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  1. Beam
  2. BEAM-14064

ElasticSearchIO#Write buffering and outputting across windows

Details

    • Bug
    • Status: Resolved
    • P1
    • Resolution: Fixed
    • 2.35.0, 2.36.0, 2.37.0
    • 2.39.0
    • io-java-elasticsearch
    • None

    Description

      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

      pipeline.apply(
                  PubsubIO.readStrings().fromSubscription(subscription)
              ).apply(ParseJsons.of(OurObject::class.java))
                  .setCoder(KryoCoder.of())
      

      and

      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" }
      

      We recently tried upgrading 2.33 to 2.36 and immediately hit a bug in the consumer, due to alleged time skew, specifically

      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)
      

      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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