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Posted to common-commits@hadoop.apache.org by sj...@apache.org on 2015/10/12 19:10:44 UTC
[04/50] [abbrv] hadoop git commit: MAPREDUCE-6335. Created MR job
based performance test driver for the timeline service v2. Contributed by
Sangjin Lee.
MAPREDUCE-6335. Created MR job based performance test driver for the timeline service v2. Contributed by Sangjin Lee.
(cherry picked from commit b689f5d43d3f5434a30fe52f1a7e12e1fc5c71f4)
Project: http://git-wip-us.apache.org/repos/asf/hadoop/repo
Commit: http://git-wip-us.apache.org/repos/asf/hadoop/commit/628e9c1e
Tree: http://git-wip-us.apache.org/repos/asf/hadoop/tree/628e9c1e
Diff: http://git-wip-us.apache.org/repos/asf/hadoop/diff/628e9c1e
Branch: refs/heads/YARN-2928-rebase
Commit: 628e9c1ee9e33ba664c951d7e6b2e08eda4eb3cc
Parents: 0ffb56f
Author: Zhijie Shen <zj...@apache.org>
Authored: Tue Apr 28 19:46:01 2015 -0700
Committer: Sangjin Lee <sj...@apache.org>
Committed: Sat Oct 10 14:39:30 2015 -0700
----------------------------------------------------------------------
hadoop-mapreduce-project/CHANGES.txt | 3 +
.../mapred/TimelineServicePerformanceV2.java | 298 +++++++++++++++++++
.../apache/hadoop/test/MapredTestDriver.java | 3 +
3 files changed, 304 insertions(+)
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http://git-wip-us.apache.org/repos/asf/hadoop/blob/628e9c1e/hadoop-mapreduce-project/CHANGES.txt
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diff --git a/hadoop-mapreduce-project/CHANGES.txt b/hadoop-mapreduce-project/CHANGES.txt
index 41bde85..b65876e 100644
--- a/hadoop-mapreduce-project/CHANGES.txt
+++ b/hadoop-mapreduce-project/CHANGES.txt
@@ -9,6 +9,9 @@ Branch YARN-2928: Timeline Server Next Generation: Phase 1
MAPREDUCE-6327. Made MR AM use timeline service v2 API to write history
events and counters. (Junping Du via zjshen)
+ MAPREDUCE-6335. Created MR job based performance test driver for the
+ timeline service v2. (Sangjin Lee via zjshen)
+
IMPROVEMENTS
OPTIMIZATIONS
http://git-wip-us.apache.org/repos/asf/hadoop/blob/628e9c1e/hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-jobclient/src/test/java/org/apache/hadoop/mapred/TimelineServicePerformanceV2.java
----------------------------------------------------------------------
diff --git a/hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-jobclient/src/test/java/org/apache/hadoop/mapred/TimelineServicePerformanceV2.java b/hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-jobclient/src/test/java/org/apache/hadoop/mapred/TimelineServicePerformanceV2.java
new file mode 100644
index 0000000..de46617
--- /dev/null
+++ b/hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-jobclient/src/test/java/org/apache/hadoop/mapred/TimelineServicePerformanceV2.java
@@ -0,0 +1,298 @@
+/**
+ * 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.io.IOException;
+import java.util.Date;
+import java.util.Random;
+
+import org.apache.commons.logging.Log;
+import org.apache.commons.logging.LogFactory;
+import org.apache.hadoop.conf.Configuration;
+import org.apache.hadoop.conf.Configured;
+import org.apache.hadoop.io.IntWritable;
+import org.apache.hadoop.io.Writable;
+import org.apache.hadoop.mapreduce.Job;
+import org.apache.hadoop.mapreduce.MRJobConfig;
+import org.apache.hadoop.mapreduce.SleepJob.SleepInputFormat;
+import org.apache.hadoop.mapreduce.TaskAttemptID;
+import org.apache.hadoop.mapreduce.lib.output.NullOutputFormat;
+import org.apache.hadoop.security.UserGroupInformation;
+import org.apache.hadoop.util.GenericOptionsParser;
+import org.apache.hadoop.util.Tool;
+import org.apache.hadoop.util.ToolRunner;
+import org.apache.hadoop.yarn.api.records.ApplicationId;
+import org.apache.hadoop.yarn.api.records.timelineservice.TimelineEntities;
+import org.apache.hadoop.yarn.api.records.timelineservice.TimelineEntity;
+import org.apache.hadoop.yarn.api.records.timelineservice.TimelineEvent;
+import org.apache.hadoop.yarn.api.records.timelineservice.TimelineMetric;
+import org.apache.hadoop.yarn.conf.YarnConfiguration;
+import org.apache.hadoop.yarn.server.timelineservice.collector.AppLevelTimelineCollector;
+import org.apache.hadoop.yarn.server.timelineservice.collector.TimelineCollectorContext;
+
+public class TimelineServicePerformanceV2 extends Configured implements Tool {
+ private static final Log LOG =
+ LogFactory.getLog(TimelineServicePerformanceV2.class);
+
+ static final int NUM_MAPS_DEFAULT = 1;
+
+ static final int SIMPLE_ENTITY_WRITER = 1;
+ // constants for mtype = 1
+ static final String KBS_SENT = "kbs sent";
+ static final int KBS_SENT_DEFAULT = 1;
+ static final String TEST_TIMES = "testtimes";
+ static final int TEST_TIMES_DEFAULT = 100;
+ static final String TIMELINE_SERVICE_PERFORMANCE_RUN_ID =
+ "timeline.server.performance.run.id";
+
+ static int mapperType = SIMPLE_ENTITY_WRITER;
+
+ protected static int printUsage() {
+ // TODO is there a way to handle mapper-specific options more gracefully?
+ System.err.println(
+ "Usage: [-m <maps>] number of mappers (default: " + NUM_MAPS_DEFAULT +
+ ")\n" +
+ " [-mtype <mapper type in integer>] \n" +
+ " 1. simple entity write mapper\n" +
+ " [-s <(KBs)test>] number of KB per put (default: " +
+ KBS_SENT_DEFAULT + " KB)\n" +
+ " [-t] package sending iterations per mapper (default: " +
+ TEST_TIMES_DEFAULT + ")\n");
+ GenericOptionsParser.printGenericCommandUsage(System.err);
+ return -1;
+ }
+
+ /**
+ * Configure a job given argv.
+ */
+ public static boolean parseArgs(String[] args, Job job) throws IOException {
+ // set the defaults
+ Configuration conf = job.getConfiguration();
+ conf.setInt(MRJobConfig.NUM_MAPS, NUM_MAPS_DEFAULT);
+ conf.setInt(KBS_SENT, KBS_SENT_DEFAULT);
+ conf.setInt(TEST_TIMES, TEST_TIMES_DEFAULT);
+
+ for (int i = 0; i < args.length; i++) {
+ if (args.length == i + 1) {
+ System.out.println("ERROR: Required parameter missing from " + args[i]);
+ return printUsage() == 0;
+ }
+ try {
+ if ("-m".equals(args[i])) {
+ if (Integer.parseInt(args[++i]) > 0) {
+ job.getConfiguration()
+ .setInt(MRJobConfig.NUM_MAPS, (Integer.parseInt(args[i])));
+ }
+ } else if ("-mtype".equals(args[i])) {
+ mapperType = Integer.parseInt(args[++i]);
+ switch (mapperType) {
+ case SIMPLE_ENTITY_WRITER:
+ job.setMapperClass(SimpleEntityWriter.class);
+ break;
+ default:
+ job.setMapperClass(SimpleEntityWriter.class);
+ }
+ } else if ("-s".equals(args[i])) {
+ if (Integer.parseInt(args[++i]) > 0) {
+ conf.setInt(KBS_SENT, (Integer.parseInt(args[i])));
+ }
+ } else if ("-t".equals(args[i])) {
+ if (Integer.parseInt(args[++i]) > 0) {
+ conf.setInt(TEST_TIMES, (Integer.parseInt(args[i])));
+ }
+ } else {
+ System.out.println("Unexpected argument: " + args[i]);
+ return printUsage() == 0;
+ }
+ } catch (NumberFormatException except) {
+ System.out.println("ERROR: Integer expected instead of " + args[i]);
+ return printUsage() == 0;
+ } catch (Exception e) {
+ throw (IOException)new IOException().initCause(e);
+ }
+ }
+
+ return true;
+ }
+
+ /**
+ * TimelineServer Performance counters
+ */
+ static enum PerfCounters {
+ TIMELINE_SERVICE_WRITE_TIME,
+ TIMELINE_SERVICE_WRITE_COUNTER,
+ TIMELINE_SERVICE_WRITE_FAILURES,
+ TIMELINE_SERVICE_WRITE_KBS,
+ }
+
+ public int run(String[] args) throws Exception {
+
+ Job job = Job.getInstance(getConf());
+ job.setJarByClass(TimelineServicePerformanceV2.class);
+ job.setMapperClass(SimpleEntityWriter.class);
+ job.setInputFormatClass(SleepInputFormat.class);
+ job.setOutputFormatClass(NullOutputFormat.class);
+ job.setNumReduceTasks(0);
+ if (!parseArgs(args, job)) {
+ return -1;
+ }
+
+ // for mtype = 1
+ // use the current timestamp as the "run id" of the test: this will be used
+ // as simulating the cluster timestamp for apps
+ Configuration conf = job.getConfiguration();
+ conf.setLong(TIMELINE_SERVICE_PERFORMANCE_RUN_ID,
+ System.currentTimeMillis());
+
+ Date startTime = new Date();
+ System.out.println("Job started: " + startTime);
+ int ret = job.waitForCompletion(true) ? 0 : 1;
+ org.apache.hadoop.mapreduce.Counters counters = job.getCounters();
+ long writetime =
+ counters.findCounter(PerfCounters.TIMELINE_SERVICE_WRITE_TIME).getValue();
+ long writecounts =
+ counters.findCounter(PerfCounters.TIMELINE_SERVICE_WRITE_COUNTER).getValue();
+ long writesize =
+ counters.findCounter(PerfCounters.TIMELINE_SERVICE_WRITE_KBS).getValue();
+ double transacrate = writecounts * 1000 / (double)writetime;
+ double iorate = writesize * 1000 / (double)writetime;
+ int numMaps = Integer.parseInt(conf.get(MRJobConfig.NUM_MAPS));
+
+ System.out.println("TRANSACTION RATE (per mapper): " + transacrate +
+ " ops/s");
+ System.out.println("IO RATE (per mapper): " + iorate + " KB/s");
+
+ System.out.println("TRANSACTION RATE (total): " + transacrate*numMaps +
+ " ops/s");
+ System.out.println("IO RATE (total): " + iorate*numMaps + " KB/s");
+
+ return ret;
+ }
+
+ public static void main(String[] args) throws Exception {
+ int res =
+ ToolRunner.run(new Configuration(), new TimelineServicePerformanceV2(),
+ args);
+ System.exit(res);
+ }
+
+ /**
+ * To ensure that the compression really gets exercised, generate a
+ * random alphanumeric fixed length payload
+ */
+ static final char[] alphaNums = new char[] { 'a', 'b', 'c', 'd', 'e', 'f',
+ 'g', 'h', 'i', 'j', 'k', 'l', 'm', 'n', 'o', 'p', 'q', 'r',
+ 's', 't', 'u', 'v', 'w', 'x', 'y', 'z', 'A', 'B', 'C', 'D',
+ 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'O', 'P',
+ 'Q', 'R', 'S', 'T', 'U', 'V', 'W', 'X', 'Y', 'Z', '1', '2',
+ '3', '4', '5', '6', '7', '8', '9', '0', ' ' };
+
+ /**
+ * Adds simple entities with random string payload, events, metrics, and
+ * configuration.
+ */
+ public static class SimpleEntityWriter
+ extends org.apache.hadoop.mapreduce.Mapper<IntWritable,IntWritable,Writable,Writable> {
+ public void map(IntWritable key, IntWritable val, Context context)
+ throws IOException {
+
+ Configuration conf = context.getConfiguration();
+ // simulate the app id with the task id
+ int taskId = context.getTaskAttemptID().getTaskID().getId();
+ long timestamp = conf.getLong(TIMELINE_SERVICE_PERFORMANCE_RUN_ID, 0);
+ ApplicationId appId = ApplicationId.newInstance(timestamp, taskId);
+
+ // create the app level timeline collector
+ Configuration tlConf = new YarnConfiguration();
+ AppLevelTimelineCollector collector =
+ new AppLevelTimelineCollector(appId);
+ collector.init(tlConf);
+ collector.start();
+
+ try {
+ // set the context
+ // flow id: job name, flow run id: timestamp, user id
+ TimelineCollectorContext tlContext =
+ collector.getTimelineEntityContext();
+ tlContext.setFlowName(context.getJobName());
+ tlContext.setFlowRunId(timestamp);
+ tlContext.setUserId(context.getUser());
+
+ final int kbs = Integer.parseInt(conf.get(KBS_SENT));
+
+ long totalTime = 0;
+ final int testtimes = Integer.parseInt(conf.get(TEST_TIMES));
+ final Random rand = new Random();
+ final TaskAttemptID taskAttemptId = context.getTaskAttemptID();
+ final char[] payLoad = new char[kbs * 1024];
+
+ for (int i = 0; i < testtimes; i++) {
+ // Generate a fixed length random payload
+ for (int xx = 0; xx < kbs * 1024; xx++) {
+ int alphaNumIdx = rand.nextInt(alphaNums.length);
+ payLoad[xx] = alphaNums[alphaNumIdx];
+ }
+ String entId = taskAttemptId + "_" + Integer.toString(i);
+ final TimelineEntity entity = new TimelineEntity();
+ entity.setId(entId);
+ entity.setType("FOO_ATTEMPT");
+ entity.addInfo("PERF_TEST", payLoad);
+ // add an event
+ TimelineEvent event = new TimelineEvent();
+ event.setTimestamp(System.currentTimeMillis());
+ event.addInfo("foo_event", "test");
+ entity.addEvent(event);
+ // add a metric
+ TimelineMetric metric = new TimelineMetric();
+ metric.setId("foo_metric");
+ metric.setSingleData(123456789L);
+ entity.addMetric(metric);
+ // add a config
+ entity.addConfig("foo", "bar");
+
+ TimelineEntities entities = new TimelineEntities();
+ entities.addEntity(entity);
+ // use the current user for this purpose
+ UserGroupInformation ugi = UserGroupInformation.getCurrentUser();
+ long startWrite = System.nanoTime();
+ try {
+ collector.putEntities(entities, ugi);
+ } catch (Exception e) {
+ context.getCounter(PerfCounters.TIMELINE_SERVICE_WRITE_FAILURES).
+ increment(1);
+ e.printStackTrace();
+ }
+ long endWrite = System.nanoTime();
+ totalTime += (endWrite-startWrite)/1000000L;
+ }
+ LOG.info("wrote " + testtimes + " entities (" + kbs*testtimes +
+ " kB) in " + totalTime + " ms");
+ context.getCounter(PerfCounters.TIMELINE_SERVICE_WRITE_TIME).
+ increment(totalTime);
+ context.getCounter(PerfCounters.TIMELINE_SERVICE_WRITE_COUNTER).
+ increment(testtimes);
+ context.getCounter(PerfCounters.TIMELINE_SERVICE_WRITE_KBS).
+ increment(kbs*testtimes);
+ } finally {
+ // clean up
+ collector.close();
+ }
+ }
+ }
+}
http://git-wip-us.apache.org/repos/asf/hadoop/blob/628e9c1e/hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-jobclient/src/test/java/org/apache/hadoop/test/MapredTestDriver.java
----------------------------------------------------------------------
diff --git a/hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-jobclient/src/test/java/org/apache/hadoop/test/MapredTestDriver.java b/hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-jobclient/src/test/java/org/apache/hadoop/test/MapredTestDriver.java
index 8fa82aa..5dcb143 100644
--- a/hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-jobclient/src/test/java/org/apache/hadoop/test/MapredTestDriver.java
+++ b/hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-jobclient/src/test/java/org/apache/hadoop/test/MapredTestDriver.java
@@ -28,6 +28,7 @@ import org.apache.hadoop.mapred.TestMapRed;
import org.apache.hadoop.mapred.TestSequenceFileInputFormat;
import org.apache.hadoop.mapred.TestTextInputFormat;
import org.apache.hadoop.mapred.ThreadedMapBenchmark;
+import org.apache.hadoop.mapred.TimelineServicePerformanceV2;
import org.apache.hadoop.mapreduce.FailJob;
import org.apache.hadoop.mapreduce.LargeSorter;
import org.apache.hadoop.mapreduce.MiniHadoopClusterManager;
@@ -90,6 +91,8 @@ public class MapredTestDriver {
pgd.addClass("fail", FailJob.class, "a job that always fails");
pgd.addClass("sleep", SleepJob.class,
"A job that sleeps at each map and reduce task.");
+ pgd.addClass("timelineperformance", TimelineServicePerformanceV2.class,
+ "A job that launch mappers to test timline service performance.");
pgd.addClass("nnbench", NNBench.class,
"A benchmark that stresses the namenode w/ MR.");
pgd.addClass("nnbenchWithoutMR", NNBenchWithoutMR.class,