TestControlledMapReduceJob.java
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上传日期:2018-01-08
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文件大小:3k
源码类别:
网格计算
开发平台:
Java
- /**
- * 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.
- */
- package org.apache.hadoop.mapred;
- import java.util.Properties;
- import org.apache.commons.logging.Log;
- import org.apache.commons.logging.LogFactory;
- import org.apache.hadoop.mapred.ControlledMapReduceJob.ControlledMapReduceJobRunner;
- /**
- * Test to verify the controlled behavior of a ControlledMapReduceJob.
- *
- */
- public class TestControlledMapReduceJob extends ClusterMapReduceTestCase {
- static final Log LOG = LogFactory.getLog(TestControlledMapReduceJob.class);
- /**
- * Starts a job with 5 maps and 5 reduces. Then controls the finishing of
- * tasks. Signals finishing tasks in batches and then verifies their
- * completion.
- *
- * @throws Exception
- */
- public void testControlledMapReduceJob()
- throws Exception {
- Properties props = new Properties();
- props.setProperty("mapred.tasktracker.map.tasks.maximum", "2");
- props.setProperty("mapred.tasktracker.reduce.tasks.maximum", "2");
- startCluster(true, props);
- LOG.info("Started the cluster");
- ControlledMapReduceJobRunner jobRunner =
- ControlledMapReduceJobRunner
- .getControlledMapReduceJobRunner(createJobConf(), 7, 6);
- jobRunner.start();
- ControlledMapReduceJob controlledJob = jobRunner.getJob();
- JobInProgress jip =
- getMRCluster().getJobTrackerRunner().getJobTracker().getJob(
- jobRunner.getJobID());
- ControlledMapReduceJob.waitTillNTasksStartRunning(jip, true, 4);
- LOG.info("Finishing 3 maps");
- controlledJob.finishNTasks(true, 3);
- ControlledMapReduceJob.waitTillNTotalTasksFinish(jip, true, 3);
- ControlledMapReduceJob.waitTillNTasksStartRunning(jip, true, 4);
- LOG.info("Finishing 4 more maps");
- controlledJob.finishNTasks(true, 4);
- ControlledMapReduceJob.waitTillNTotalTasksFinish(jip, true, 7);
- ControlledMapReduceJob.waitTillNTasksStartRunning(jip, false, 4);
- LOG.info("Finishing 2 reduces");
- controlledJob.finishNTasks(false, 2);
- ControlledMapReduceJob.waitTillNTotalTasksFinish(jip, false, 2);
- ControlledMapReduceJob.waitTillNTasksStartRunning(jip, false, 4);
- LOG.info("Finishing 4 more reduces");
- controlledJob.finishNTasks(false, 4);
- ControlledMapReduceJob.waitTillNTotalTasksFinish(jip, false, 6);
- jobRunner.join();
- }
- }