HyukjinKwon commented on code in PR #39424: URL: https://github.com/apache/spark/pull/39424#discussion_r1065304753
########## python/pyspark/tests/test_stage_sched.py: ########## @@ -0,0 +1,140 @@ +# +# 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 tempfile +import unittest +import time +import shutil +import json + +from pyspark import SparkConf, SparkContext +from pyspark.resource.profile import ResourceProfileBuilder +from pyspark.resource.requests import TaskResourceRequests + + +class StageSchedulingTest(unittest.TestCase): + def setUp(self): + self.temp_dir = tempfile.mkdtemp() + + def tearDown(self): + shutil.rmtree(self.temp_dir, ignore_errors=True) + if getattr(self, "sc", None) is not None: + self.sc.stop() + self.sc = None + + def _test_stage_scheduling( + self, + cpus_per_worker, + gpus_per_worker, + num_tasks, + resource_profile, + expected_max_concurrent_tasks, + ): + conf = SparkConf() + conf.setMaster(f"local-cluster[1,{cpus_per_worker},1024]").set( + "spark.task.maxFailures", "1" + ) + + if gpus_per_worker: + worker_res_config_file = os.path.join(self.temp_dir, "worker_res.json") + worker_res = [ + { + "id": { + "componentName": "spark.worker", + "resourceName": "gpu", + }, + "addresses": [str(i) for i in range(gpus_per_worker)], + } + ] + with open(worker_res_config_file, "w") as fp: + json.dump(worker_res, fp) + + conf.set("spark.worker.resource.gpu.amount", str(gpus_per_worker)) + conf.set("spark.worker.resourcesFile", worker_res_config_file) + conf.set("spark.executor.resource.gpu.amount", str(gpus_per_worker)) + + self.sc = SparkContext(conf=conf) + pids_output_dir = os.path.join(self.temp_dir, "pids") + os.mkdir(pids_output_dir) + + def mapper(_): + from pyspark.taskcontext import TaskContext + + task_id = TaskContext.get().partitionId() + pid_file_path = os.path.join(pids_output_dir, str(task_id)) + with open(pid_file_path, mode="w"): + pass + time.sleep(0.1) + num_concurrent_tasks = len(os.listdir(pids_output_dir)) + time.sleep(1) + os.remove(pid_file_path) + return num_concurrent_tasks + + results = ( + self.sc.parallelize(range(num_tasks), num_tasks) + .withResources(resource_profile) + .map(mapper) + .collect() + ) + assert max(results) == expected_max_concurrent_tasks + + def test_stage_scheduling_4_cpus_per_task(self): + rp = ResourceProfileBuilder().require(TaskResourceRequests().cpus(4)).build + self._test_stage_scheduling( + cpus_per_worker=4, + gpus_per_worker=0, + num_tasks=2, + resource_profile=rp, + expected_max_concurrent_tasks=1, + ) + + def test_stage_scheduling_1_cpu_per_task(self): + rp = ResourceProfileBuilder().require(TaskResourceRequests().cpus(1)).build + self._test_stage_scheduling( + cpus_per_worker=4, + gpus_per_worker=0, + num_tasks=4, + resource_profile=rp, + expected_max_concurrent_tasks=4, + ) + + def test_stage_scheduling_2_cpus_2_gpus_per_task(self): + rp = ( + ResourceProfileBuilder() + .require(TaskResourceRequests().cpus(2).resource("gpu", 2)) + .build + ) + self._test_stage_scheduling( + cpus_per_worker=4, + gpus_per_worker=4, + num_tasks=4, + resource_profile=rp, + expected_max_concurrent_tasks=2, + ) + + +if __name__ == "__main__": + from pyspark.tests.test_memory_profiler import * # noqa: F401 Review Comment: I would actually name it something like `test_resource` -- 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. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected] --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
