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Why can't I run more than 1 query in parallel in Hive?

Expert Contributor

I have a small one node hdp2.6 cluster (8 CPUs, 32GB ram), and I cannot run more than 1 query at a time, although I was pretty sure that I configures the relevant settings to allow more than one container.

The relevant configs are:

yarn-site/yarn.nodemanager.resource.memory-mb = 27660
yarn-site/yarn.scheduler.minimum-allocation-mb = 5532
yarn-site/yarn.scheduler.maximum-allocation-mb = 27660
mapred-site/ = 5532
mapred-site/mapreduce.reduce.memory.mb = 11064
mapred-site/ = -Xmx4425m
mapred-site/ =  -Xmx8851m
mapred-site/ = 11059
mapred-site/ = -Xmx8851m -Dhdp.version=${hdp.version}

hive-site/hive.execution.engine = tez
hive-site/hive.tez.container.size = 5532
hive-site/ = 1546859315
tez-site/tez.runtime.unordered.output.buffer.size-mb = 414
tez-interactive-site/ = 5532
tez-site/ = 5532
tez-site/tez.task.resource.memory.mb = 5532
tez-site/ = 1351
hive-site/ = -server -Xmx4425m -XX:NewRatio=8 -XX:+UseNUMA -XX:+UseParallelGC -XX:+PrintGCDetails -verbose:gc -XX:+PrintGCTimeStamps

capacity-scheduler/yarn.scheduler.capacity.resource-calculator = org.apache.hadoop.yarn.util.resource.DominantResourceCalculatororg.apache.hadoop.yarn.util.resource.DominantResourceCalculator
yarn-site/yarn.nodemanager.resource.cpu-vcores = 6
yarn-site/yarn.scheduler.maximum-allocation-vcores = 6

mapred-site/ = true
hive-site/hive.exec.compress.intermediate = true
hive-site/hive.exec.compress.output = true

hive-interactive-env/enable_hive_interactive = false

Which if I understand it well, gives 5GB per container.

If I run a hive query, it will use 5GB, 1 core, leaving about 15GB and 5 cores for the rest. I do not understand why the next query cannot start at the same time.


Any help would be much welcome.


Accepted Solutions

Expert Contributor

In Mapreduce the Reducer output would wait after all ten Mapper is finished. We recommend to use Tez.

View solution in original post



@Guillaume Roger: The issue seems to be happening as the maximum application master limit has been set to 20%.

Maximum percent of resources in the cluster which can be used to run application masters - controls number of concurrent active applications. Limits on each queue are directly proportional to their queue capacities and user limits.

Since the limit here has been reached, I guess the application is not able to spawn another application master and hence the query is not running. Can we try increasing the parameter yarn.scheduler.capacity.maximum-am-resource-percent / yarn.scheduler.capacity.<queue-path>.maximum-am-resource-percent to 35% and see if it resolves the issue?

Expert Contributor

@Vani, Thanks for your answer.

I do not see an immediate change, but I carry on looking in this direction.

What would be a good logical value for this maximum-am-resource-percent?

Currently the AM memory (tez-site/ is set to the min container size (5GB in my case). Does that make sense?


@Guillaume Roger

If AM memory (tez-site/ is set to the min container size, only 1 application can be launched at any given point of time. Please tune the property depending on your requirement .

Expert Contributor

@Vani I am trying to understand what will this memory be used for. My understanding is that:

  • any application will require its own AM
  • one AM will use 1 container only
  • tez-site/ defines the memory usable by the total of all AM

So logically

  • all AM memory should never be more than half of the available memory (for the worst case scenario where all application only use one container)
  • I should allocate in tez-site/ (minimum container size * expected number of applications)

Could you confirm my understanding?


New Contributor

@Guillaume Roger, did you manage to sort your issue out. I am facing the same problem i.e unable to run 2 concurrent jobs although there is enought memory to spin new containers.

Any help will be highly appreciated..


Stuck here with the same issue  on HDP 3.0.1, still searching the correct parameters to set.


Platform is Comunity Edition on PowerPC

Expert Contributor

There are 2 things forground thread and background thread.


Foreground thread is used for parsing/complilation.The hive.server2.async.exec.threads determine how many concurrent threads can Hiveserver2 handle,it defaults to 500.


Background thread comes after compliation/parsing phase,where it runs Tez jobs. This depends on number of Tez AM .


In this case, you need to increase the Tez AM's.


So if you have one Hiveserver2,it will run 2 background threads. 


Please refer below document for more information:


just i have hive.server2.tez.sessions.per.default.queue=4 ...