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https://issues.apache.org/jira/browse/FLINK-11050?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17336543#comment-17336543
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Flink Jira Bot commented on FLINK-11050:
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This issue was labeled "stale-major" 7 ago and has not received any updates so
it is being deprioritized. If this ticket is actually Major, please raise the
priority and ask a committer to assign you the issue or revive the public
discussion.
> When IntervalJoin, get left or right buffer's entries more quickly by
> assigning lowerBound
> ------------------------------------------------------------------------------------------
>
> Key: FLINK-11050
> URL: https://issues.apache.org/jira/browse/FLINK-11050
> Project: Flink
> Issue Type: Improvement
> Components: Runtime / State Backends
> Affects Versions: 1.6.2, 1.7.0
> Reporter: Liu
> Priority: Major
> Labels: performance, pull-request-available, stale-major
> Time Spent: 10m
> Remaining Estimate: 0h
>
> When IntervalJoin, it is very slow to get left or right buffer's entries.
> Because we have to scan all buffer's values, including the deleted values
> which are out of time range. These deleted values's processing consumes too
> much time in RocksDB's level 0. Since lowerBound is known, it can be
> optimized by seek from the timestamp of lowerBound.
> Our usage is like below:
> {code:java}
> labelStream.keyBy(uuid).intervalJoin(adLogStream.keyBy(uuid))
> .between(Time.milliseconds(0), Time.milliseconds(600000))
> .process(new processFunction())
> .sink(kafkaProducer)
> {code}
> Our data is huge. The job always runs for an hour and is stuck by
> RocksDB's seek when get buffer's entries. We use rocksDB's data to simulate
> the problem RocksDB and find that it takes too much time in deleted values.
> So we decide to optimize it by assigning the lowerBound instead of global
> search.
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