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[CI] ClassificationIT testWithCustomFeatureProcessors failing #134001

@elasticsearchmachine

Description

@elasticsearchmachine

Build Scans:

Reproduction Line:

./gradlew ":x-pack:plugin:ml:qa:native-multi-node-tests:javaRestTest" --tests "org.elasticsearch.xpack.ml.integration.ClassificationIT.testWithCustomFeatureProcessors" -Dtests.seed=E5D17EFE225D2AB6 -Dtests.locale=af-Latn-ZA -Dtests.timezone=America/North_Dakota/Center -Druntime.java=24

Applicable branches:
main

Reproduces locally?:
N/A

Failure History:
See dashboard

Failure Message:

java.lang.AssertionError: 
Expected: (a collection containing a string starting with "Created analytics with type [classification]" and a collection containing a string starting with "Estimated memory usage [" and a collection containing a string starting with "Starting analytics on node" and a collection containing a string starting with "Started analytics" and a collection containing a string starting with "Creating destination index [classification_with_custom_feature_processors_source_index_results]" and a collection containing a string starting with "Started reindexing to destination index [classification_with_custom_feature_processors_source_index_results]" and a collection containing a string starting with "Finished reindexing to destination index [classification_with_custom_feature_processors_source_index_results]" and a collection containing a string starting with "Started loading data" and a collection containing a string starting with "Started analyzing" and a collection con
[truncated]

Issue Reasons:

  • [main] 4 failures in test testWithCustomFeatureProcessors (0.9% fail rate in 455 executions)
  • [main] 2 failures in step part-4 (2.9% fail rate in 68 executions)
  • [main] 2 failures in pipeline elasticsearch-pull-request (2.9% fail rate in 68 executions)

Note:
This issue was created using new test triage automation. Please report issues or feedback to es-delivery.

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:mlMachine learning>test-failureTriaged test failures from CITeam:MLMeta label for the ML teamlow-riskAn open issue or test failure that is a low risk to future releases

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