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The following commit(s) were added to refs/heads/master by this push:
     new 9e7bfc54b2ce [MINOR][TESTS] Reduce the number of iterations in tuning 
tests
9e7bfc54b2ce is described below

commit 9e7bfc54b2ce6d8ce5b23aac366d9d9dbc80911d
Author: Ruifeng Zheng <ruife...@apache.org>
AuthorDate: Wed May 7 08:09:35 2025 +0900

    [MINOR][TESTS] Reduce the number of iterations in tuning tests
    
    ### What changes were proposed in this pull request?
    Reduce the number of iterations in tuning tests:
    
    - test_legacy_mode_tuning
    - test_connect_tuning
    
    ### Why are the changes needed?
    to speed up tests, they sometimes take more than 300sec, after this change 
150sec
    
    ### Does this PR introduce _any_ user-facing change?
    no. test-only
    
    ### How was this patch tested?
    ci
    
    ### Was this patch authored or co-authored using generative AI tooling?
    no
    
    Closes #50802 from zhengruifeng/test_legacy_num_iter.
    
    Authored-by: Ruifeng Zheng <ruife...@apache.org>
    Signed-off-by: Hyukjin Kwon <gurwls...@apache.org>
---
 python/pyspark/ml/tests/connect/test_legacy_mode_tuning.py | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/python/pyspark/ml/tests/connect/test_legacy_mode_tuning.py 
b/python/pyspark/ml/tests/connect/test_legacy_mode_tuning.py
index 6cee852247ad..c3da3dc6ed08 100644
--- a/python/pyspark/ml/tests/connect/test_legacy_mode_tuning.py
+++ b/python/pyspark/ml/tests/connect/test_legacy_mode_tuning.py
@@ -201,7 +201,7 @@ class CrossValidatorTestsMixin:
         lorv2 = LORV2(numTrainWorkers=2, featuresCol="scaled_features")
         pipeline = Pipeline(stages=[scaler, lorv2])
 
-        grid2 = ParamGridBuilder().addGrid(lorv2.maxIter, [2, 200]).build()
+        grid2 = ParamGridBuilder().addGrid(lorv2.maxIter, [2, 5]).build()
         cv = CrossValidator(
             estimator=pipeline,
             estimatorParamMaps=grid2,
@@ -219,7 +219,7 @@ class CrossValidatorTestsMixin:
         )
         pd.testing.assert_frame_equal(transformed_result, 
expected_transformed_result)
 
-        assert cv_model.bestModel.stages[1].getMaxIter() == 200
+        assert cv_model.bestModel.stages[1].getMaxIter() == 5
 
         # trial of index 2 should have better metric value
         # because it sets higher `maxIter` param.
@@ -246,7 +246,7 @@ class CrossValidatorTestsMixin:
             assert cv_model.bestModel.uid == loaded_cv_model.bestModel.uid
             assert cv_model.bestModel.stages[0].uid == 
loaded_cv_model.bestModel.stages[0].uid
             assert cv_model.bestModel.stages[1].uid == 
loaded_cv_model.bestModel.stages[1].uid
-            assert loaded_cv_model.bestModel.stages[1].getMaxIter() == 200
+            assert loaded_cv_model.bestModel.stages[1].getMaxIter() == 5
 
             np.testing.assert_allclose(cv_model.avgMetrics, 
loaded_cv_model.avgMetrics)
             np.testing.assert_allclose(cv_model.stdMetrics, 
loaded_cv_model.stdMetrics)
@@ -270,7 +270,7 @@ class CrossValidatorTestsMixin:
 
         lorv2 = LORV2(numTrainWorkers=2)
 
-        grid2 = ParamGridBuilder().addGrid(lorv2.maxIter, [2, 200]).build()
+        grid2 = ParamGridBuilder().addGrid(lorv2.maxIter, [2, 5]).build()
         cv = CrossValidator(
             estimator=lorv2,
             estimatorParamMaps=grid2,


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