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test_statcounter.py
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test_statcounter.py
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#
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
from pyspark.statcounter import StatCounter
from pyspark.testing.utils import ReusedPySparkTestCase
import math
class StatCounterTests(ReusedPySparkTestCase):
def test_base(self):
stats = self.sc.parallelize([1.0, 2.0, 3.0, 4.0]).stats()
self.assertEqual(stats.count(), 4)
self.assertEqual(stats.max(), 4.0)
self.assertEqual(stats.mean(), 2.5)
self.assertEqual(stats.min(), 1.0)
self.assertAlmostEqual(stats.stdev(), 1.118033988749895)
self.assertAlmostEqual(stats.sampleStdev(), 1.2909944487358056)
self.assertEqual(stats.sum(), 10.0)
self.assertAlmostEqual(stats.variance(), 1.25)
self.assertAlmostEqual(stats.sampleVariance(), 1.6666666666666667)
def test_as_dict(self):
stats = self.sc.parallelize([1.0, 2.0, 3.0, 4.0]).stats().asDict()
self.assertEqual(stats["count"], 4)
self.assertEqual(stats["max"], 4.0)
self.assertEqual(stats["mean"], 2.5)
self.assertEqual(stats["min"], 1.0)
self.assertAlmostEqual(stats["stdev"], 1.2909944487358056)
self.assertEqual(stats["sum"], 10.0)
self.assertAlmostEqual(stats["variance"], 1.6666666666666667)
stats = self.sc.parallelize([1.0, 2.0, 3.0, 4.0]).stats().asDict(sample=True)
self.assertEqual(stats["count"], 4)
self.assertEqual(stats["max"], 4.0)
self.assertEqual(stats["mean"], 2.5)
self.assertEqual(stats["min"], 1.0)
self.assertAlmostEqual(stats["stdev"], 1.118033988749895)
self.assertEqual(stats["sum"], 10.0)
self.assertAlmostEqual(stats["variance"], 1.25)
def test_merge(self):
stats = StatCounter([1.0, 2.0, 3.0, 4.0])
stats.merge(5.0)
self.assertEqual(stats.count(), 5)
self.assertEqual(stats.max(), 5.0)
self.assertEqual(stats.mean(), 3.0)
self.assertEqual(stats.min(), 1.0)
self.assertAlmostEqual(stats.stdev(), 1.414213562373095)
self.assertAlmostEqual(stats.sampleStdev(), 1.5811388300841898)
self.assertEqual(stats.sum(), 15.0)
self.assertAlmostEqual(stats.variance(), 2.0)
self.assertAlmostEqual(stats.sampleVariance(), 2.5)
def test_merge_stats(self):
stats1 = StatCounter([1.0, 2.0, 3.0, 4.0])
stats2 = StatCounter([1.0, 2.0, 3.0, 4.0])
stats = stats1.mergeStats(stats2)
self.assertEqual(stats.count(), 8)
self.assertEqual(stats.max(), 4.0)
self.assertEqual(stats.mean(), 2.5)
self.assertEqual(stats.min(), 1.0)
self.assertAlmostEqual(stats.stdev(), 1.118033988749895)
self.assertAlmostEqual(stats.sampleStdev(), 1.1952286093343936)
self.assertEqual(stats.sum(), 20.0)
self.assertAlmostEqual(stats.variance(), 1.25)
self.assertAlmostEqual(stats.sampleVariance(), 1.4285714285714286)
execution_statements = [
StatCounter([1.0, 2.0]).mergeStats(StatCounter(range(1, 301))),
StatCounter(range(1, 301)).mergeStats(StatCounter([1.0, 2.0])),
]
for stats in execution_statements:
self.assertEqual(stats.count(), 302)
self.assertEqual(stats.max(), 300.0)
self.assertEqual(stats.min(), 1.0)
self.assertAlmostEqual(stats.mean(), 149.51324503311)
self.assertAlmostEqual(stats.variance(), 7596.302804701549)
self.assertAlmostEqual(stats.sampleVariance(), 7621.539691095905)
def test_variance_when_size_zero(self):
# SPARK-38854: Test case to improve test coverage when
# StatCounter argument is empty list or None
arguments = [[], None]
for arg in arguments:
stats = StatCounter(arg)
self.assertTrue(math.isnan(stats.variance()))
self.assertTrue(math.isnan(stats.sampleVariance()))
self.assertEqual(stats.count(), 0)
self.assertTrue(math.isinf(stats.max()))
self.assertTrue(math.isinf(stats.min()))
self.assertEqual(stats.mean(), 0.0)
def test_merge_stats_with_self(self):
stats = StatCounter([1.0, 2.0, 3.0, 4.0])
stats.mergeStats(stats)
self.assertEqual(stats.count(), 8)
self.assertEqual(stats.max(), 4.0)
self.assertEqual(stats.mean(), 2.5)
self.assertEqual(stats.min(), 1.0)
self.assertAlmostEqual(stats.stdev(), 1.118033988749895)
self.assertAlmostEqual(stats.sampleStdev(), 1.1952286093343936)
self.assertEqual(stats.sum(), 20.0)
self.assertAlmostEqual(stats.variance(), 1.25)
self.assertAlmostEqual(stats.sampleVariance(), 1.4285714285714286)
if __name__ == "__main__":
import unittest
from pyspark.tests.test_statcounter import * # noqa: F401
try:
import xmlrunner
testRunner = xmlrunner.XMLTestRunner(output="target/test-reports", verbosity=2)
except ImportError:
testRunner = None
unittest.main(testRunner=testRunner, verbosity=2)