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Streams the contents of the DataFrame to a data source and returns a StreamingQuery object.
Syntax
start(path=None, format=None, outputMode=None, partitionBy=None, queryName=None, **options)
Parameters
| Parameter | Type | Description |
|---|---|---|
path |
str, optional | Path in a Hadoop-supported file system. |
format |
str, optional | The format used to save. |
outputMode |
str, optional | How data is written to the sink: append, complete, or update. |
partitionBy |
str or list, optional | Names of partitioning columns. |
queryName |
str, optional | Unique name for the query. |
**options |
All other string options. Provide checkpointLocation for most streams; not required for a memory stream. |
Returns
StreamingQuery
Examples
df = spark.readStream.format("rate").load()
Basic example:
q = df.writeStream.format('memory').queryName('this_query').start()
q.isActive
# True
q.name
# 'this_query'
q.stop()
q.isActive
# False
With a trigger and additional parameters:
q = df.writeStream.trigger(processingTime='5 seconds').start(
queryName='that_query', outputMode="append", format='memory')
q.name
# 'that_query'
q.isActive
# True
q.stop()