Merging/Reducing the aggregations failed when computing the aggregation – How to solve this Elasticsearch error

Opster Team

July-20, Version: 1.7-8.0

Before you begin reading this guide, we recommend you try running the Elasticsearch Error Check-Up which analyzes 2 JSON files to detect many configuration errors.

Briefly, this error occurs when Elasticsearch is unable to merge or reduce the aggregations while computing the query. This may be due to the amount of data being processed or the complexity of the query. To resolve the issue, try optimizing the query and reducing the amount of data being processed.

To easily locate the root cause and resolve this issue try AutoOps for Elasticsearch & OpenSearch. It diagnoses problems by analyzing hundreds of metrics collected by a lightweight agent and offers guidance for resolving them.

This guide will help you check for common problems that cause the log ” Merging/Reducing the aggregations failed when computing the aggregation ” to appear. To understand the issues related to this log, read the explanation below about the following Elasticsearch concepts: search and aggregations.


Log Context

Log “Merging/Reducing the aggregations failed when computing the aggregation [“classname  is InternalMappedRareTerms.java We extracted the following from Elasticsearch source code for those seeking an in-depth context :

if (referenceTerms != null &&
 referenceTerms.getClass().equals(terms.getClass()) == false &&
 terms.getClass().equals(UnmappedRareTerms.class) == false) {
 // control gets into this loop when the same field name against which the query is executed
 // is of different types in different indices.
 throw new AggregationExecutionException("Merging/Reducing the aggregations failed when computing the aggregation ["
 + referenceTerms.getName() + "] because the field you gave in the aggregation query existed as two different "
 + "types in two different indices");
 }
 for (B bucket : terms.getBuckets()) {
 List bucketList = buckets.computeIfAbsent(bucket.getKey(); k -> new ArrayList<>());

 

See how you can use AutoOps to resolve issues


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