rangadi opened a new pull request, #40373:
URL: https://github.com/apache/spark/pull/40373
[This is not meant for merge, but a preliminary POC for streaming support in
Spark Connect].
This includes basic functionality to run streaming queries over spark
connect.
Expectation is 1:1 parity with standard streaming API.
How to try it in local mode ( `./bin/pyspark --remote "local[*]"`)
```
>>>
>>> query = (
... spark
... .readStream
... .format("rate")
... .option("numPartitions", "1")
... .load()
... .writeStream
... .format("memory")
... .queryName("rate_table")
... .start()
... )
>>> query.isActive
True
>>> query.status
{'message': 'Waiting for data to arrive', 'isDataAvailable': False,
'isTriggerActive': False}
>>> query.lastProgress
{'id': 'c962c6f4-7fcf-494a-a16d-ec107701fe66', 'runId':
'3f1b4c3d-648c-4da3-abe6-69b5b683d7ad', 'name': 'rate_table', 'timestamp':
'2023-03-10T21:33:12.424Z', 'batchId': 19, 'numInputRows': 1,
'inputRowsPerSecond': 76.92307692307692, 'processedRowsPerSecond': 6.25,
'durationMs': {'addBatch': 11, 'commitOffsets': 73, 'getBatch': 0,
'latestOffset': 0, 'queryPlanning': 1, 'triggerExecution': 160, 'walCommit':
75}, 'stateOperators': [], 'sources': [{'description':
'RateStreamV2[rowsPerSecond=1, rampUpTimeSeconds=0, numPartitions=1',
'startOffset': 18, 'endOffset': 19, 'latestOffset': 19, 'numInputRows': 1,
'inputRowsPerSecond': 76.92307692307692, 'processedRowsPerSecond': 6.25}],
'sink': {'description': 'MemorySink', 'numOutputRows': 1}}
>>> query.stop()
```
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