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https://issues.apache.org/jira/browse/BEAM-14064?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17503622#comment-17503622
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Etienne Chauchot commented on BEAM-14064:
-----------------------------------------

[~lcwik] thanks for opening this issue and [~egalpin] thanks for the fix! That 
being said, 2.37.0 is being deployed so I guess it is too late, this change 
will be put to 2.38 as 2.37 was cut before the change was merged. Adding the 
current ticket to the name of the PR/commits would have helped in merging it 
quicker (as the PR was sumitted before 2.37.0 cut) by making it obvious that it 
was linked to a (blocker) bug.

> ElasticSearchIO#Write buffering and outputting across windows
> -------------------------------------------------------------
>
>                 Key: BEAM-14064
>                 URL: https://issues.apache.org/jira/browse/BEAM-14064
>             Project: Beam
>          Issue Type: Bug
>          Components: io-java-elasticsearch
>    Affects Versions: 2.35.0, 2.36.0
>            Reporter: Luke Cwik
>            Assignee: Evan Galpin
>            Priority: P2
>
> Source: https://lists.apache.org/thread/mtwtno2o88lx3zl12jlz7o5w1lcgm2db
> Bug PR: https://github.com/apache/beam/pull/15381
> ElasticsearchIO is collecting results from elements in window X and then 
> trying to output them in window Y when flushing the batch. This exposed a bug 
> where elements that were being buffered were being output as part of a 
> different window than what the window that produced them was.
> This became visible because validation was added recently to ensure that when 
> the pipeline is processing elements in window X that output with a timestamp 
> is valid for window X. Note that this validation only occurs in 
> *@ProcessElement* since output is associated with the current window with the 
> input element that is being processed.
> It is ok to do this in *@FinishBundle* since there is no existing windowing 
> context and when you output that element is assigned to an appropriate window.
> *Further Context*
> We’ve bisected it to being introduced in 2.35.0, and I’m reasonably certain 
> it’s this PR https://github.com/apache/beam/pull/15381
> Our scenario is pretty trivial, we read off Pubsub and write to Elastic in a 
> streaming job, the config for the source and sink is respectively
> {noformat}
> pipeline.apply(
>             PubsubIO.readStrings().fromSubscription(subscription)
>         ).apply(ParseJsons.of(OurObject::class.java))
>             .setCoder(KryoCoder.of())
> {noformat}
> and
> {noformat}
> ElasticsearchIO.write()
>             .withUseStatefulBatches(true)
>             .withMaxParallelRequestsPerWindow(1)
>             .withMaxBufferingDuration(Duration.standardSeconds(30))
>             // 5 bytes **> KiB **> MiB, so 5 MiB
>             .withMaxBatchSizeBytes(5L * 1024 * 1024)
>             // # of docs
>             .withMaxBatchSize(1000)
>             .withConnectionConfiguration(
>                 ElasticsearchIO.ConnectionConfiguration.create(
>                     arrayOf(host),
>                     "fubar",
>                     "_doc"
>                 ).withConnectTimeout(5000)
>                     .withSocketTimeout(30000)
>             )
>             .withRetryConfiguration(
>                 ElasticsearchIO.RetryConfiguration.create(
>                     10,
>                     // the duration is wall clock, against the connection and 
> socket timeouts specified
>                     // above. I.e., 10 x 30s is gonna be more than 3 minutes, 
> so if we're getting
>                     // 10 socket timeouts in a row, this would ignore the 
> "10" part and terminate
>                     // after 6. The idea is that in a mixed failure mode, 
> you'd get different timeouts
>                     // of different durations, and on average 10 x fails < 4m.
>                     // That said, 4m is arbitrary, so adjust as and when 
> needed.
>                     Duration.standardMinutes(4)
>                 )
>             )
>             .withIdFn { f: JsonNode -> f["id"].asText() }
>             .withIndexFn { f: JsonNode -> f["schema_name"].asText() }
>             .withIsDeleteFn { f: JsonNode -> f["_action"].asText("noop") == 
> "delete" }
> {noformat}
> We recently tried upgrading 2.33 to 2.36 and immediately hit a bug in the 
> consumer, due to alleged time skew, specifically
> {noformat}
> 2022-03-07 10:48:37.886 GMTError message from worker: 
> java.lang.IllegalArgumentException: Cannot output with timestamp 
> 2022-03-07T10:43:38.640Z. Output timestamps must be no earlier than the 
> timestamp of the 
> current input (2022-03-07T10:43:43.562Z) minus the allowed skew (0 
> milliseconds) and no later than 294247-01-10T04:00:54.775Z. See the 
> DoFn#getAllowedTimestampSkew() Javadoc 
> for details on changing the allowed skew. 
> org.apache.beam.runners.dataflow.worker.repackaged.org.apache.beam.runners.core.SimpleDoFnRunner$DoFnProcessContext.checkTimestamp(SimpleDoFnRunner.java:446)
>  
> org.apache.beam.runners.dataflow.worker.repackaged.org.apache.beam.runners.core.SimpleDoFnRunner$DoFnProcessContext.outputWithTimestamp(SimpleDoFnRunner.java:422)
>  
> org.apache.beam.sdk.io.elasticsearch.ElasticsearchIO$BulkIO$BulkIOBaseFn$ProcessContextAdapter.output(ElasticsearchIO.java:2364)
>  
> org.apache.beam.sdk.io.elasticsearch.ElasticsearchIO$BulkIO$BulkIOBaseFn.flushAndOutputResults(ElasticsearchIO.java:2404)
> org.apache.beam.sdk.io.elasticsearch.ElasticsearchIO$BulkIO$BulkIOBaseFn.addAndMaybeFlush(ElasticsearchIO.java:2419)
> org.apache.beam.sdk.io.elasticsearch.ElasticsearchIO$BulkIO$BulkIOStatefulFn.processElement(ElasticsearchIO.java:2300)
> {noformat}
> I’ve bisected it and 2.34 works fine, 2.35 is the first version this breaks, 
> and it seems like the code in the trace is largely added by the PR linked 
> above. The error usually claims a skew of a few seconds, but obviously I 
> can’t override getAllowedTimestampSkew() on the internal Elastic DoFn, and 
> it’s marked deprecated anyway.
> I’m happy to raise a JIRA but I’m not 100% sure what the code was intending 
> to fix, and additionally, I’d also be happy if someone else can reproduce 
> this or knows of similar reports. I feel like what we’re doing is not that 
> uncommon a scenario, so I would have thought someone else would have hit this 
> by now.



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