Package org.apache.hadoop.mapreduce.jobhistory

Examples of org.apache.hadoop.mapreduce.jobhistory.NormalizedResourceEvent

578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
        Container container = Container.newInstance(cId, nodeId,
            NM_HOST + ":" + NM_HTTP_PORT, resource, null, containerToken);
        JobID id = TypeConverter.fromYarn(applicationId);
        JobId jobId = TypeConverter.toYarn(id);
        getContext().getEventHandler().handle(new JobHistoryEvent(jobId,
            new NormalizedResourceEvent(
                org.apache.hadoop.mapreduce.TaskType.REDUCE,
            100)));
        getContext().getEventHandler().handle(new JobHistoryEvent(jobId,
            new NormalizedResourceEvent(
                org.apache.hadoop.mapreduce.TaskType.MAP,
            100)));
        getContext().getEventHandler().handle(
            new TaskAttemptContainerAssignedEvent(event.getAttemptID(),
                container, null));
View Full Code Here
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
        Container container = Container.newInstance(cId, nodeId,
            NM_HOST + ":" + NM_HTTP_PORT, resource, null, containerToken);
        JobID id = TypeConverter.fromYarn(applicationId);
        JobId jobId = TypeConverter.toYarn(id);
        getContext().getEventHandler().handle(new JobHistoryEvent(jobId,
            new NormalizedResourceEvent(
                org.apache.hadoop.mapreduce.TaskType.REDUCE,
            100)));
        getContext().getEventHandler().handle(new JobHistoryEvent(jobId,
            new NormalizedResourceEvent(
                org.apache.hadoop.mapreduce.TaskType.MAP,
            100)));
        getContext().getEventHandler().handle(
            new TaskAttemptContainerAssignedEvent(event.getAttemptID(),
                container, null));
View Full Code Here
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
          getMaxContainerCapability().getMemory();
      if (reqEvent.getAttemptID().getTaskId().getTaskType().equals(TaskType.MAP)) {
        if (mapResourceRequest == 0) {
          mapResourceRequest = reqEvent.getCapability().getMemory();
          eventHandler.handle(new JobHistoryEvent(jobId,
              new NormalizedResourceEvent(org.apache.hadoop.mapreduce.TaskType.MAP,
                  mapResourceRequest)));
          LOG.info("mapResourceRequest:"+ mapResourceRequest);
          if (mapResourceRequest > supportedMaxContainerCapability) {
            String diagMsg = "MAP capability required is more than the supported " +
            "max container capability in the cluster. Killing the Job. mapResourceRequest: " +
                mapResourceRequest + " maxContainerCapability:" + supportedMaxContainerCapability;
            LOG.info(diagMsg);
            eventHandler.handle(new JobDiagnosticsUpdateEvent(
                jobId, diagMsg));
            eventHandler.handle(new JobEvent(jobId, JobEventType.JOB_KILL));
          }
        }
        //set the rounded off memory
        reqEvent.getCapability().setMemory(mapResourceRequest);
        scheduledRequests.addMap(reqEvent);//maps are immediately scheduled
      } else {
        if (reduceResourceRequest == 0) {
          reduceResourceRequest = reqEvent.getCapability().getMemory();
          eventHandler.handle(new JobHistoryEvent(jobId,
              new NormalizedResourceEvent(
                  org.apache.hadoop.mapreduce.TaskType.REDUCE,
                  reduceResourceRequest)));
          LOG.info("reduceResourceRequest:"+ reduceResourceRequest);
          if (reduceResourceRequest > supportedMaxContainerCapability) {
            String diagMsg = "REDUCE capability required is more than the " +
View Full Code Here
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
          mapResourceReqt = reqEvent.getCapability().getMemory();
          int minSlotMemSize = getMinContainerCapability().getMemory();
          mapResourceReqt = (int) Math.ceil((float) mapResourceReqt/minSlotMemSize)
              * minSlotMemSize;
          eventHandler.handle(new JobHistoryEvent(jobId,
              new NormalizedResourceEvent(org.apache.hadoop.mapreduce.TaskType.MAP,
              mapResourceReqt)));
          LOG.info("mapResourceReqt:"+mapResourceReqt);
          if (mapResourceReqt > supportedMaxContainerCapability) {
            String diagMsg = "MAP capability required is more than the supported " +
            "max container capability in the cluster. Killing the Job. mapResourceReqt: " +
            mapResourceReqt + " maxContainerCapability:" + supportedMaxContainerCapability;
            LOG.info(diagMsg);
            eventHandler.handle(new JobDiagnosticsUpdateEvent(
                jobId, diagMsg));
            eventHandler.handle(new JobEvent(jobId, JobEventType.JOB_KILL));
          }
        }
        //set the rounded off memory
        reqEvent.getCapability().setMemory(mapResourceReqt);
        scheduledRequests.addMap(reqEvent);//maps are immediately scheduled
      } else {
        if (reduceResourceReqt == 0) {
          reduceResourceReqt = reqEvent.getCapability().getMemory();
          int minSlotMemSize = getMinContainerCapability().getMemory();
          //round off on slotsize
          reduceResourceReqt = (int) Math.ceil((float)
              reduceResourceReqt/minSlotMemSize) * minSlotMemSize;
          eventHandler.handle(new JobHistoryEvent(jobId,
              new NormalizedResourceEvent(
                  org.apache.hadoop.mapreduce.TaskType.REDUCE,
              reduceResourceReqt)));
          LOG.info("reduceResourceReqt:"+reduceResourceReqt);
          if (reduceResourceReqt > supportedMaxContainerCapability) {
            String diagMsg = "REDUCE capability required is more than the " +
View Full Code Here
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
        Container container = BuilderUtils.newContainer(cId, nodeId,
            NM_HOST + ":" + NM_HTTP_PORT, null, null, null);
        JobID id = TypeConverter.fromYarn(applicationId);
        JobId jobId = TypeConverter.toYarn(id);
        getContext().getEventHandler().handle(new JobHistoryEvent(jobId,
            new NormalizedResourceEvent(
                org.apache.hadoop.mapreduce.TaskType.REDUCE,
            100)));
        getContext().getEventHandler().handle(new JobHistoryEvent(jobId,
            new NormalizedResourceEvent(
                org.apache.hadoop.mapreduce.TaskType.MAP,
            100)));
        getContext().getEventHandler().handle(
            new TaskAttemptContainerAssignedEvent(event.getAttemptID(),
                container, null));
View Full Code Here
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
        Container container = BuilderUtils.newContainer(cId, nodeId,
            NM_HOST + ":" + NM_HTTP_PORT, null, null, null);
        JobID id = TypeConverter.fromYarn(applicationId);
        JobId jobId = TypeConverter.toYarn(id);
        getContext().getEventHandler().handle(new JobHistoryEvent(jobId,
            new NormalizedResourceEvent(
                org.apache.hadoop.mapreduce.TaskType.REDUCE,
            100)));
        getContext().getEventHandler().handle(new JobHistoryEvent(jobId,
            new NormalizedResourceEvent(
                org.apache.hadoop.mapreduce.TaskType.MAP,
            100)));
        getContext().getEventHandler().handle(
            new TaskAttemptContainerAssignedEvent(event.getAttemptID(),
                container, null));
View Full Code Here
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
        Container container = BuilderUtils.newContainer(cId, nodeId,
            NM_HOST + ":" + NM_HTTP_PORT, null, null, null);
        JobID id = TypeConverter.fromYarn(applicationId);
        JobId jobId = TypeConverter.toYarn(id);
        getContext().getEventHandler().handle(new JobHistoryEvent(jobId,
            new NormalizedResourceEvent(
                org.apache.hadoop.mapreduce.TaskType.REDUCE,
            100)));
        getContext().getEventHandler().handle(new JobHistoryEvent(jobId,
            new NormalizedResourceEvent(
                org.apache.hadoop.mapreduce.TaskType.MAP,
            100)));
        getContext().getEventHandler().handle(
            new TaskAttemptContainerAssignedEvent(event.getAttemptID(),
                container, null));
View Full Code Here
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
          mapResourceReqt = reqEvent.getCapability().getMemory();
          int minSlotMemSize = getMinContainerCapability().getMemory();
          mapResourceReqt = (int) Math.ceil((float) mapResourceReqt/minSlotMemSize)
              * minSlotMemSize;
          eventHandler.handle(new JobHistoryEvent(jobId,
              new NormalizedResourceEvent(org.apache.hadoop.mapreduce.TaskType.MAP,
              mapResourceReqt)));
          LOG.info("mapResourceReqt:"+mapResourceReqt);
          if (mapResourceReqt > supportedMaxContainerCapability) {
            String diagMsg = "MAP capability required is more than the supported " +
            "max container capability in the cluster. Killing the Job. mapResourceReqt: " +
            mapResourceReqt + " maxContainerCapability:" + supportedMaxContainerCapability;
            LOG.info(diagMsg);
            eventHandler.handle(new JobDiagnosticsUpdateEvent(
                jobId, diagMsg));
            eventHandler.handle(new JobEvent(jobId, JobEventType.JOB_KILL));
          }
        }
        //set the rounded off memory
        reqEvent.getCapability().setMemory(mapResourceReqt);
        scheduledRequests.addMap(reqEvent);//maps are immediately scheduled
      } else {
        if (reduceResourceReqt == 0) {
          reduceResourceReqt = reqEvent.getCapability().getMemory();
          int minSlotMemSize = getMinContainerCapability().getMemory();
          //round off on slotsize
          reduceResourceReqt = (int) Math.ceil((float)
              reduceResourceReqt/minSlotMemSize) * minSlotMemSize;
          eventHandler.handle(new JobHistoryEvent(jobId,
              new NormalizedResourceEvent(
                  org.apache.hadoop.mapreduce.TaskType.REDUCE,
              reduceResourceReqt)));
          LOG.info("reduceResourceReqt:"+reduceResourceReqt);
          if (reduceResourceReqt > supportedMaxContainerCapability) {
            String diagMsg = "REDUCE capability required is more than the " +
View Full Code Here
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
          getMaxContainerCapability().getMemory();
      if (reqEvent.getAttemptID().getTaskId().getTaskType().equals(TaskType.MAP)) {
        if (mapResourceReqt == 0) {
          mapResourceReqt = reqEvent.getCapability().getMemory();
          eventHandler.handle(new JobHistoryEvent(jobId,
              new NormalizedResourceEvent(org.apache.hadoop.mapreduce.TaskType.MAP,
              mapResourceReqt)));
          LOG.info("mapResourceReqt:"+mapResourceReqt);
          if (mapResourceReqt > supportedMaxContainerCapability) {
            String diagMsg = "MAP capability required is more than the supported " +
            "max container capability in the cluster. Killing the Job. mapResourceReqt: " +
            mapResourceReqt + " maxContainerCapability:" + supportedMaxContainerCapability;
            LOG.info(diagMsg);
            eventHandler.handle(new JobDiagnosticsUpdateEvent(
                jobId, diagMsg));
            eventHandler.handle(new JobEvent(jobId, JobEventType.JOB_KILL));
          }
        }
        //set the rounded off memory
        reqEvent.getCapability().setMemory(mapResourceReqt);
        scheduledRequests.addMap(reqEvent);//maps are immediately scheduled
      } else {
        if (reduceResourceReqt == 0) {
          reduceResourceReqt = reqEvent.getCapability().getMemory();
          eventHandler.handle(new JobHistoryEvent(jobId,
              new NormalizedResourceEvent(
                  org.apache.hadoop.mapreduce.TaskType.REDUCE,
              reduceResourceReqt)));
          LOG.info("reduceResourceReqt:"+reduceResourceReqt);
          if (reduceResourceReqt > supportedMaxContainerCapability) {
            String diagMsg = "REDUCE capability required is more than the " +
View Full Code Here
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
        Container container = Container.newInstance(cId, nodeId,
            NM_HOST + ":" + NM_HTTP_PORT, resource, null, containerToken);
        JobID id = TypeConverter.fromYarn(applicationId);
        JobId jobId = TypeConverter.toYarn(id);
        getContext().getEventHandler().handle(new JobHistoryEvent(jobId,
            new NormalizedResourceEvent(
                org.apache.hadoop.mapreduce.TaskType.REDUCE,
            100)));
        getContext().getEventHandler().handle(new JobHistoryEvent(jobId,
            new NormalizedResourceEvent(
                org.apache.hadoop.mapreduce.TaskType.MAP,
            100)));
        getContext().getEventHandler().handle(
            new TaskAttemptContainerAssignedEvent(event.getAttemptID(),
                container, null));
View Full Code Here
TOP

Related Classes of org.apache.hadoop.mapreduce.jobhistory.NormalizedResourceEvent

  • org.apache.hadoop.mapreduce.v2.app.MRApp
  • org.apache.hadoop.mapreduce.v2.app.MRApp$MRAppContainerAllocator
  • org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator
    • Copyright © 2018 www.massapicom. All rights reserved.
    All source code are property of their respective owners. Java is a trademark of Sun Microsystems, Inc and owned by ORACLE Inc. Contact coftware#gmail.com.