"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 " +
"supported max container capability in the cluster. Killing the " +
"Job. reduceResourceReqt: " + reduceResourceReqt +
" 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(reduceResourceReqt);
if (reqEvent.getEarlierAttemptFailed()) {