Search code examples
springhadoophadoop-yarnspring-cloudspring-cloud-dataflow

Spring DataFlow Yarn - Container is running beyond physical memory

I'm running Spring Cloud Tasks on Yarn simple tasks work fine but running bigger tasks which require more resources I got "Container is running beyond physical memory" error:

onContainerCompleted:ContainerStatus: [ContainerId: 
container_1485796744143_0030_01_000002, State: COMPLETE, Diagnostics: Container [pid=27456,containerID=container_1485796744143_0030_01_000002] is running beyond physical memory limits. Current usage: 652.5 MB of 256 MB physical memory used; 5.6 GB of 1.3 GB virtual memory used. Killing container.
Dump of the process-tree for container_1485796744143_0030_01_000002 :
        |- PID PPID PGRPID SESSID CMD_NAME USER_MODE_TIME(MILLIS) SYSTEM_TIME(MILLIS) VMEM_USAGE(BYTES) RSSMEM_USAGE(PAGES) FULL_CMD_LINE
        |- 27461 27456 27456 27456 (java) 1215 126 5858455552 166335 /usr/lib/jvm/java-1.8.0/bin/java -Dserver.port=0 -Dspring.jmx.enabled=false -Dspring.config.location=servers.yml -jar cities-job-0.0.1.jar --spring.datasource.driverClassName=org.h2.Driver --spring.datasource.username=sa --spring.cloud.task.name=city2 --spring.datasource.url=jdbc:h2:tcp://localhost:19092/mem:dataflow 
        |- 27456 27454 27456 27456 (bash) 0 0 115806208 705 /bin/bash -c /usr/lib/jvm/java-1.8.0/bin/java  -Dserver.port=0 -Dspring.jmx.enabled=false -Dspring.config.location=servers.yml -jar cities-job-0.0.1.jar --spring.datasource.driverClassName='org.h2.Driver' --spring.datasource.username='sa' --spring.cloud.task.name='city2' --spring.datasource.url='jdbc:h2:tcp://localhost:19092/mem:dataflow' 1>/var/log/hadoop-yarn/containers/application_1485796744143_0030/container_1485796744143_0030_01_000002/Container.stdout 2>/var/log/hadoop-yarn/containers/application_1485796744143_0030/container_1485796744143_0030_01_000002/Container.stderr

I tried tuning options in DataFlow's server.yml settings:

spring:
 deployer:
   yarn:
     app:
       baseDir: /dataflow
       taskappmaster:
         memory: 512m
         virtualCores: 1
         javaOpts: "-Xms512m -Xmx512m"
       taskcontainer:
         priority: 1
         memory: 512m
         virtualCores: 1
         javaOpts: "-Xms256m -Xmx512m"

I found out that taskappmaster memory changes are visible (AM container in YARN is set to this value), but taskcontainer memory options isnt changing - every container for Cloud Task which is created has only 256 mb which is default option for YarnDeployer.

For this server.yml expected result is allocation of 2 containers with 512 both for Application Master and Application Container. But YARN allocates 2 containers 512 for application master and 256 mb for application.

I dont think this problem is connected with YARN wrong options because Spark Applications work correctly seizing GBs of memory.

Some of my YARN settings:

mapreduce.reduce.java.opts -Xmx2304m
mapreduce.reduce.memory.mb 2880
mapreduce.map.java.opts -Xmx3277m
mapreduce.map.memory.mb 4096
yarn.nodemanager.vmem-pmem-ratio 5
yarn.nodemanager.vmem-check-enabled false
yarn.scheduler.minimum-allocation-mb 32
yarn.nodemanager.resource.memory-mb 11520

My Hadoop runtime is EMR 4.4.0 also I had to change default java to 1.8.

Solution

  • Cleaning up /dataflow directory in HDFS resolves problem, after deleting this directory Spring DataFlow upload all needed files. The other way is to remove file by yourself and upload new one.