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Posted to issues@spark.apache.org by "Dongjoon Hyun (JIRA)" <ji...@apache.org> on 2019/08/14 19:38:00 UTC
[jira] [Updated] (SPARK-28736) pyspark.mllib.clustering fails on
JDK11
[ https://issues.apache.org/jira/browse/SPARK-28736?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Dongjoon Hyun updated SPARK-28736:
----------------------------------
Description:
Build Spark and run PySpark UT with JDK11.
{code}
$ build/sbt -Phadoop-3.2 test:package
$ python/run-tests --testnames 'pyspark.mllib.clustering' --python-executables python
...
File "/Users/dongjoon/APACHE/spark-master/python/pyspark/mllib/clustering.py", line 386, in __main__.GaussianMixtureModel
Failed example:
abs(softPredicted[0] - 1.0) < 0.001
Expected:
True
Got:
False
**********************************************************************
File "/Users/dongjoon/APACHE/spark-master/python/pyspark/mllib/clustering.py", line 388, in __main__.GaussianMixtureModel
Failed example:
abs(softPredicted[1] - 0.0) < 0.001
Expected:
True
Got:
False
**********************************************************************
2 of 31 in __main__.GaussianMixtureModel
***Test Failed*** 2 failures.
{code}
was:
Build Spark and run PySpark UT with JDK11. The last commented `assertTrue` failed.
{code}
$ build/sbt -Phadoop-3.2 test:package
$ python/run-tests --testnames 'pyspark.ml.tests.test_algorithms' --python-executables python
...
======================================================================
FAIL: test_raw_and_probability_prediction (pyspark.ml.tests.test_algorithms.MultilayerPerceptronClassifierTest)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/Users/dongjoon/APACHE/spark-master/python/pyspark/ml/tests/test_algorithms.py", line 89, in test_raw_and_probability_prediction
self.assertTrue(np.allclose(result.rawPrediction, expected_rawPrediction, atol=1E-4))
AssertionError: False is not true
{code}
{code:python}
class MultilayerPerceptronClassifierTest(SparkSessionTestCase):
def test_raw_and_probability_prediction(self):
data_path = "data/mllib/sample_multiclass_classification_data.txt"
df = self.spark.read.format("libsvm").load(data_path)
mlp = MultilayerPerceptronClassifier(maxIter=100, layers=[4, 5, 4, 3],
blockSize=128, seed=123)
model = mlp.fit(df)
test = self.sc.parallelize([Row(features=Vectors.dense(0.1, 0.1, 0.25, 0.25))]).toDF()
result = model.transform(test).head()
expected_prediction = 2.0
expected_probability = [0.0, 0.0, 1.0]
expected_rawPrediction = [-11.6081922998, -8.15827998691, 22.17757045]
self.assertTrue(result.prediction, expected_prediction)
self.assertTrue(np.allclose(result.probability, expected_probability, atol=1E-4))
self.assertTrue(np.allclose(result.rawPrediction, expected_rawPrediction, atol=1E-4))
# self.assertTrue(np.allclose(result.rawPrediction, expected_rawPrediction, atol=1E-4))
{code}
> pyspark.mllib.clustering fails on JDK11
> ---------------------------------------
>
> Key: SPARK-28736
> URL: https://issues.apache.org/jira/browse/SPARK-28736
> Project: Spark
> Issue Type: Sub-task
> Components: PySpark
> Affects Versions: 3.0.0
> Reporter: Dongjoon Hyun
> Priority: Major
>
> Build Spark and run PySpark UT with JDK11.
> {code}
> $ build/sbt -Phadoop-3.2 test:package
> $ python/run-tests --testnames 'pyspark.mllib.clustering' --python-executables python
> ...
> File "/Users/dongjoon/APACHE/spark-master/python/pyspark/mllib/clustering.py", line 386, in __main__.GaussianMixtureModel
> Failed example:
> abs(softPredicted[0] - 1.0) < 0.001
> Expected:
> True
> Got:
> False
> **********************************************************************
> File "/Users/dongjoon/APACHE/spark-master/python/pyspark/mllib/clustering.py", line 388, in __main__.GaussianMixtureModel
> Failed example:
> abs(softPredicted[1] - 0.0) < 0.001
> Expected:
> True
> Got:
> False
> **********************************************************************
> 2 of 31 in __main__.GaussianMixtureModel
> ***Test Failed*** 2 failures.
> {code}
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