Elasticsearch CircuitBreakingException: Data exceeded memory limits - Common Causes & Fixes

The CircuitBreakingException with the message "Data exceeded memory limits" occurs in Elasticsearch when the amount of data being processed exceeds the configured memory limits. This error is triggered by Elasticsearch's circuit breaker mechanism, which is designed to prevent out-of-memory errors and maintain cluster stability.

Impact

This error can significantly impact the performance and stability of your Elasticsearch cluster:

• Queries or indexing operations may fail
• Data ingestion could be interrupted
• Search results may be incomplete or unavailable
• Overall cluster performance may degrade

Common Causes

1. Insufficient JVM heap size allocation
2. Large field data cache usage
3. Complex aggregations or queries on high-cardinality fields
4. Poorly optimized mapping causing excessive memory usage
5. Bulk indexing operations with large payloads

Troubleshooting and Resolution Steps

1. Check current memory usage and circuit breaker settings:

   GET /_nodes/stats/breaker
   

2. Increase JVM heap size if possible:

   • Edit jvm.options file
   • Set -Xms and -Xmx to higher values (e.g., -Xms4g -Xmx4g)

3. Adjust circuit breaker settings:

   PUT /_cluster/settings
   {
     "persistent": {
       "indices.breaker.total.limit": "70%",
       "indices.breaker.request.limit": "60%",
       "indices.breaker.fielddata.limit": "40%"
     }
   }
   

4. Optimize queries and aggregations:

   • Use filters instead of queries where possible
   • Limit the size of aggregations
   • Consider using composite aggregations for high-cardinality fields

5. Review and optimize index mappings:

   • Disable fielddata for text fields not requiring aggregations
   • Use appropriate data types (e.g., keyword instead of text for non-analyzed fields)

6. Implement pagination for large result sets

7. Monitor and manage field data cache:

   GET /_stats/fielddata?fields=*
   

8. Consider scaling your cluster horizontally by adding more nodes

Best Practices

• Regularly monitor cluster health and resource usage
• Implement proper capacity planning and scaling strategies
• Use the Elasticsearch Monitoring (or ELK stack) to track cluster metrics
• Optimize your data model and queries for better performance
• Implement circuit breaker monitoring and alerting in your operations workflow

Frequently Asked Questions

Q: Can increasing the JVM heap size solve all CircuitBreakingExceptions?
A: While increasing JVM heap size can help, it's not always the best solution. It's important to identify the root cause and optimize queries, mappings, and data structures. Excessive heap sizes can lead to long garbage collection pauses.

Q: How do I determine which circuit breaker is triggering the exception?
A: Check the Elasticsearch logs for detailed error messages. You can also use the GET /_nodes/stats/breaker API to view the current state of all circuit breakers and identify which one is close to or exceeding its limit.

Q: Are there any risks in increasing circuit breaker limits?
A: Yes, increasing limits without addressing underlying issues can lead to node instability or out-of-memory errors. It's crucial to balance between allowing necessary operations and protecting cluster stability.

Q: How can I prevent CircuitBreakingExceptions during bulk indexing?
A: Optimize your bulk requests by reducing payload size, increasing the number of shards for better distribution, and monitoring your cluster's capacity. Consider using the ?wait_for_active_shards parameter to ensure proper shard allocation before sending large bulk requests.

Q: Does the CircuitBreakingException affect all nodes in the cluster?
A: The exception typically occurs on a specific node where the memory limit is exceeded. However, it can indirectly affect the entire cluster by causing failed operations and increased load on other nodes. Proper load balancing and shard allocation are important to mitigate cluster-wide impacts.