Apache Hadoop Yarn - Underutilization of cores

Question

No matter how much I tinker with the settings in yarn-site.xml i.e using all of the below options

yarn.scheduler.minimum-allocation-vcores
yarn.         


        

Answer 1

I had the similar kind of issue and from my code i was setting up the spark.executor.cores as 5. Even though it was just taking 1 which is the default core. In the spark UI and in environment tab i was seeing 5 cores. But while checking the executors tabs i was just able to see 1 process is in RUNNING state against an executor. I was using the spark version 1.6.3.

So then i have tried to hit the spark-submit command as --conf spark.executor.cores=5 which is working fine as using 5 cores

or just

--executor-cores 5 which also works.

Answer 2

The problem lies not with yarn-site.xml or spark-defaults.conf but actually with the resource calculator that assigns the cores to the executors or in the case of MapReduce jobs, to the Mappers/Reducers.

The default resource calculator i.e org.apache.hadoop.yarn.util.resource.DefaultResourceCalculator uses only memory information for allocating containers and CPU scheduling is not enabled by default. To use both memory as well as the CPU, the resource calculator needs to be changed to org.apache.hadoop.yarn.util.resource.DominantResourceCalculator in the capacity-scheduler.xml file.

Here's what needs to change.

<property>
    <name>yarn.scheduler.capacity.resource-calculator</name>
    <value>org.apache.hadoop.yarn.util.resource.DominantResourceCalculator</value>
</property>