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Posted to issues@spark.apache.org by "Dongjoon Hyun (JIRA)" <ji...@apache.org> on 2019/08/14 19:37:00 UTC
[jira] [Created] (SPARK-28736) pyspark.mllib.clustering fails on
JDK11
Dongjoon Hyun created SPARK-28736:
-------------------------------------
Summary: 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
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}
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