a2fc48c28c
## What changes were proposed in this pull request? This PR breaks down the large mllib/tests.py file that contains all Python MLlib unit tests into several smaller test files to be easier to read and maintain. The tests are broken down as follows: ``` pyspark ├── __init__.py ... ├── mllib │ ├── __init__.py ... │ ├── tests │ │ ├── __init__.py │ │ ├── test_algorithms.py │ │ ├── test_feature.py │ │ ├── test_linalg.py │ │ ├── test_stat.py │ │ ├── test_streaming_algorithms.py │ │ └── test_util.py ... ├── testing ... │ ├── mllibutils.py ... ``` ## How was this patch tested? Ran tests manually by module to ensure test count was the same, and ran `python/run-tests --modules=pyspark-mllib` to verify all passing with Python 2.7 and Python 3.6. Also installed scipy to include optional tests in test_linalg. Closes #23056 from BryanCutler/python-test-breakup-mllib-SPARK-26034. Authored-by: Bryan Cutler <cutlerb@gmail.com> Signed-off-by: hyukjinkwon <gurwls223@apache.org>
45 lines
1.4 KiB
Python
45 lines
1.4 KiB
Python
#
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# Licensed to the Apache Software Foundation (ASF) under one or more
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# contributor license agreements. See the NOTICE file distributed with
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# this work for additional information regarding copyright ownership.
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# The ASF licenses this file to You under the Apache License, Version 2.0
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# (the "License"); you may not use this file except in compliance with
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# the License. You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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import sys
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if sys.version_info[:2] <= (2, 6):
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try:
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import unittest2 as unittest
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except ImportError:
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sys.stderr.write('Please install unittest2 to test with Python 2.6 or earlier')
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sys.exit(1)
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else:
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import unittest
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from pyspark import SparkContext
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from pyspark.serializers import PickleSerializer
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from pyspark.sql import SparkSession
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def make_serializer():
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return PickleSerializer()
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class MLlibTestCase(unittest.TestCase):
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def setUp(self):
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self.sc = SparkContext('local[4]', "MLlib tests")
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self.spark = SparkSession(self.sc)
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def tearDown(self):
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self.spark.stop()
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