Merk
Tilgang til denne siden krever autorisasjon. Du kan prøve å logge på eller endre kataloger.
Tilgang til denne siden krever autorisasjon. Du kan prøve å endre kataloger.
Partitions the output by the given columns on the file system. If specified, the output is laid out on the file system similar to Hive's partitioning scheme.
Syntax
partitionBy(*cols)
Parameters
| Parameter | Type | Description |
|---|---|---|
*cols |
str or list | Names of the columns to partition by. |
Returns
DataFrameWriter
Examples
Write a DataFrame into a Parquet file in a partitioned manner, and read it back.
import tempfile, os
with tempfile.TemporaryDirectory(prefix="partitionBy") as d:
spark.createDataFrame(
[{"age": 100, "name": "Alice"}, {"age": 120, "name": "Ruifeng Zheng"}]
).write.partitionBy("name").mode("overwrite").format("parquet").save(d)
spark.read.parquet(d).sort("age").show()
# +---+-------------+
# |age| name|
# +---+-------------+
# |100| Alice|
# |120|Ruifeng Zheng|
# +---+-------------+
# Read one partition as a DataFrame.
spark.read.parquet(f"{d}{os.path.sep}name=Alice").show()
# +---+
# |age|
# +---+
# |100|
# +---+