Briefly, this error occurs when Elasticsearch’s Garbage Collection (GC) process is unable to free up enough memory even after several attempts. This could be due to high memory usage or insufficient memory allocation. To resolve this issue, you can: 1) Increase the heap size allocated to Elasticsearch, ensuring it’s no more than 50% of your total physical RAM. 2) Optimize your queries and indices to reduce memory usage. 3) Regularly monitor and manage your cluster’s health to prevent memory leaks. 4) Consider upgrading your hardware if memory issues persist.
This guide will help you check for common problems that cause the log ” GC did not bring memory usage down; before [{}]; after [{}]; allocations [{}]; duration [{}] ” to appear. To understand the issues related to this log, read the explanation below about the following Elasticsearch concepts: memory, indices, breaker.
Overview
Elasticsearch has the concept of circuit breakers to deal with OutOfMemory errors that cause nodes to crash. When a request reaches Elasticsearch nodes, the circuit breakers first estimate the amount of memory needed to load the required data. They then compare the estimated size with the configured heap size limit. If the estimated size is greater than the heap size, the query is terminated and an exception is thrown to avoid the node loading more than the available heap size.
What they are used for
Elasticsearch has several circuit breakers available such as fielddata, requests, network, indices and script compilation. Each breaker is used to limit the memory an operation can use. In addition, Elasticsearch has a parent circuit breaker which is used to limit the combined memory used by all the other circuit breakers.
Examples
Increasing circuit breaker size for fielddata limit – The default limit for fielddata breakers is 40%. The following command can be used to increase it to 60%:
PUT /_cluster/settings
{
"persistent": {
"indices.breaker.fielddata.limit": "60%"
}
}Notes
- Each breaker ships with default limits and their limits can be modified as well. But this is an expert level setting and you should understand the pitfalls carefully before changing the limits, otherwise the node may start throwing OOM exceptions.
- Sometimes it is better to fail a query instead of getting an OOM exception, because when OOM appears JVM becomes unresponsive.
- It is important to keep indices.breaker.request.limit lower than indices.breaker.total.limit so that request circuit breakers trip before the total circuit breaker.
Common problems
- The most common error resulting from circuit breakers is “data too large” with 429 status code. The application should be ready to handle such exceptions.
- If the application starts throwing exceptions because of circuit breaker limits, it is important to review the queries and memory requirements. In most cases, a scaling is required by adding more resources to the cluster.
Log Context
Log “GC did not bring memory usage down; before [{}]; after [{}]; allocations [{}]; duration [{}]” classname is HierarchyCircuitBreakerService.java.
We extracted the following from Elasticsearch source code for those seeking an in-depth context :
}
return new MemoryUsage(current; memoryUsed.totalUsage - memoryUsed.baseUsage + current;
memoryUsed.transientChildUsage; memoryUsed.permanentChildUsage);
} else {
if (leader) {
logger.info("GC did not bring memory usage down; before [{}]; after [{}]; allocations [{}]; duration [{}]";
memoryUsed.baseUsage; current; allocationIndex; allocationDuration);
}
// prefer original measurement when reporting if heap usage was not brought down.
return memoryUsed;
}
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