed in version 3.4.0: Supports Spark Connect.

Parameters

pathstr

the path in any Hadoop supported file system

modestr, optional

specifies the behavior of the save operation when data already exists.

append: Append contents of this DataFrame to existing data.
overwrite: Overwrite existing data.
ignore: Silently ignore this operation if data already exists.
error or errorifexists (default case): Throw an exception if data already exists.

partitionBystr or list, optional

names of partitioning columns

Other Parameters

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

Examples

Write a DataFrame into a Parquet file and read it back.

>>> import tempfile
>>> with tempfile.TemporaryDirectory() as d:
...     # Write a DataFrame into a Parquet file
...     spark.createDataFrame(
...         [{"age": 100, "name": "Hyukjin Kwon"}]
...     ).write.parquet(d, mode="overwrite")
...
...     # Read the Parquet file as a DataFrame.
...     spark.read.format("parquet").load(d).show()
+---+------------+
|age|        name|
+---+------------+
|100|Hyukjin Kwon|
+---+------------+

pyspark.sql.DataFrameWriter.orc

pyspark.sql.DataFrameWriter.partitionBy