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new a28977e25801 [SPARK-51711][ML][PYTHON][CONNECT] Propagates the active
remote spark session to new threads to fix CrossValidator
a28977e25801 is described below
commit a28977e25801bf30ea962b55339da6d2eed24863
Author: Xi Lyu <xi....@databricks.com>
AuthorDate: Wed Apr 23 19:38:37 2025 +0800
[SPARK-51711][ML][PYTHON][CONNECT] Propagates the active remote spark
session to new threads to fix CrossValidator
### What changes were proposed in this pull request?
In SparkML with Spark Connect, the `_parallelFitTasks` fails when running
`CrossValidator` fitting, as the active remote spark session is not properly
propagated to the new threads.
Before the PR, this code will fail in the line `cvModel = cv.fit(data)`:
```
from pyspark.ml.classification import RandomForestClassifier
from pyspark.ml.evaluation import BinaryClassificationEvaluator
from pyspark.ml.tuning import ParamGridBuilder, CrossValidator
from pyspark.ml.linalg import Vectors
data = spark.createDataFrame([
(Vectors.dense(1.0, 2.0), 0),
(Vectors.dense(2.0, 3.0), 1),
(Vectors.dense(1.5, 2.5), 0),
(Vectors.dense(3.0, 4.0), 1),
(Vectors.dense(1.1, 2.1), 0),
(Vectors.dense(2.5, 3.5), 1),
], ["features", "label"])
rf = RandomForestClassifier(labelCol="label", featuresCol="features")
evaluator = BinaryClassificationEvaluator(labelCol="label")
paramGrid = (ParamGridBuilder()
.addGrid(rf.maxDepth, [2])
.addGrid(rf.numTrees, [5, 10])
.build())
cv = CrossValidator(estimator=rf,
estimatorParamMaps=paramGrid,
evaluator=evaluator,
numFolds=3)
cvModel = cv.fit(data)
bestModel = cvModel.bestModel
print(f"Best maxDepth: {bestModel.getMaxDepth()}")
print(f"Best maxBins: {bestModel.getMaxBins()}")
print(f"Best numTrees: {bestModel.getNumTrees}")
```
It fails because the active remote spark session is not properly set on
that thread:
```
File ~/spark/python/pyspark/ml/util.py:250, in
try_remote_call.<locals>.wrapped(self, name, *args)
247 from pyspark.ml.connect.serialize import serialize, deserialize
249 session = SparkSession.getActiveSession()
--> 250 assert session is not None
251 assert isinstance(self._java_obj, str)
252 methods, obj_ref = _extract_id_methods(self._java_obj)
AssertionError:
```
With this fix, the above code snippet works correctly.
### Why are the changes needed?
It fixes a bug with CrossValidator fitting.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
New test.
### Was this patch authored or co-authored using generative AI tooling?
No.
Closes #50507 from xi-db/fix-parallelFitTasks.
Lead-authored-by: Xi Lyu <xi....@databricks.com>
Co-authored-by: Xi Lyu <159039256+xi...@users.noreply.github.com>
Signed-off-by: Ruifeng Zheng <ruife...@apache.org>
---
python/pyspark/ml/connect/tuning.py | 2 +-
python/pyspark/ml/tests/test_tuning.py | 25 ++++++++++++++++++++++++-
python/pyspark/util.py | 6 ++++++
3 files changed, 31 insertions(+), 2 deletions(-)
diff --git a/python/pyspark/ml/connect/tuning.py
b/python/pyspark/ml/connect/tuning.py
index 2bbc63ef4dc2..1ef055d25007 100644
--- a/python/pyspark/ml/connect/tuning.py
+++ b/python/pyspark/ml/connect/tuning.py
@@ -434,7 +434,7 @@ class CrossValidator(
tasks = _parallelFitTasks(est, train, eva, validation, epm)
if not is_remote():
- tasks = list(map(inheritable_thread_target, tasks))
+ tasks =
list(map(inheritable_thread_target(dataset.sparkSession), tasks))
for j, metric in pool.imap_unordered(lambda f: f(), tasks):
metrics_all[i][j] = metric
diff --git a/python/pyspark/ml/tests/test_tuning.py
b/python/pyspark/ml/tests/test_tuning.py
index 0b79373f9991..5885761272a2 100644
--- a/python/pyspark/ml/tests/test_tuning.py
+++ b/python/pyspark/ml/tests/test_tuning.py
@@ -22,7 +22,7 @@ import numpy as np
from pyspark.ml.evaluation import BinaryClassificationEvaluator
from pyspark.ml.linalg import Vectors
-from pyspark.ml.classification import LogisticRegression
+from pyspark.ml.classification import LogisticRegression,
RandomForestClassifier
from pyspark.ml.tuning import (
ParamGridBuilder,
CrossValidator,
@@ -94,6 +94,7 @@ class TuningTestsMixin:
self.assertEqual(str(tvs_model.getEstimator()),
str(model2.getEstimator()))
self.assertEqual(str(tvs_model.getEvaluator()),
str(model2.getEvaluator()))
+ @unittest.skip("Disabled due to a Python side reference count issue in
_parallelFitTasks.")
def test_cross_validator(self):
dataset = self.spark.createDataFrame(
[
@@ -246,6 +247,28 @@ class TuningTestsMixin:
with self.assertRaisesRegex(Exception, "The validation data at fold 3
is empty"):
cv.fit(dataset_with_folds)
+ def test_crossvalidator_with_random_forest_classifier(self):
+ dataset = self.spark.createDataFrame(
+ [
+ (Vectors.dense(1.0, 2.0), 0),
+ (Vectors.dense(2.0, 3.0), 1),
+ (Vectors.dense(1.5, 2.5), 0),
+ (Vectors.dense(3.0, 4.0), 1),
+ (Vectors.dense(1.1, 2.1), 0),
+ (Vectors.dense(2.5, 3.5), 1),
+ ],
+ ["features", "label"],
+ )
+ rf = RandomForestClassifier(labelCol="label", featuresCol="features")
+ evaluator = BinaryClassificationEvaluator(labelCol="label")
+ paramGrid = (
+ ParamGridBuilder().addGrid(rf.maxDepth, [2]).addGrid(rf.numTrees,
[5, 10]).build()
+ )
+ cv = CrossValidator(
+ estimator=rf, estimatorParamMaps=paramGrid, evaluator=evaluator,
numFolds=3
+ )
+ cv.fit(dataset)
+
class TuningTests(TuningTestsMixin, ReusedSQLTestCase):
pass
diff --git a/python/pyspark/util.py b/python/pyspark/util.py
index 2a2bd8d6aea7..605f4f070b5a 100644
--- a/python/pyspark/util.py
+++ b/python/pyspark/util.py
@@ -397,6 +397,12 @@ def inheritable_thread_target(f: Optional[Union[Callable,
"SparkSession"]] = Non
@functools.wraps(ff)
def inner(*args: Any, **kwargs: Any) -> Any:
+ # Propagates the active remote spark session to the current
thread.
+ from pyspark.sql.connect.session import SparkSession as
RemoteSparkSession
+
+ RemoteSparkSession._set_default_and_active_session(
+ session # type: ignore[arg-type]
+ )
# Set thread locals in child thread.
for attr, value in session_client_thread_local_attrs:
setattr(
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