HyukjinKwon commented on a change in pull request #24898: [SPARK-22340][PYTHON] Add a mode to pin Python thread into JVM's URL: https://github.com/apache/spark/pull/24898#discussion_r339884667
########## File path: python/pyspark/tests/test_pin_thread.py ########## @@ -0,0 +1,156 @@ +# +# 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 time +import random +import threading +import unittest + +from pyspark import SparkContext, SparkConf + + +class PinThreadTests(unittest.TestCase): + # These tests are in a separate class because it uses + # 'PYSPARK_PIN_THREAD' environment variable to test thread pin feature. + + @classmethod + def setUpClass(cls): + cls.old_pin_thread = os.environ.get("PYSPARK_PIN_THREAD") + os.environ["PYSPARK_PIN_THREAD"] = "true" + cls.sc = SparkContext('local[4]', cls.__name__, conf=SparkConf()) + + @classmethod + def tearDownClass(cls): + cls.sc.stop() + if cls.old_pin_thread is not None: + os.environ["PYSPARK_PIN_THREAD"] = cls.old_pin_thread + else: + del os.environ["PYSPARK_PIN_THREAD"] + + def test_pinned_thread(self): + threads = [] + exceptions = [] + property_name = "test_property_%s" % PinThreadTests.__name__ + jvm_thread_ids = [] + + for i in range(10): + def test_local_property(): + jvm_thread_id = self.sc._jvm.java.lang.Thread.currentThread().getId() + jvm_thread_ids.append(jvm_thread_id) + + # If a property is set in this thread, later it should get the same property + # within this thread. + self.sc.setLocalProperty(property_name, str(i)) + + # Sleep for some arbitrary time. + time.sleep(random.random()) + + try: + assert self.sc.getLocalProperty(property_name) == str(i) + + # Each command might create a thread in multi-treading mode in Py4J. + # This assert makes sure that the created thread is being reused. + assert jvm_thread_id == self.sc._jvm.java.lang.Thread.currentThread().getId() + except Exception as e: + exceptions.append(e) + threads.append(threading.Thread(target=test_local_property)) + + for t in threads: + t.start() + + for t in threads: + t.join() + + for e in exceptions: + raise e + + # Created JVM threads should be 10 because Python thread are 10. + assert len(set(jvm_thread_ids)) == 10 + + def test_multiple_group_jobs(self): + # SPARK-22340 Add a mode to pin Python thread into JVM's + + group_a = "job_ids_to_cancel" + group_b = "job_ids_to_run" + + threads = [] + thread_ids = range(4) + thread_ids_to_cancel = [i for i in thread_ids if i % 2 == 0] + thread_ids_to_run = [i for i in thread_ids if i % 2 != 0] + + # A list which records whether job is cancelled. + # The index of the array is the thread index which job run in. + is_job_cancelled = [False for _ in thread_ids] + + def run_job(job_group, index): + """ + Executes a job with the group ``job_group``. Each job waits for 3 seconds + and then exits. + """ + try: + self.sc.setJobGroup(job_group, "test rdd collect with setting job group") + self.sc.parallelize([3]).map(lambda x: time.sleep(x)).collect() + is_job_cancelled[index] = False + except Exception: + # Assume that exception means job cancellation. + is_job_cancelled[index] = True + + # Test if job succeeded when not cancelled. + run_job(group_a, 0) + self.assertFalse(is_job_cancelled[0]) + + # Run jobs + for i in thread_ids_to_cancel: + t = threading.Thread(target=run_job, args=(group_a, i)) + t.start() + threads.append(t) + + for i in thread_ids_to_run: + t = threading.Thread(target=run_job, args=(group_b, i)) + t.start() + threads.append(t) + + # Wait to make sure all jobs are executed. + time.sleep(1) Review comment: Seems like `threading.Barrier` is new as of Python 3.2 and it won't work actually because `job_cancelled` will be serialized and deserialized at `sc.parallelize([3]).map(job_func)` .. :-(. Anyway I got the point - let me try to fix it ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services --------------------------------------------------------------------- To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
