4ad9bfd53b
### What changes were proposed in this pull request? This PR aims to drop Python 2.7, 3.4 and 3.5. Roughly speaking, it removes all the widely known Python 2 compatibility workarounds such as `sys.version` comparison, `__future__`. Also, it removes the Python 2 dedicated codes such as `ArrayConstructor` in Spark. ### Why are the changes needed? 1. Unsupport EOL Python versions 2. Reduce maintenance overhead and remove a bit of legacy codes and hacks for Python 2. 3. PyPy2 has a critical bug that causes a flaky test, SPARK-28358 given my testing and investigation. 4. Users can use Python type hints with Pandas UDFs without thinking about Python version 5. Users can leverage one latest cloudpickle, https://github.com/apache/spark/pull/28950. With Python 3.8+ it can also leverage C pickle. ### Does this PR introduce _any_ user-facing change? Yes, users cannot use Python 2.7, 3.4 and 3.5 in the upcoming Spark version. ### How was this patch tested? Manually tested and also tested in Jenkins. Closes #28957 from HyukjinKwon/SPARK-32138. Authored-by: HyukjinKwon <gurwls223@apache.org> Signed-off-by: HyukjinKwon <gurwls223@apache.org>
109 lines
3.6 KiB
Python
109 lines
3.6 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 sys
|
|
import tempfile
|
|
import unittest
|
|
from io import StringIO
|
|
|
|
from pyspark import SparkConf, SparkContext, BasicProfiler
|
|
from pyspark.testing.utils import PySparkTestCase
|
|
|
|
|
|
class ProfilerTests(PySparkTestCase):
|
|
|
|
def setUp(self):
|
|
self._old_sys_path = list(sys.path)
|
|
class_name = self.__class__.__name__
|
|
conf = SparkConf().set("spark.python.profile", "true")
|
|
self.sc = SparkContext('local[4]', class_name, conf=conf)
|
|
|
|
def test_profiler(self):
|
|
self.do_computation()
|
|
|
|
profilers = self.sc.profiler_collector.profilers
|
|
self.assertEqual(1, len(profilers))
|
|
id, profiler, _ = profilers[0]
|
|
stats = profiler.stats()
|
|
self.assertTrue(stats is not None)
|
|
width, stat_list = stats.get_print_list([])
|
|
func_names = [func_name for fname, n, func_name in stat_list]
|
|
self.assertTrue("heavy_foo" in func_names)
|
|
|
|
old_stdout = sys.stdout
|
|
sys.stdout = io = StringIO()
|
|
self.sc.show_profiles()
|
|
self.assertTrue("heavy_foo" in io.getvalue())
|
|
sys.stdout = old_stdout
|
|
|
|
d = tempfile.gettempdir()
|
|
self.sc.dump_profiles(d)
|
|
self.assertTrue("rdd_%d.pstats" % id in os.listdir(d))
|
|
|
|
def test_custom_profiler(self):
|
|
class TestCustomProfiler(BasicProfiler):
|
|
def show(self, id):
|
|
self.result = "Custom formatting"
|
|
|
|
self.sc.profiler_collector.profiler_cls = TestCustomProfiler
|
|
|
|
self.do_computation()
|
|
|
|
profilers = self.sc.profiler_collector.profilers
|
|
self.assertEqual(1, len(profilers))
|
|
_, profiler, _ = profilers[0]
|
|
self.assertTrue(isinstance(profiler, TestCustomProfiler))
|
|
|
|
self.sc.show_profiles()
|
|
self.assertEqual("Custom formatting", profiler.result)
|
|
|
|
def do_computation(self):
|
|
def heavy_foo(x):
|
|
for i in range(1 << 18):
|
|
x = 1
|
|
|
|
rdd = self.sc.parallelize(range(100))
|
|
rdd.foreach(heavy_foo)
|
|
|
|
|
|
class ProfilerTests2(unittest.TestCase):
|
|
def test_profiler_disabled(self):
|
|
sc = SparkContext(conf=SparkConf().set("spark.python.profile", "false"))
|
|
try:
|
|
self.assertRaisesRegexp(
|
|
RuntimeError,
|
|
"'spark.python.profile' configuration must be set",
|
|
lambda: sc.show_profiles())
|
|
self.assertRaisesRegexp(
|
|
RuntimeError,
|
|
"'spark.python.profile' configuration must be set",
|
|
lambda: sc.dump_profiles("/tmp/abc"))
|
|
finally:
|
|
sc.stop()
|
|
|
|
|
|
if __name__ == "__main__":
|
|
from pyspark.tests.test_profiler import *
|
|
|
|
try:
|
|
import xmlrunner
|
|
testRunner = xmlrunner.XMLTestRunner(output='target/test-reports', verbosity=2)
|
|
except ImportError:
|
|
testRunner = None
|
|
unittest.main(testRunner=testRunner, verbosity=2)
|