318 lines
12 KiB
Python
318 lines
12 KiB
Python
#
|
|
# 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.
|
|
#
|
|
import os
|
|
import random
|
|
import shutil
|
|
import stat
|
|
import sys
|
|
import tempfile
|
|
import time
|
|
import unittest
|
|
|
|
from pyspark import SparkConf, SparkContext, TaskContext, BarrierTaskContext
|
|
from pyspark.testing.utils import PySparkTestCase, SPARK_HOME
|
|
|
|
if sys.version_info[0] >= 3:
|
|
xrange = range
|
|
|
|
|
|
class TaskContextTests(PySparkTestCase):
|
|
|
|
def setUp(self):
|
|
self._old_sys_path = list(sys.path)
|
|
class_name = self.__class__.__name__
|
|
# Allow retries even though they are normally disabled in local mode
|
|
self.sc = SparkContext('local[4, 2]', class_name)
|
|
|
|
def test_stage_id(self):
|
|
"""Test the stage ids are available and incrementing as expected."""
|
|
rdd = self.sc.parallelize(range(10))
|
|
stage1 = rdd.map(lambda x: TaskContext.get().stageId()).take(1)[0]
|
|
stage2 = rdd.map(lambda x: TaskContext.get().stageId()).take(1)[0]
|
|
# Test using the constructor directly rather than the get()
|
|
stage3 = rdd.map(lambda x: TaskContext().stageId()).take(1)[0]
|
|
self.assertEqual(stage1 + 1, stage2)
|
|
self.assertEqual(stage1 + 2, stage3)
|
|
self.assertEqual(stage2 + 1, stage3)
|
|
|
|
def test_resources(self):
|
|
"""Test the resources are empty by default."""
|
|
rdd = self.sc.parallelize(range(10))
|
|
resources1 = rdd.map(lambda x: TaskContext.get().resources()).take(1)[0]
|
|
# Test using the constructor directly rather than the get()
|
|
resources2 = rdd.map(lambda x: TaskContext().resources()).take(1)[0]
|
|
self.assertEqual(len(resources1), 0)
|
|
self.assertEqual(len(resources2), 0)
|
|
|
|
def test_partition_id(self):
|
|
"""Test the partition id."""
|
|
rdd1 = self.sc.parallelize(range(10), 1)
|
|
rdd2 = self.sc.parallelize(range(10), 2)
|
|
pids1 = rdd1.map(lambda x: TaskContext.get().partitionId()).collect()
|
|
pids2 = rdd2.map(lambda x: TaskContext.get().partitionId()).collect()
|
|
self.assertEqual(0, pids1[0])
|
|
self.assertEqual(0, pids1[9])
|
|
self.assertEqual(0, pids2[0])
|
|
self.assertEqual(1, pids2[9])
|
|
|
|
def test_attempt_number(self):
|
|
"""Verify the attempt numbers are correctly reported."""
|
|
rdd = self.sc.parallelize(range(10))
|
|
# Verify a simple job with no failures
|
|
attempt_numbers = rdd.map(lambda x: TaskContext.get().attemptNumber()).collect()
|
|
map(lambda attempt: self.assertEqual(0, attempt), attempt_numbers)
|
|
|
|
def fail_on_first(x):
|
|
"""Fail on the first attempt so we get a positive attempt number"""
|
|
tc = TaskContext.get()
|
|
attempt_number = tc.attemptNumber()
|
|
partition_id = tc.partitionId()
|
|
attempt_id = tc.taskAttemptId()
|
|
if attempt_number == 0 and partition_id == 0:
|
|
raise Exception("Failing on first attempt")
|
|
else:
|
|
return [x, partition_id, attempt_number, attempt_id]
|
|
result = rdd.map(fail_on_first).collect()
|
|
# We should re-submit the first partition to it but other partitions should be attempt 0
|
|
self.assertEqual([0, 0, 1], result[0][0:3])
|
|
self.assertEqual([9, 3, 0], result[9][0:3])
|
|
first_partition = filter(lambda x: x[1] == 0, result)
|
|
map(lambda x: self.assertEqual(1, x[2]), first_partition)
|
|
other_partitions = filter(lambda x: x[1] != 0, result)
|
|
map(lambda x: self.assertEqual(0, x[2]), other_partitions)
|
|
# The task attempt id should be different
|
|
self.assertTrue(result[0][3] != result[9][3])
|
|
|
|
def test_tc_on_driver(self):
|
|
"""Verify that getting the TaskContext on the driver returns None."""
|
|
tc = TaskContext.get()
|
|
self.assertTrue(tc is None)
|
|
|
|
def test_get_local_property(self):
|
|
"""Verify that local properties set on the driver are available in TaskContext."""
|
|
key = "testkey"
|
|
value = "testvalue"
|
|
self.sc.setLocalProperty(key, value)
|
|
try:
|
|
rdd = self.sc.parallelize(range(1), 1)
|
|
prop1 = rdd.map(lambda _: TaskContext.get().getLocalProperty(key)).collect()[0]
|
|
self.assertEqual(prop1, value)
|
|
prop2 = rdd.map(lambda _: TaskContext.get().getLocalProperty("otherkey")).collect()[0]
|
|
self.assertTrue(prop2 is None)
|
|
finally:
|
|
self.sc.setLocalProperty(key, None)
|
|
|
|
def test_barrier(self):
|
|
"""
|
|
Verify that BarrierTaskContext.barrier() performs global sync among all barrier tasks
|
|
within a stage.
|
|
"""
|
|
rdd = self.sc.parallelize(range(10), 4)
|
|
|
|
def f(iterator):
|
|
yield sum(iterator)
|
|
|
|
def context_barrier(x):
|
|
tc = BarrierTaskContext.get()
|
|
time.sleep(random.randint(1, 10))
|
|
tc.barrier()
|
|
return time.time()
|
|
|
|
times = rdd.barrier().mapPartitions(f).map(context_barrier).collect()
|
|
self.assertTrue(max(times) - min(times) < 1)
|
|
|
|
def test_barrier_infos(self):
|
|
"""
|
|
Verify that BarrierTaskContext.getTaskInfos() returns a list of all task infos in the
|
|
barrier stage.
|
|
"""
|
|
rdd = self.sc.parallelize(range(10), 4)
|
|
|
|
def f(iterator):
|
|
yield sum(iterator)
|
|
|
|
taskInfos = rdd.barrier().mapPartitions(f).map(lambda x: BarrierTaskContext.get()
|
|
.getTaskInfos()).collect()
|
|
self.assertTrue(len(taskInfos) == 4)
|
|
self.assertTrue(len(taskInfos[0]) == 4)
|
|
|
|
def test_context_get(self):
|
|
"""
|
|
Verify that TaskContext.get() works both in or not in a barrier stage.
|
|
"""
|
|
rdd = self.sc.parallelize(range(10), 4)
|
|
|
|
def f(iterator):
|
|
taskContext = TaskContext.get()
|
|
if isinstance(taskContext, BarrierTaskContext):
|
|
yield taskContext.partitionId() + 1
|
|
elif isinstance(taskContext, TaskContext):
|
|
yield taskContext.partitionId() + 2
|
|
else:
|
|
yield -1
|
|
|
|
# for normal stage
|
|
result1 = rdd.mapPartitions(f).collect()
|
|
self.assertTrue(result1 == [2, 3, 4, 5])
|
|
# for barrier stage
|
|
result2 = rdd.barrier().mapPartitions(f).collect()
|
|
self.assertTrue(result2 == [1, 2, 3, 4])
|
|
|
|
def test_barrier_context_get(self):
|
|
"""
|
|
Verify that BarrierTaskContext.get() should only works in a barrier stage.
|
|
"""
|
|
rdd = self.sc.parallelize(range(10), 4)
|
|
|
|
def f(iterator):
|
|
try:
|
|
taskContext = BarrierTaskContext.get()
|
|
except Exception:
|
|
yield -1
|
|
else:
|
|
yield taskContext.partitionId()
|
|
|
|
# for normal stage
|
|
result1 = rdd.mapPartitions(f).collect()
|
|
self.assertTrue(result1 == [-1, -1, -1, -1])
|
|
# for barrier stage
|
|
result2 = rdd.barrier().mapPartitions(f).collect()
|
|
self.assertTrue(result2 == [0, 1, 2, 3])
|
|
|
|
|
|
class TaskContextTestsWithWorkerReuse(unittest.TestCase):
|
|
|
|
def setUp(self):
|
|
class_name = self.__class__.__name__
|
|
conf = SparkConf().set("spark.python.worker.reuse", "true")
|
|
self.sc = SparkContext('local[2]', class_name, conf=conf)
|
|
|
|
def test_barrier_with_python_worker_reuse(self):
|
|
"""
|
|
Regression test for SPARK-25921: verify that BarrierTaskContext.barrier() with
|
|
reused python worker.
|
|
"""
|
|
# start a normal job first to start all workers and get all worker pids
|
|
worker_pids = self.sc.parallelize(range(2), 2).map(lambda x: os.getpid()).collect()
|
|
# the worker will reuse in this barrier job
|
|
rdd = self.sc.parallelize(range(10), 2)
|
|
|
|
def f(iterator):
|
|
yield sum(iterator)
|
|
|
|
def context_barrier(x):
|
|
tc = BarrierTaskContext.get()
|
|
time.sleep(random.randint(1, 10))
|
|
tc.barrier()
|
|
return (time.time(), os.getpid())
|
|
|
|
result = rdd.barrier().mapPartitions(f).map(context_barrier).collect()
|
|
times = list(map(lambda x: x[0], result))
|
|
pids = list(map(lambda x: x[1], result))
|
|
# check both barrier and worker reuse effect
|
|
self.assertTrue(max(times) - min(times) < 1)
|
|
for pid in pids:
|
|
self.assertTrue(pid in worker_pids)
|
|
|
|
def test_task_context_correct_with_python_worker_reuse(self):
|
|
"""Verify the task context correct when reused python worker"""
|
|
# start a normal job first to start all workers and get all worker pids
|
|
worker_pids = self.sc.parallelize(xrange(2), 2).map(lambda x: os.getpid()).collect()
|
|
# the worker will reuse in this barrier job
|
|
rdd = self.sc.parallelize(xrange(10), 2)
|
|
|
|
def context(iterator):
|
|
tp = TaskContext.get().partitionId()
|
|
try:
|
|
bp = BarrierTaskContext.get().partitionId()
|
|
except Exception:
|
|
bp = -1
|
|
|
|
yield (tp, bp, os.getpid())
|
|
|
|
# normal stage after normal stage
|
|
normal_result = rdd.mapPartitions(context).collect()
|
|
tps, bps, pids = zip(*normal_result)
|
|
print(tps)
|
|
self.assertTrue(tps == (0, 1))
|
|
self.assertTrue(bps == (-1, -1))
|
|
for pid in pids:
|
|
self.assertTrue(pid in worker_pids)
|
|
# barrier stage after normal stage
|
|
barrier_result = rdd.barrier().mapPartitions(context).collect()
|
|
tps, bps, pids = zip(*barrier_result)
|
|
self.assertTrue(tps == (0, 1))
|
|
self.assertTrue(bps == (0, 1))
|
|
for pid in pids:
|
|
self.assertTrue(pid in worker_pids)
|
|
# normal stage after barrier stage
|
|
normal_result2 = rdd.mapPartitions(context).collect()
|
|
tps, bps, pids = zip(*normal_result2)
|
|
self.assertTrue(tps == (0, 1))
|
|
self.assertTrue(bps == (-1, -1))
|
|
for pid in pids:
|
|
self.assertTrue(pid in worker_pids)
|
|
|
|
def tearDown(self):
|
|
self.sc.stop()
|
|
|
|
|
|
class TaskContextTestsWithResources(unittest.TestCase):
|
|
|
|
def setUp(self):
|
|
class_name = self.__class__.__name__
|
|
self.tempFile = tempfile.NamedTemporaryFile(delete=False)
|
|
self.tempFile.write(b'echo {\\"name\\": \\"gpu\\", \\"addresses\\": [\\"0\\"]}')
|
|
self.tempFile.close()
|
|
# create temporary directory for Worker resources coordination
|
|
self.tempdir = tempfile.NamedTemporaryFile(delete=False)
|
|
os.unlink(self.tempdir.name)
|
|
os.chmod(self.tempFile.name, stat.S_IRWXU | stat.S_IXGRP | stat.S_IRGRP |
|
|
stat.S_IROTH | stat.S_IXOTH)
|
|
conf = SparkConf().set("spark.test.home", SPARK_HOME)
|
|
conf = conf.set("spark.resources.dir", self.tempdir.name)
|
|
conf = conf.set("spark.worker.resource.gpu.discoveryScript", self.tempFile.name)
|
|
conf = conf.set("spark.worker.resource.gpu.amount", 1)
|
|
conf = conf.set("spark.task.resource.gpu.amount", "1")
|
|
conf = conf.set("spark.executor.resource.gpu.amount", "1")
|
|
self.sc = SparkContext('local-cluster[2,1,1024]', class_name, conf=conf)
|
|
|
|
def test_resources(self):
|
|
"""Test the resources are available."""
|
|
rdd = self.sc.parallelize(range(10))
|
|
resources = rdd.map(lambda x: TaskContext.get().resources()).take(1)[0]
|
|
self.assertEqual(len(resources), 1)
|
|
self.assertTrue('gpu' in resources)
|
|
self.assertEqual(resources['gpu'].name, 'gpu')
|
|
self.assertEqual(resources['gpu'].addresses, ['0'])
|
|
|
|
def tearDown(self):
|
|
os.unlink(self.tempFile.name)
|
|
shutil.rmtree(self.tempdir.name)
|
|
self.sc.stop()
|
|
|
|
if __name__ == "__main__":
|
|
import unittest
|
|
from pyspark.tests.test_taskcontext import *
|
|
|
|
try:
|
|
import xmlrunner
|
|
testRunner = xmlrunner.XMLTestRunner(output='target/test-reports', verbosity=2)
|
|
except ImportError:
|
|
testRunner = None
|
|
unittest.main(testRunner=testRunner, verbosity=2)
|