bozhang2820 opened a new pull request #33763:
URL: https://github.com/apache/spark/pull/33763
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### What changes were proposed in this pull request?
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This change creates a new type of Trigger: Trigger.AvailableNow for
streaming queries. It is like Trigger.Once, which process all available data
then stop the query, but with better scalability since data can be processed in
multiple batches instead of one.
To achieve this, this change proposes a new interface
`SupportsTriggerAvailableNow`, which is an extension of
`SupportsAdmissionControl`. It has one method, `prepareForTriggerAvailableNow`,
which will be called at the beginning of streaming queries with
Trigger.AvailableNow, to let the source record the offset for the current
latest data at the time (a.k.a the target offset for the query). The source
should then behave as if there is no new data coming in after the beginning of
the query, i.e., the source will not return an offset higher than the target
offset when `latestOffset` is called.
This change also updates `FileStreamSource` to be an implementation of
`SupportsTriggerAvailableNow`.
For other sources that does not implement `SupportsTriggerAvailableNow`,
this change also provides a new class
`FakeLatestOffsetSupportsTriggerAvailableNow`, which wraps the sources and
makes them support Trigger.AvailableNow, by overriding their `latestOffset`
method to always return the latest offset `latestOffset` is first called. It is
as if there is no new data coming in from the source after the first
`latestOffset` call.
### Why are the changes needed?
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Currently streaming queries with Trigger.Once will always load all of the
available data in a single batch. Because of this, the amount of data the
queries can process is limited, or Spark driver will run out of memory.
### Does this PR introduce _any_ user-facing change?
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Users will be able to use Trigger.AvailableNow (to process all available
data then stop the streaming query) with this change.
### How was this patch tested?
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Added unit tests.
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