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https://issues.apache.org/jira/browse/SPARK-61325?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Hyukjin Kwon updated SPARK-61325:
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Fix Version/s: connect-rust-4.3.0
> Pin the Python hash seed of the official Connect test runs so that the
> default pyspark.ml seeds are the same in every run
> -------------------------------------------------------------------------------------------------------------------------
>
> Key: SPARK-61325
> URL: https://issues.apache.org/jira/browse/SPARK-61325
> Project: Spark
> Issue Type: Test
> Components: Connect
> Affects Versions: connect-rust-4.3.0
> Reporter: Hyukjin Kwon
> Priority: Major
> Fix For: connect-rust-4.3.0
>
>
> The official Connect test runs of scripts/run_official_tests.py (the "Connect
> drop-in" and "Connect parity" CI jobs) run with a random Python hash seed.
> The default seed of a pyspark.ml estimator is hash(type(self).__name__)
> (HasSeed), so the random k-fold split of CrossValidator differs per run. In
> about 7% of the runs (22 of 300 seeds: 19, 66, 97, ...), the official
> test_crossvalidator_with_random_forest_classifier
> (pyspark/ml/tests/connect/test_parity_tuning.py) trains a fold on label 0
> only and fails with "requirement failed: rawPredictionCol vectors must have
> length=2, but got 1". The official 4.3.0 client fails the same way for the
> same seeds, so this is the test's randomness, not a client bug. It failed the
> drop-in job of master at 094f47b6
> (https://github.com/apache/spark-connect-rust/actions/runs/42717540506).
> Set PYTHONHASHSEED=0 for the test processes of run_official_tests.py, so that
> the default seeds are the same in every run (the default seed of
> CrossValidator is then -3087263388934076904, which passes on both clients).
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