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Example 76 with Job

use of org.apache.hadoop.mapreduce.v2.app.job.Job in project hadoop by apache.

the class JHEventHandlerForSigtermTest method testSigTermedFunctionality.

@Test
public /**
   * Tests that in case of SIGTERM, the JHEH stops without processing its event
   * queue (because we must stop quickly lest we get SIGKILLed) and processes
   * a JobUnsuccessfulEvent for jobs which were still running (so that they may
   * show up in the JobHistoryServer)
   */
void testSigTermedFunctionality() throws IOException {
    AppContext mockedContext = Mockito.mock(AppContext.class);
    JHEventHandlerForSigtermTest jheh = new JHEventHandlerForSigtermTest(mockedContext, 0);
    JobId jobId = Mockito.mock(JobId.class);
    jheh.addToFileMap(jobId);
    //Submit 4 events and check that they're handled in the absence of a signal
    final int numEvents = 4;
    JobHistoryEvent[] events = new JobHistoryEvent[numEvents];
    for (int i = 0; i < numEvents; ++i) {
        events[i] = getEventToEnqueue(jobId);
        jheh.handle(events[i]);
    }
    jheh.stop();
    //Make sure events were handled
    assertTrue("handleEvent should've been called only 4 times but was " + jheh.eventsHandled, jheh.eventsHandled == 4);
    //Create a new jheh because the last stop closed the eventWriter etc.
    jheh = new JHEventHandlerForSigtermTest(mockedContext, 0);
    // Make constructor of JobUnsuccessfulCompletionEvent pass
    Job job = Mockito.mock(Job.class);
    Mockito.when(mockedContext.getJob(jobId)).thenReturn(job);
    // Make TypeConverter(JobID) pass
    ApplicationId mockAppId = Mockito.mock(ApplicationId.class);
    Mockito.when(mockAppId.getClusterTimestamp()).thenReturn(1000l);
    Mockito.when(jobId.getAppId()).thenReturn(mockAppId);
    jheh.addToFileMap(jobId);
    jheh.setForcejobCompletion(true);
    for (int i = 0; i < numEvents; ++i) {
        events[i] = getEventToEnqueue(jobId);
        jheh.handle(events[i]);
    }
    jheh.stop();
    //Make sure events were handled, 4 + 1 finish event
    assertTrue("handleEvent should've been called only 5 times but was " + jheh.eventsHandled, jheh.eventsHandled == 5);
    assertTrue("Last event handled wasn't JobUnsuccessfulCompletionEvent", jheh.lastEventHandled.getHistoryEvent() instanceof JobUnsuccessfulCompletionEvent);
}
Also used : RunningAppContext(org.apache.hadoop.mapreduce.v2.app.MRAppMaster.RunningAppContext) AppContext(org.apache.hadoop.mapreduce.v2.app.AppContext) Job(org.apache.hadoop.mapreduce.v2.app.job.Job) ApplicationId(org.apache.hadoop.yarn.api.records.ApplicationId) JobId(org.apache.hadoop.mapreduce.v2.api.records.JobId) Test(org.junit.Test)

Example 77 with Job

use of org.apache.hadoop.mapreduce.v2.app.job.Job in project hadoop by apache.

the class TestRecovery method testRecoveryWithoutShuffleSecret.

@Test(timeout = 30000)
public void testRecoveryWithoutShuffleSecret() throws Exception {
    int runCount = 0;
    MRApp app = new MRAppNoShuffleSecret(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 task1Attempt = 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(task1Attempt, TaskAttemptState.RUNNING);
    app.waitForState(task2Attempt, TaskAttemptState.RUNNING);
    app.waitForState(reduceTask, TaskState.RUNNING);
    //send the done signal to the 1st map attempt
    app.getContext().getEventHandler().handle(new TaskAttemptEvent(task1Attempt.getID(), TaskAttemptEventType.TA_DONE));
    //wait for first map task to complete
    app.waitForState(mapTask1, TaskState.SUCCEEDED);
    //stop the app
    app.stop();
    //in recovery the 1st map should NOT be recovered from previous run
    //since the shuffle secret was not provided with the job credentials
    //and had to be rolled per app attempt
    app = new MRAppNoShuffleSecret(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();
    app.waitForState(mapTask1, TaskState.RUNNING);
    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);
    //verify first map task is still running
    app.waitForState(mapTask1, TaskState.RUNNING);
    //send the done signal to the 2nd map task
    app.getContext().getEventHandler().handle(new TaskAttemptEvent(mapTask1.getAttempts().values().iterator().next().getID(), TaskAttemptEventType.TA_DONE));
    //wait to get it completed
    app.waitForState(mapTask1, 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();
}
Also used : Task(org.apache.hadoop.mapreduce.v2.app.job.Task) Configuration(org.apache.hadoop.conf.Configuration) TaskAttemptEvent(org.apache.hadoop.mapreduce.v2.app.job.event.TaskAttemptEvent) TaskAttempt(org.apache.hadoop.mapreduce.v2.app.job.TaskAttempt) Job(org.apache.hadoop.mapreduce.v2.app.job.Job) Test(org.junit.Test)

Example 78 with Job

use of org.apache.hadoop.mapreduce.v2.app.job.Job 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();
}
Also used : Task(org.apache.hadoop.mapreduce.v2.app.job.Task) Configuration(org.apache.hadoop.conf.Configuration) TaskAttemptEvent(org.apache.hadoop.mapreduce.v2.app.job.event.TaskAttemptEvent) TaskAttempt(org.apache.hadoop.mapreduce.v2.app.job.TaskAttempt) Job(org.apache.hadoop.mapreduce.v2.app.job.Job) Test(org.junit.Test)

Example 79 with Job

use of org.apache.hadoop.mapreduce.v2.app.job.Job 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();
}
Also used : Task(org.apache.hadoop.mapreduce.v2.app.job.Task) Configuration(org.apache.hadoop.conf.Configuration) TaskAttemptEvent(org.apache.hadoop.mapreduce.v2.app.job.event.TaskAttemptEvent) TaskAttempt(org.apache.hadoop.mapreduce.v2.app.job.TaskAttempt) Job(org.apache.hadoop.mapreduce.v2.app.job.Job) Test(org.junit.Test)

Example 80 with Job

use of org.apache.hadoop.mapreduce.v2.app.job.Job 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();
}
Also used : Task(org.apache.hadoop.mapreduce.v2.app.job.Task) Configuration(org.apache.hadoop.conf.Configuration) TaskAttemptEvent(org.apache.hadoop.mapreduce.v2.app.job.event.TaskAttemptEvent) TaskAttempt(org.apache.hadoop.mapreduce.v2.app.job.TaskAttempt) Job(org.apache.hadoop.mapreduce.v2.app.job.Job) Test(org.junit.Test)

Aggregations

Job (org.apache.hadoop.mapreduce.v2.app.job.Job)291 Test (org.junit.Test)266 JobId (org.apache.hadoop.mapreduce.v2.api.records.JobId)221 Configuration (org.apache.hadoop.conf.Configuration)145 Task (org.apache.hadoop.mapreduce.v2.app.job.Task)141 ClientResponse (com.sun.jersey.api.client.ClientResponse)110 WebResource (com.sun.jersey.api.client.WebResource)110 JSONObject (org.codehaus.jettison.json.JSONObject)90 TaskAttempt (org.apache.hadoop.mapreduce.v2.app.job.TaskAttempt)80 TaskAttemptId (org.apache.hadoop.mapreduce.v2.api.records.TaskAttemptId)49 TaskId (org.apache.hadoop.mapreduce.v2.api.records.TaskId)49 YarnConfiguration (org.apache.hadoop.yarn.conf.YarnConfiguration)44 IOException (java.io.IOException)35 Path (org.apache.hadoop.fs.Path)31 JobEvent (org.apache.hadoop.mapreduce.v2.app.job.event.JobEvent)30 ApplicationAttemptId (org.apache.hadoop.yarn.api.records.ApplicationAttemptId)30 AppContext (org.apache.hadoop.mapreduce.v2.app.AppContext)28 TaskAttemptEvent (org.apache.hadoop.mapreduce.v2.app.job.event.TaskAttemptEvent)28 DrainDispatcher (org.apache.hadoop.yarn.event.DrainDispatcher)25 Path (javax.ws.rs.Path)23