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https://issues.apache.org/jira/browse/FLINK-6485?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Flink Jira Bot updated FLINK-6485:
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Labels: auto-deprioritized-major stale-minor (was:
auto-deprioritized-major)
I am the [Flink Jira Bot|https://github.com/apache/flink-jira-bot/] and I help
the community manage its development. I see this issues has been marked as
Minor but is unassigned and neither itself nor its Sub-Tasks have been updated
for 180 days. I have gone ahead and marked it "stale-minor". If this ticket is
still Minor, please either assign yourself or give an update. Afterwards,
please remove the label or in 7 days the issue will be deprioritized.
> Use buffering to avoid frequent memtable flushes for short intervals in
> RockdDB incremental checkpoints
> -------------------------------------------------------------------------------------------------------
>
> Key: FLINK-6485
> URL: https://issues.apache.org/jira/browse/FLINK-6485
> Project: Flink
> Issue Type: Improvement
> Components: Runtime / Checkpointing
> Reporter: Stefan Richter
> Priority: Minor
> Labels: auto-deprioritized-major, stale-minor
>
> The current implementation of incremental checkpoitns in RocksDB needs to
> flush the memtable to disk prior to a checkpoint and this will generate a SST
> file.
> What is required for fast checkpoint intervals is an alternative mechanism to
> quickly determine a delta from the previous incremental checkpoint to avoid
> this frequent flushing. This could be implemented through custom buffering
> inside the backend, e.g. a changelog buffer that is maintain up to a certain
> size.
> The buffer's content becomes part of the private state in the incremental
> snapshot and the buffer is dropped i) after each checkpoint or ii) after
> exceeding a certain size that justifies flushing and writing a new SST file.
> This mechanism should not be blocking, which we can achieve in the following
> way:
> 1) We have a clear upper limit to the buffer size (e.g. 64MB), once the limit
> of diffs is reached, we can drop the buffer because we can assume enough work
> was done to justify a new SST file
> 2) We write the buffer to a local FS, so we can expect this to be reasonable
> fast and that it will not suffer from the kind of blocking that we have in
> DFS. I mean technically, also flushing the SST file can block. Then, in the
> async part, we can transfer the locally written buffer file to DFS.
> There might be other mechanisms in RocksDB that we could exploit for this,
> such as the write ahead log, but this could be already be a good solution.
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