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Briefly, this error occurs when OpenSearch is unable to combine the results of the aggregations from different shards. This could be due to memory issues, complex queries, or a bug in the system. To resolve this, you can try simplifying your query, increasing the memory allocation for OpenSearch, or updating your OpenSearch version to the latest one to fix potential bugs. Additionally, consider optimizing your data model to reduce the complexity of the aggregations.
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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 OpenSearch concepts: aggregations, search.
Quick links
Overview
Search refers to the searching of documents in an index or multiple indices. The simple search is just a GET API request to the _search endpoint. The search query can either be provided in query string or through a request body.
Examples
When looking for any documents in this index, if search parameters are not provided, every document is a hit and by default 10 hits will be returned.
GET my_documents/_search
A JSON object is returned in response to a search query. A 200 response code means the request was completed successfully.
{
"took" : 1,
"timed_out" : false,
"_shards" : {
"total" : 2,
"successful" : 2,
"failed" : 0
},
"hits" : {
"total" : 2,
"max_score" : 1.0,
"hits" : [
...
]
}
}Notes and good things to know
- Distributed search is challenging and every shard of the index needs to be searched for hits, and then those hits are combined into a single sorted list as a final result.
- There are two phases of search: the query phase and the fetch phase.
- In the query phase, the query is executed on each shard locally and top hits are returned to the coordinating node. The coordinating node merges the results and creates a global sorted list.
- In the fetch phase, the coordinating node brings the actual documents for those hit IDs and returns them to the requesting client.
- A coordinating node needs enough memory and CPU in order to handle the fetch phase.
Log Context
Log “Merging/Reducing the aggregations failed when computing the aggregation [” class name is InternalMappedRareTerms.java. We extracted the following from OpenSearch 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<>());
