Elasticsearch Memory



Elasticsearch Memory

Opster Team

July 2020, Version: 1.7-8.0


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Memory in Elasticsearch

What is it

Memory is one of the most critical resources to monitor in Elasticsearch. Elasticsearch runs on JVM and uses heap memory areas for query cache, request cache, accessing lucene segments and storing fielddata for aggregations and sorting.

Commos problems and important points
  • The most common error that arises in Elasticsearch is OutOfMemory error. This error comes when the node is not able to cope up with the required heap size space. To avoid this, you need to closely monitor the heap utilization and garbage collector performance.
  • As per the most up-to-date best practices you should not allocate more than 50 percent of total RAM to JVM heap size. Starting from Elasticsearch version 5.x onward this can be set using -Xms and -Xmx parameters inside jvm.options configuration file. The defaults are set to 1 GB for both minimum and maximum heap size.
  • The heap size should not set more than 31 GB in any case to avoid the poor garbage collection.

Related log errors to this ES concept


Failed to refresh job memory requirements
Exception retrieving free physical memory
Exception retrieving total physical memory
GetFreePhysicalMemorySize is not available
GetTotalPhysicalMemorySize is not available
OS reported a negative free memory value
OS reported a negative total memory value
New used memory for data of would be larger than configured breaker: ; breaking
Unable to retrieve max size virtual memory
Couldnt schedule ML memory update node might be shutting down
Unable to lock JVM memory. Failed to set working set size. Error code
Falling back to allocating job by job counts because a memory requirement refresh could not be scheduled

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