pyspark.sql.streaming.DataStreamWriter

class pyspark.sql.streaming.DataStreamWriter(df: DataFrame)[source]

Interface used to write a streaming DataFrame to external storage systems (e.g. file systems, key-value stores, etc). Use DataFrame.writeStream to access this.

New in version 2.0.0.

Changed in version 3.5.0: Supports Spark Connect.

Notes

This API is evolving.

Examples

The example below uses Rate source that generates rows continuously. After that, we operate a modulo by 3, and then writes the stream out to the console. The streaming query stops in 3 seconds.

>>> import time
>>> df = spark.readStream.format("rate").load()
>>> df = df.selectExpr("value % 3 as v")
>>> q = df.writeStream.format("console").start()
>>> time.sleep(3)
>>> q.stop()

Methods

foreach(f)

Sets the output of the streaming query to be processed using the provided writer f.

foreachBatch(func)

Sets the output of the streaming query to be processed using the provided function.

format(source)

Specifies the underlying output data source.

option(key, value)

Adds an output option for the underlying data source.

options(**options)

Adds output options for the underlying data source.

outputMode(outputMode)

Specifies how data of a streaming DataFrame/Dataset is written to a streaming sink.

partitionBy(*cols)

Partitions the output by the given columns on the file system.

queryName(queryName)

Specifies the name of the StreamingQuery that can be started with start().

start([path, format, outputMode, …])

Streams the contents of the DataFrame to a data source.

toTable(tableName[, format, outputMode, …])

Starts the execution of the streaming query, which will continually output results to the given table as new data arrives.

trigger(*[, processingTime, once, …])

Set the trigger for the stream query.