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OpenSearch is an open-source search and analytics suite derived from Elasticsearch. It is designed to provide a robust, scalable, and secure solution for searching, analyzing, and visualizing data in real-time. OpenSearch is commonly used for log analytics, full-text search, and operational intelligence.
In OpenSearch, a Frequent Garbage Collection alert indicates that the Java Virtual Machine (JVM) is spending a significant amount of time performing garbage collection. This can lead to increased latency and reduced throughput, affecting the overall performance of the OpenSearch cluster.
Garbage collection is a process by which the JVM reclaims memory by removing objects that are no longer in use. While necessary for memory management, excessive garbage collection can lead to performance bottlenecks.
Frequent garbage collection can cause increased CPU usage and slow down query processing. It may also lead to node instability if not addressed promptly.
Ensure that your heap usage is optimized. Monitor the heap size and usage patterns using tools like Elasticsearch's Monitoring API. Aim to keep heap usage below 75% to avoid frequent garbage collection.
If your heap usage is consistently high, consider increasing the heap size. This can be done by setting the OPENSEARCH_JAVA_OPTS
environment variable:
export OPENSEARCH_JAVA_OPTS="-Xms4g -Xmx4g"
Ensure that the heap size is set to 50% of the available RAM, but not more than 32GB.
Consider tuning the garbage collection settings to better suit your workload. You can adjust the garbage collector type and related parameters in the jvm.options
file. For example, switching to the G1 garbage collector can be beneficial for some workloads:
-XX:+UseG1GC
Refer to the Elasticsearch Advanced Configuration guide for more details.
By optimizing heap usage, adjusting heap size, and tuning garbage collection settings, you can mitigate the impact of frequent garbage collection on your OpenSearch cluster. Regular monitoring and adjustments based on workload changes are essential to maintaining optimal performance.
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