use of org.apache.hadoop.mapreduce.v2.hs.TestJobHistoryEvents.MRAppWithHistory in project hadoop by apache.
the class TestFetchFailure method testFetchFailureWithRecovery.
/**
* This tests that if a map attempt was failed (say due to fetch failures),
* then it gets re-run. When the next map attempt is running, if the AM dies,
* then, on AM re-run, the AM does not incorrectly remember the first failed
* attempt. Currently recovery does not recover running tasks. Effectively,
* the AM re-runs the maps from scratch.
*/
@Test
public void testFetchFailureWithRecovery() throws Exception {
int runCount = 0;
MRApp app = new MRAppWithHistory(1, 1, false, this.getClass().getName(), true, ++runCount);
Configuration conf = new Configuration();
// map -> reduce -> fetch-failure -> map retry is incompatible with
// sequential, single-task-attempt approach in uber-AM, so disable:
conf.setBoolean(MRJobConfig.JOB_UBERTASK_ENABLE, false);
Job job = app.submit(conf);
app.waitForState(job, JobState.RUNNING);
//all maps would be running
Assert.assertEquals("Num tasks not correct", 2, job.getTasks().size());
Iterator<Task> it = job.getTasks().values().iterator();
Task mapTask = it.next();
Task reduceTask = it.next();
//wait for Task state move to RUNNING
app.waitForState(mapTask, TaskState.RUNNING);
TaskAttempt mapAttempt1 = mapTask.getAttempts().values().iterator().next();
app.waitForState(mapAttempt1, TaskAttemptState.RUNNING);
//send the done signal to the map attempt
app.getContext().getEventHandler().handle(new TaskAttemptEvent(mapAttempt1.getID(), TaskAttemptEventType.TA_DONE));
// wait for map success
app.waitForState(mapTask, TaskState.SUCCEEDED);
TaskAttemptCompletionEvent[] events = job.getTaskAttemptCompletionEvents(0, 100);
Assert.assertEquals("Num completion events not correct", 1, events.length);
Assert.assertEquals("Event status not correct", TaskAttemptCompletionEventStatus.SUCCEEDED, events[0].getStatus());
// wait for reduce to start running
app.waitForState(reduceTask, TaskState.RUNNING);
TaskAttempt reduceAttempt = reduceTask.getAttempts().values().iterator().next();
app.waitForState(reduceAttempt, TaskAttemptState.RUNNING);
//send 3 fetch failures from reduce to trigger map re execution
sendFetchFailure(app, reduceAttempt, mapAttempt1, "host");
sendFetchFailure(app, reduceAttempt, mapAttempt1, "host");
sendFetchFailure(app, reduceAttempt, mapAttempt1, "host");
//wait for map Task state move back to RUNNING
app.waitForState(mapTask, TaskState.RUNNING);
// Crash the app again.
app.stop();
//rerun
app = new MRAppWithHistory(1, 1, false, this.getClass().getName(), false, ++runCount);
conf = new Configuration();
conf.setBoolean(MRJobConfig.MR_AM_JOB_RECOVERY_ENABLE, true);
conf.setBoolean(MRJobConfig.JOB_UBERTASK_ENABLE, false);
job = app.submit(conf);
app.waitForState(job, JobState.RUNNING);
//all maps would be running
Assert.assertEquals("Num tasks not correct", 2, job.getTasks().size());
it = job.getTasks().values().iterator();
mapTask = it.next();
reduceTask = it.next();
// the map is not in a SUCCEEDED state after restart of AM
app.waitForState(mapTask, TaskState.RUNNING);
mapAttempt1 = mapTask.getAttempts().values().iterator().next();
app.waitForState(mapAttempt1, TaskAttemptState.RUNNING);
//send the done signal to the map attempt
app.getContext().getEventHandler().handle(new TaskAttemptEvent(mapAttempt1.getID(), TaskAttemptEventType.TA_DONE));
// wait for map success
app.waitForState(mapTask, TaskState.SUCCEEDED);
reduceAttempt = reduceTask.getAttempts().values().iterator().next();
//send done to reduce
app.getContext().getEventHandler().handle(new TaskAttemptEvent(reduceAttempt.getID(), TaskAttemptEventType.TA_DONE));
app.waitForState(job, JobState.SUCCEEDED);
events = job.getTaskAttemptCompletionEvents(0, 100);
Assert.assertEquals("Num completion events not correct", 2, events.length);
}
use of org.apache.hadoop.mapreduce.v2.hs.TestJobHistoryEvents.MRAppWithHistory in project hadoop by apache.
the class TestRecovery method testRecoverySuccessUsingCustomOutputCommitter.
/**
* This test case primarily verifies if the recovery is controlled through config
* property. In this case, recover is turned ON. AM with 3 maps and 0 reduce.
* AM crashes after the first two tasks finishes and recovers completely and
* succeeds in the second generation.
*
* @throws Exception
*/
@Test
public void testRecoverySuccessUsingCustomOutputCommitter() throws Exception {
int runCount = 0;
MRApp app = new MRAppWithHistory(3, 0, false, this.getClass().getName(), true, ++runCount);
Configuration conf = new Configuration();
conf.setClass("mapred.output.committer.class", TestFileOutputCommitter.class, org.apache.hadoop.mapred.OutputCommitter.class);
conf.set(FileOutputFormat.OUTDIR, outputDir.toString());
conf.setBoolean("want.am.recovery", true);
Job job = app.submit(conf);
app.waitForState(job, JobState.RUNNING);
// all maps would be running
Assert.assertEquals("No of tasks not correct", 3, job.getTasks().size());
Iterator<Task> it = job.getTasks().values().iterator();
Task mapTask1 = it.next();
Task mapTask2 = it.next();
Task mapTask3 = it.next();
// all maps must be running
app.waitForState(mapTask1, TaskState.RUNNING);
app.waitForState(mapTask2, TaskState.RUNNING);
app.waitForState(mapTask3, TaskState.RUNNING);
TaskAttempt task1Attempt = mapTask1.getAttempts().values().iterator().next();
TaskAttempt task2Attempt = mapTask2.getAttempts().values().iterator().next();
TaskAttempt task3Attempt = mapTask3.getAttempts().values().iterator().next();
// before sending the TA_DONE, event make sure attempt has come to
// RUNNING state
app.waitForState(task1Attempt, TaskAttemptState.RUNNING);
app.waitForState(task2Attempt, TaskAttemptState.RUNNING);
app.waitForState(task3Attempt, TaskAttemptState.RUNNING);
// send the done signal to the 1st two maps
app.getContext().getEventHandler().handle(new TaskAttemptEvent(task1Attempt.getID(), TaskAttemptEventType.TA_DONE));
app.getContext().getEventHandler().handle(new TaskAttemptEvent(task2Attempt.getID(), TaskAttemptEventType.TA_DONE));
// wait for first two map task to complete
app.waitForState(mapTask1, TaskState.SUCCEEDED);
app.waitForState(mapTask2, TaskState.SUCCEEDED);
// stop the app
app.stop();
// rerun
// in rerun the 1st two map will be recovered from previous run
app = new MRAppWithHistory(2, 1, false, this.getClass().getName(), false, ++runCount);
conf = new Configuration();
conf.setClass("mapred.output.committer.class", TestFileOutputCommitter.class, org.apache.hadoop.mapred.OutputCommitter.class);
conf.setBoolean("want.am.recovery", true);
conf.set(FileOutputFormat.OUTDIR, outputDir.toString());
// Set num-reduces explicitly in conf as recovery logic depends on it.
conf.setInt(MRJobConfig.NUM_REDUCES, 0);
conf.setBoolean(MRJobConfig.JOB_UBERTASK_ENABLE, false);
job = app.submit(conf);
app.waitForState(job, JobState.RUNNING);
Assert.assertEquals("No of tasks not correct", 3, job.getTasks().size());
it = job.getTasks().values().iterator();
mapTask1 = it.next();
mapTask2 = it.next();
mapTask3 = it.next();
// first two maps will be recovered, no need to send done
app.waitForState(mapTask1, TaskState.SUCCEEDED);
app.waitForState(mapTask2, TaskState.SUCCEEDED);
app.waitForState(mapTask3, TaskState.RUNNING);
task3Attempt = mapTask3.getAttempts().values().iterator().next();
// before sending the TA_DONE, event make sure attempt has come to
// RUNNING state
app.waitForState(task3Attempt, TaskAttemptState.RUNNING);
// send the done signal to the 3rd map task
app.getContext().getEventHandler().handle(new TaskAttemptEvent(mapTask3.getAttempts().values().iterator().next().getID(), TaskAttemptEventType.TA_DONE));
// wait to get it completed
app.waitForState(mapTask3, TaskState.SUCCEEDED);
app.waitForState(job, JobState.SUCCEEDED);
app.verifyCompleted();
}
use of org.apache.hadoop.mapreduce.v2.hs.TestJobHistoryEvents.MRAppWithHistory in project hadoop by apache.
the class TestRecovery method testMultipleCrashes.
@Test
public void testMultipleCrashes() throws Exception {
int runCount = 0;
MRApp app = new MRAppWithHistory(2, 1, false, this.getClass().getName(), true, ++runCount);
Configuration conf = new Configuration();
conf.setBoolean("mapred.mapper.new-api", true);
conf.setBoolean("mapred.reducer.new-api", true);
conf.setBoolean(MRJobConfig.JOB_UBERTASK_ENABLE, false);
conf.set(FileOutputFormat.OUTDIR, outputDir.toString());
Job job = app.submit(conf);
app.waitForState(job, JobState.RUNNING);
//all maps would be running
Assert.assertEquals("No of tasks not correct", 3, job.getTasks().size());
Iterator<Task> it = job.getTasks().values().iterator();
Task mapTask1 = it.next();
Task mapTask2 = it.next();
Task reduceTask = it.next();
// all maps must be running
app.waitForState(mapTask1, TaskState.RUNNING);
app.waitForState(mapTask2, TaskState.RUNNING);
TaskAttempt task1Attempt1 = mapTask1.getAttempts().values().iterator().next();
TaskAttempt task2Attempt = mapTask2.getAttempts().values().iterator().next();
//before sending the TA_DONE, event make sure attempt has come to
//RUNNING state
app.waitForState(task1Attempt1, TaskAttemptState.RUNNING);
app.waitForState(task2Attempt, TaskAttemptState.RUNNING);
// reduces must be in NEW state
Assert.assertEquals("Reduce Task state not correct", TaskState.RUNNING, reduceTask.getReport().getTaskState());
//send the done signal to the 1st map
app.getContext().getEventHandler().handle(new TaskAttemptEvent(task1Attempt1.getID(), TaskAttemptEventType.TA_DONE));
//wait for first map task to complete
app.waitForState(mapTask1, TaskState.SUCCEEDED);
// Crash the app
app.stop();
//rerun
//in rerun the 1st map will be recovered from previous run
app = new MRAppWithHistory(2, 1, false, this.getClass().getName(), false, ++runCount);
conf = new Configuration();
conf.setBoolean(MRJobConfig.MR_AM_JOB_RECOVERY_ENABLE, true);
conf.setBoolean("mapred.mapper.new-api", true);
conf.setBoolean("mapred.reducer.new-api", true);
conf.set(FileOutputFormat.OUTDIR, outputDir.toString());
conf.setBoolean(MRJobConfig.JOB_UBERTASK_ENABLE, false);
job = app.submit(conf);
app.waitForState(job, JobState.RUNNING);
//all maps would be running
Assert.assertEquals("No of tasks not correct", 3, job.getTasks().size());
it = job.getTasks().values().iterator();
mapTask1 = it.next();
mapTask2 = it.next();
reduceTask = it.next();
// first map will be recovered, no need to send done
app.waitForState(mapTask1, TaskState.SUCCEEDED);
app.waitForState(mapTask2, TaskState.RUNNING);
task2Attempt = mapTask2.getAttempts().values().iterator().next();
//before sending the TA_DONE, event make sure attempt has come to
//RUNNING state
app.waitForState(task2Attempt, TaskAttemptState.RUNNING);
//send the done signal to the 2nd map task
app.getContext().getEventHandler().handle(new TaskAttemptEvent(mapTask2.getAttempts().values().iterator().next().getID(), TaskAttemptEventType.TA_DONE));
//wait to get it completed
app.waitForState(mapTask2, TaskState.SUCCEEDED);
// Crash the app again.
app.stop();
//rerun
//in rerun the 1st and 2nd map will be recovered from previous run
app = new MRAppWithHistory(2, 1, false, this.getClass().getName(), false, ++runCount);
conf = new Configuration();
conf.setBoolean(MRJobConfig.MR_AM_JOB_RECOVERY_ENABLE, true);
conf.setBoolean("mapred.mapper.new-api", true);
conf.setBoolean("mapred.reducer.new-api", true);
conf.set(FileOutputFormat.OUTDIR, outputDir.toString());
conf.setBoolean(MRJobConfig.JOB_UBERTASK_ENABLE, false);
job = app.submit(conf);
app.waitForState(job, JobState.RUNNING);
//all maps would be running
Assert.assertEquals("No of tasks not correct", 3, job.getTasks().size());
it = job.getTasks().values().iterator();
mapTask1 = it.next();
mapTask2 = it.next();
reduceTask = it.next();
// The maps will be recovered, no need to send done
app.waitForState(mapTask1, TaskState.SUCCEEDED);
app.waitForState(mapTask2, TaskState.SUCCEEDED);
//wait for reduce to be running before sending done
app.waitForState(reduceTask, TaskState.RUNNING);
//send the done signal to the reduce
app.getContext().getEventHandler().handle(new TaskAttemptEvent(reduceTask.getAttempts().values().iterator().next().getID(), TaskAttemptEventType.TA_DONE));
app.waitForState(job, JobState.SUCCEEDED);
app.verifyCompleted();
}
use of org.apache.hadoop.mapreduce.v2.hs.TestJobHistoryEvents.MRAppWithHistory in project hadoop by apache.
the class TestRecovery method testCrashOfMapsOnlyJob.
/**
* AM with 3 maps and 0 reduce. AM crashes after the first two tasks finishes
* and recovers completely and succeeds in the second generation.
*
* @throws Exception
*/
@Test
public void testCrashOfMapsOnlyJob() throws Exception {
int runCount = 0;
MRApp app = new MRAppWithHistory(3, 0, false, this.getClass().getName(), true, ++runCount);
Configuration conf = new Configuration();
conf.setBoolean("mapred.mapper.new-api", true);
conf.setBoolean(MRJobConfig.JOB_UBERTASK_ENABLE, false);
conf.set(FileOutputFormat.OUTDIR, outputDir.toString());
Job job = app.submit(conf);
app.waitForState(job, JobState.RUNNING);
// all maps would be running
Assert.assertEquals("No of tasks not correct", 3, job.getTasks().size());
Iterator<Task> it = job.getTasks().values().iterator();
Task mapTask1 = it.next();
Task mapTask2 = it.next();
Task mapTask3 = it.next();
// all maps must be running
app.waitForState(mapTask1, TaskState.RUNNING);
app.waitForState(mapTask2, TaskState.RUNNING);
app.waitForState(mapTask3, TaskState.RUNNING);
TaskAttempt task1Attempt = mapTask1.getAttempts().values().iterator().next();
TaskAttempt task2Attempt = mapTask2.getAttempts().values().iterator().next();
TaskAttempt task3Attempt = mapTask3.getAttempts().values().iterator().next();
// before sending the TA_DONE, event make sure attempt has come to
// RUNNING state
app.waitForState(task1Attempt, TaskAttemptState.RUNNING);
app.waitForState(task2Attempt, TaskAttemptState.RUNNING);
app.waitForState(task3Attempt, TaskAttemptState.RUNNING);
// send the done signal to the 1st two maps
app.getContext().getEventHandler().handle(new TaskAttemptEvent(task1Attempt.getID(), TaskAttemptEventType.TA_DONE));
app.getContext().getEventHandler().handle(new TaskAttemptEvent(task2Attempt.getID(), TaskAttemptEventType.TA_DONE));
// wait for first two map task to complete
app.waitForState(mapTask1, TaskState.SUCCEEDED);
app.waitForState(mapTask2, TaskState.SUCCEEDED);
// stop the app
app.stop();
// rerun
// in rerun the 1st two map will be recovered from previous run
app = new MRAppWithHistory(2, 1, false, this.getClass().getName(), false, ++runCount);
conf = new Configuration();
conf.setBoolean(MRJobConfig.MR_AM_JOB_RECOVERY_ENABLE, true);
conf.setBoolean("mapred.mapper.new-api", true);
conf.set(FileOutputFormat.OUTDIR, outputDir.toString());
// Set num-reduces explicitly in conf as recovery logic depends on it.
conf.setInt(MRJobConfig.NUM_REDUCES, 0);
conf.setBoolean(MRJobConfig.JOB_UBERTASK_ENABLE, false);
job = app.submit(conf);
app.waitForState(job, JobState.RUNNING);
Assert.assertEquals("No of tasks not correct", 3, job.getTasks().size());
it = job.getTasks().values().iterator();
mapTask1 = it.next();
mapTask2 = it.next();
mapTask3 = it.next();
// first two maps will be recovered, no need to send done
app.waitForState(mapTask1, TaskState.SUCCEEDED);
app.waitForState(mapTask2, TaskState.SUCCEEDED);
app.waitForState(mapTask3, TaskState.RUNNING);
task3Attempt = mapTask3.getAttempts().values().iterator().next();
// before sending the TA_DONE, event make sure attempt has come to
// RUNNING state
app.waitForState(task3Attempt, TaskAttemptState.RUNNING);
// send the done signal to the 3rd map task
app.getContext().getEventHandler().handle(new TaskAttemptEvent(mapTask3.getAttempts().values().iterator().next().getID(), TaskAttemptEventType.TA_DONE));
// wait to get it completed
app.waitForState(mapTask3, TaskState.SUCCEEDED);
app.waitForState(job, JobState.SUCCEEDED);
app.verifyCompleted();
}
use of org.apache.hadoop.mapreduce.v2.hs.TestJobHistoryEvents.MRAppWithHistory in project hadoop by apache.
the class TestRecovery method testOutputRecoveryMapsOnly.
@Test
public void testOutputRecoveryMapsOnly() throws Exception {
int runCount = 0;
MRApp app = new MRAppWithHistory(2, 1, false, this.getClass().getName(), true, ++runCount);
Configuration conf = new Configuration();
conf.setBoolean("mapred.mapper.new-api", true);
conf.setBoolean("mapred.reducer.new-api", true);
conf.setBoolean(MRJobConfig.JOB_UBERTASK_ENABLE, false);
conf.set(FileOutputFormat.OUTDIR, outputDir.toString());
Job job = app.submit(conf);
app.waitForState(job, JobState.RUNNING);
Assert.assertEquals("No of tasks not correct", 3, job.getTasks().size());
Iterator<Task> it = job.getTasks().values().iterator();
Task mapTask1 = it.next();
Task mapTask2 = it.next();
Task reduceTask1 = it.next();
// all maps must be running
app.waitForState(mapTask1, TaskState.RUNNING);
TaskAttempt task1Attempt1 = mapTask1.getAttempts().values().iterator().next();
//before sending the TA_DONE, event make sure attempt has come to
//RUNNING state
app.waitForState(task1Attempt1, TaskAttemptState.RUNNING);
// write output corresponding to map1 (This is just to validate that it is
//no included in the output)
writeBadOutput(task1Attempt1, conf);
//send the done signal to the map
app.getContext().getEventHandler().handle(new TaskAttemptEvent(task1Attempt1.getID(), TaskAttemptEventType.TA_DONE));
//wait for map task to complete
app.waitForState(mapTask1, TaskState.SUCCEEDED);
// Verify the shuffle-port
Assert.assertEquals(5467, task1Attempt1.getShufflePort());
//stop the app before the job completes.
app.stop();
//rerun
//in rerun the map will be recovered from previous run
app = new MRAppWithHistory(2, 1, false, this.getClass().getName(), false, ++runCount);
conf = new Configuration();
conf.setBoolean(MRJobConfig.MR_AM_JOB_RECOVERY_ENABLE, true);
conf.setBoolean("mapred.mapper.new-api", true);
conf.setBoolean("mapred.reducer.new-api", true);
conf.set(FileOutputFormat.OUTDIR, outputDir.toString());
conf.setBoolean(MRJobConfig.JOB_UBERTASK_ENABLE, false);
job = app.submit(conf);
app.waitForState(job, JobState.RUNNING);
Assert.assertEquals("No of tasks not correct", 3, job.getTasks().size());
it = job.getTasks().values().iterator();
mapTask1 = it.next();
mapTask2 = it.next();
reduceTask1 = it.next();
// map will be recovered, no need to send done
app.waitForState(mapTask1, TaskState.SUCCEEDED);
// Verify the shuffle-port after recovery
task1Attempt1 = mapTask1.getAttempts().values().iterator().next();
Assert.assertEquals(5467, task1Attempt1.getShufflePort());
app.waitForState(mapTask2, TaskState.RUNNING);
TaskAttempt task2Attempt1 = mapTask2.getAttempts().values().iterator().next();
//before sending the TA_DONE, event make sure attempt has come to
//RUNNING state
app.waitForState(task2Attempt1, TaskAttemptState.RUNNING);
//send the done signal to the map
app.getContext().getEventHandler().handle(new TaskAttemptEvent(task2Attempt1.getID(), TaskAttemptEventType.TA_DONE));
//wait for map task to complete
app.waitForState(mapTask2, TaskState.SUCCEEDED);
// Verify the shuffle-port
Assert.assertEquals(5467, task2Attempt1.getShufflePort());
app.waitForState(reduceTask1, TaskState.RUNNING);
TaskAttempt reduce1Attempt1 = reduceTask1.getAttempts().values().iterator().next();
// write output corresponding to reduce1
writeOutput(reduce1Attempt1, conf);
//send the done signal to the 1st reduce
app.getContext().getEventHandler().handle(new TaskAttemptEvent(reduce1Attempt1.getID(), TaskAttemptEventType.TA_DONE));
//wait for first reduce task to complete
app.waitForState(reduceTask1, TaskState.SUCCEEDED);
app.waitForState(job, JobState.SUCCEEDED);
app.verifyCompleted();
validateOutput();
}
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