If you've encountered the following error while working with Elasticsearch, you know it can be frustrating — and it's a clear sign that your cluster is hitting the heap memory limit:

elasticsearch.exceptions.TransportError: TransportError(429, 'circuit_breaking_exception', '[parent] Data too large, data for [<http_request>] would be [16118156956/15.6gb], which is larger than the limit of [16328705792/15.1gb], real usage: [16118156956/15.6gb], new bytes reserved: [440/440b], usages [request=0/0b, fielddata=41739122/39.8mb, in_flight_requests=440/440b]')

In this article, we’ll break down what causes this problem and what alternatives are recommended by Elasticsearch to fix it.

What Is a “circuit_breaking_exception”?

Elasticsearch uses a mechanism called the circuit breaker to prevent operations from consuming too much JVM heap memory and crashing the cluster. When a request exceeds the configured memory limit — typically 95% of the heap — it’s interrupted with a 429 error.

Error Breakdown

From the error message:

Estimated request memory: 15.6 GB
Parent circuit breaker limit: 15.1 GB
Actual usage at the time: 15.6 GB
Fielddata usage: ~39.8 MB

This means Elasticsearch tried to allocate memory beyond what the parent circuit breaker allowed.

How to Resolve It (Recommended by Elasticsearch)

1. Optimize Your Queries

Before tweaking memory settings, first review the query that triggered the error:

Avoid wildcards or heavy regular expressions.
Use filter instead of must in bool queries when scoring isn't needed.
Reduce aggregation result sizes using size limits.
Use _source: false to avoid retrieving full documents unless needed.

2. Avoid Unnecessary Fielddata Usage

If you're aggregating on text fields, Elasticsearch needs to load that data into fielddata, which uses heap memory.

Fix:

Prefer keyword fields for aggregations or sorting.
Or enable subfields explicitly in your mapping:

"mapping": {
  "name": {
    "type": "text",
    "fields": {
      "keyword": { "type": "keyword" }
    }
  }
}

3. Increase the Circuit Breaker Limit (Cautiously)

If you're confident your system can handle it, increase the parent circuit breaker limit:

PUT _cluster/settings
{
  "persistent": {
    "indices.breaker.total.limit": "95%"  // or 96–98% with caution
  }
}

Caution: Raising this too high can lead to OutOfMemoryError. Don’t go over 98% unless absolutely necessary.

4. Increase JVM Heap Size

If memory usage is consistently high, you may need to raise the heap size:

In your jvm.options file:

diffCopiarEditar-Xms16g
-Xmx16g

Best practices:

Set heap to 50% of available physical RAM.
Keep Xms and Xmx values equal to avoid dynamic heap resizing.

5. Partition Data More Effectively

Avoid massive single indices. Instead, use time-based indices such as:

logs-2025-07-01
logs-2025-07-02

This allows queries to operate on smaller slices of data, reducing memory consumption.

6. Monitor with the Right Tools

Use:

Kibana > Stack Monitoring
_nodes/stats/jvm
_nodes/stats/breaker

These APIs and dashboards help you understand heap usage and identify heavy operations.

Conclusion

The circuit_breaking_exception is a safety mechanism — not a bug. Solving it requires a careful balance between:

Efficient query design
Memory-conscious mapping choices
Proper memory and heap sizing

Before scaling up your resources, look for optimization opportunities in queries and data structure. A few adjustments can go a long way in preventing this error.

How to Fix Circuit Breaking Exception in ElasticSearch