2018-11-14 23:30:52 -05:00
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#
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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 os
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import sys
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import tempfile
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import threading
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import time
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2019-01-27 21:02:27 -05:00
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import unittest
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has_resource_module = True
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try:
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import resource
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except ImportError:
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has_resource_module = False
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2018-11-14 23:30:52 -05:00
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from py4j.protocol import Py4JJavaError
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2019-01-08 22:55:12 -05:00
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from pyspark.testing.utils import ReusedPySparkTestCase, PySparkTestCase, QuietTest
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2018-11-14 23:30:52 -05:00
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if sys.version_info[0] >= 3:
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xrange = range
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class WorkerTests(ReusedPySparkTestCase):
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def test_cancel_task(self):
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temp = tempfile.NamedTemporaryFile(delete=True)
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temp.close()
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path = temp.name
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def sleep(x):
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import os
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import time
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with open(path, 'w') as f:
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f.write("%d %d" % (os.getppid(), os.getpid()))
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time.sleep(100)
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# start job in background thread
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def run():
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try:
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self.sc.parallelize(range(1), 1).foreach(sleep)
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except Exception:
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pass
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import threading
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t = threading.Thread(target=run)
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t.daemon = True
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t.start()
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daemon_pid, worker_pid = 0, 0
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while True:
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if os.path.exists(path):
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with open(path) as f:
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data = f.read().split(' ')
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daemon_pid, worker_pid = map(int, data)
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break
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time.sleep(0.1)
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# cancel jobs
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self.sc.cancelAllJobs()
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t.join()
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for i in range(50):
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try:
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os.kill(worker_pid, 0)
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time.sleep(0.1)
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except OSError:
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break # worker was killed
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else:
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self.fail("worker has not been killed after 5 seconds")
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try:
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os.kill(daemon_pid, 0)
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except OSError:
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self.fail("daemon had been killed")
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# run a normal job
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rdd = self.sc.parallelize(xrange(100), 1)
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self.assertEqual(100, rdd.map(str).count())
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def test_after_exception(self):
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def raise_exception(_):
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raise Exception()
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rdd = self.sc.parallelize(xrange(100), 1)
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with QuietTest(self.sc):
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self.assertRaises(Exception, lambda: rdd.foreach(raise_exception))
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self.assertEqual(100, rdd.map(str).count())
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def test_after_jvm_exception(self):
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tempFile = tempfile.NamedTemporaryFile(delete=False)
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tempFile.write(b"Hello World!")
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tempFile.close()
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data = self.sc.textFile(tempFile.name, 1)
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filtered_data = data.filter(lambda x: True)
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self.assertEqual(1, filtered_data.count())
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os.unlink(tempFile.name)
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with QuietTest(self.sc):
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self.assertRaises(Exception, lambda: filtered_data.count())
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rdd = self.sc.parallelize(xrange(100), 1)
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self.assertEqual(100, rdd.map(str).count())
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def test_accumulator_when_reuse_worker(self):
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from pyspark.accumulators import INT_ACCUMULATOR_PARAM
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acc1 = self.sc.accumulator(0, INT_ACCUMULATOR_PARAM)
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self.sc.parallelize(xrange(100), 20).foreach(lambda x: acc1.add(x))
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self.assertEqual(sum(range(100)), acc1.value)
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acc2 = self.sc.accumulator(0, INT_ACCUMULATOR_PARAM)
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self.sc.parallelize(xrange(100), 20).foreach(lambda x: acc2.add(x))
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self.assertEqual(sum(range(100)), acc2.value)
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self.assertEqual(sum(range(100)), acc1.value)
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def test_reuse_worker_after_take(self):
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rdd = self.sc.parallelize(xrange(100000), 1)
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self.assertEqual(0, rdd.first())
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def count():
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try:
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rdd.count()
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except Exception:
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pass
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t = threading.Thread(target=count)
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t.daemon = True
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t.start()
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t.join(5)
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self.assertTrue(not t.isAlive())
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self.assertEqual(100000, rdd.count())
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def test_with_different_versions_of_python(self):
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rdd = self.sc.parallelize(range(10))
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rdd.count()
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version = self.sc.pythonVer
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self.sc.pythonVer = "2.0"
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try:
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with QuietTest(self.sc):
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self.assertRaises(Py4JJavaError, lambda: rdd.count())
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finally:
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self.sc.pythonVer = version
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2019-01-08 22:55:12 -05:00
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class WorkerReuseTest(PySparkTestCase):
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def test_reuse_worker_of_parallelize_xrange(self):
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rdd = self.sc.parallelize(xrange(20), 8)
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previous_pids = rdd.map(lambda x: os.getpid()).collect()
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current_pids = rdd.map(lambda x: os.getpid()).collect()
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for pid in current_pids:
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self.assertTrue(pid in previous_pids)
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2019-01-27 21:02:27 -05:00
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@unittest.skipIf(
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not has_resource_module,
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"Memory limit feature in Python worker is dependent on "
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"Python's 'resource' module; however, not found.")
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class WorkerMemoryTest(PySparkTestCase):
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def test_memory_limit(self):
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self.sc._conf.set("spark.executor.pyspark.memory", "1m")
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rdd = self.sc.parallelize(xrange(1), 1)
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def getrlimit():
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import resource
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return resource.getrlimit(resource.RLIMIT_AS)
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actual = rdd.map(lambda _: getrlimit()).collect()
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self.assertTrue(len(actual) == 1)
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self.assertTrue(len(actual[0]) == 2)
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[(soft_limit, hard_limit)] = actual
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self.assertEqual(soft_limit, 1024 * 1024)
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self.assertEqual(hard_limit, 1024 * 1024)
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2018-11-14 23:30:52 -05:00
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if __name__ == "__main__":
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import unittest
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from pyspark.tests.test_worker import *
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try:
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import xmlrunner
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2019-06-23 20:58:17 -04:00
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testRunner = xmlrunner.XMLTestRunner(output='target/test-reports', verbosity=2)
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2018-11-14 23:30:52 -05:00
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except ImportError:
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testRunner = None
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unittest.main(testRunner=testRunner, verbosity=2)
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