(spark) branch master updated: [SPARK-55020][PYTHON][TEST] Skip flaky test_distributed_lda test temporarily

[ru...@apache.org]

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ruifengz pushed a commit to branch master
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The following commit(s) were added to refs/heads/master by this push:
     new 44e38b56cf97 [SPARK-55020][PYTHON][TEST] Skip flaky test_distributed_lda test temporarily
44e38b56cf97 is described below

commit 44e38b56cf97874847f2238ea2c7e04b90aa3561
Author: Tian Gao <ga...@hotmail.com>
AuthorDate: Tue Jan 13 17:16:26 2026 +0800

    [SPARK-55020][PYTHON][TEST] Skip flaky test_distributed_lda test temporarily
    
    ### What changes were proposed in this pull request?
    
    Skip the flaky `test_distributed_lda`.
    
    ### Why are the changes needed?
    
    We had another real fix discussion in #53783 but it doesn't seem like we can merge it in 24 hours. Meanwhile this test is interrupting people's work. We will disable the test for now and re-enable it in #53783.
    
    ### Does this PR introduce _any_ user-facing change?
    
    No
    
    ### How was this patch tested?
    
    Disable test, CI should work.
    
    ### Was this patch authored or co-authored using generative AI tooling?
    
    No.
    
    Closes #53785 from gaogaotiantian/disable-flaky-test.
    
    Authored-by: Tian Gao <ga...@hotmail.com>
    Signed-off-by: Ruifeng Zheng <ru...@apache.org>
---
 python/pyspark/ml/tests/test_clustering.py | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/python/pyspark/ml/tests/test_clustering.py b/python/pyspark/ml/tests/test_clustering.py
index e22e97a5e7f1..8bd021903fba 100644
--- a/python/pyspark/ml/tests/test_clustering.py
+++ b/python/pyspark/ml/tests/test_clustering.py
@@ -16,6 +16,7 @@
 #
 
 import tempfile
+import unittest
 
 import numpy as np
 
@@ -383,6 +384,7 @@ class ClusteringTestsMixin:
             model2 = LocalLDAModel.load(d)
             self.assertEqual(str(model), str(model2))
 
+    @unittest.skip("SPARK-55020: Test triggers frequent deadlock in CI")
     def test_distributed_lda(self):
         spark = self.spark
         df = (


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