spark-instrumented-optimizer/python/pyspark/mllib
HyukjinKwon ef142371e7 [SPARK-28736][SPARK-28735][PYTHON][ML] Fix PySpark ML tests to pass in JDK 11
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### What changes were proposed in this pull request?
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This PR proposes to fix both tests below:

```
======================================================================
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
```

```
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
```

to pass in JDK 11.

The root cause seems to be different float values being understood via Py4J. This issue also was found in https://github.com/apache/spark/pull/25132 before.

When floats are transferred from Python to JVM, the values are sent as are. Python floats are not "precise" due to its own limitation - https://docs.python.org/3/tutorial/floatingpoint.html.
For some reasons, the floats from Python on JDK 8 and JDK 11 are different, which is already explicitly not guaranteed.

This seems why only some tests in PySpark with floats are being failed.

So, this PR fixes it by increasing tolerance in identified test cases in PySpark.

### Why are the changes needed?
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  1. If you propose a new API, clarify the use case for a new API.
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To fully support JDK 11. See, for instance, https://github.com/apache/spark/pull/25443 and https://github.com/apache/spark/pull/25423 for ongoing efforts.

### Does this PR introduce any user-facing change?
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No.

### How was this patch tested?
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Manually tested as described in JIRAs:

```
$ build/sbt -Phadoop-3.2 test:package
$ python/run-tests --testnames 'pyspark.ml.tests.test_algorithms' --python-executables python
```

```
$ build/sbt -Phadoop-3.2 test:package
$ python/run-tests --testnames 'pyspark.mllib.clustering' --python-executables python
```

Closes #25475 from HyukjinKwon/SPARK-28735.

Authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
2019-08-16 19:47:29 +09:00
..
linalg [SPARK-28140][MLLIB][PYTHON] Accept DataFrames in RowMatrix and IndexedRowMatrix constructors 2019-07-09 16:39:21 -05:00
stat [SPARK-28206][PYTHON] Remove the legacy Epydoc in PySpark API documentation 2019-07-05 10:08:22 -07:00
tests [SPARK-28140][MLLIB][PYTHON] Accept DataFrames in RowMatrix and IndexedRowMatrix constructors 2019-07-09 16:39:21 -05:00
__init__.py [SPARK-14817][ML][MLLIB][DOC] Made DataFrame-based API primary in MLlib guide 2016-07-15 13:38:23 -07:00
classification.py [SPARK-28206][PYTHON] Remove the legacy Epydoc in PySpark API documentation 2019-07-05 10:08:22 -07:00
clustering.py [SPARK-28736][SPARK-28735][PYTHON][ML] Fix PySpark ML tests to pass in JDK 11 2019-08-16 19:47:29 +09:00
common.py [SPARK-17679] [PYSPARK] remove unnecessary Py4J ListConverter patch 2016-10-03 14:12:03 -07:00
evaluation.py [SPARK-27540][MLLIB] Add 'meanAveragePrecision_at_k' metric to RankingMetrics 2019-05-09 08:47:05 -05:00
feature.py [SPARK-26616][MLLIB] Expose document frequency in IDFModel 2019-01-22 07:41:54 -06:00
fpm.py [SPARK-26640][CORE][ML][SQL][STREAMING][PYSPARK] Code cleanup from lgtm.com analysis 2019-01-17 19:40:39 -06:00
random.py [SPARK-28206][PYTHON] Remove the legacy Epydoc in PySpark API documentation 2019-07-05 10:08:22 -07:00
recommendation.py [SPARK-23643][CORE][SQL][ML] Shrinking the buffer in hashSeed up to size of the seed parameter 2019-03-23 11:26:09 -05:00
regression.py [SPARK-26640][CORE][ML][SQL][STREAMING][PYSPARK] Code cleanup from lgtm.com analysis 2019-01-17 19:40:39 -06:00
tree.py [SPARK-26640][CORE][ML][SQL][STREAMING][PYSPARK] Code cleanup from lgtm.com analysis 2019-01-17 19:40:39 -06:00
util.py [SPARK-28206][PYTHON] Remove the legacy Epydoc in PySpark API documentation 2019-07-05 10:08:22 -07:00