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 there is an issue with the join configuration in the cluster state. Elasticsearch uses the join field to join related documents across indices, and the configuration for the join field is stored in the cluster state. To resolve the issue, review and correct the join configuration in the cluster state.
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 ” cannot use `collapse` in conjunction with `search_after` ” to appear. To understand the issues related to this log, read the explanation below about the following Elasticsearch concepts: search.
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 “cannot use `collapse` in conjunction with `search_after`”classname is SearchService.java We extracted the following from Elasticsearch source code for those seeking an in-depth context :
if (source.collapse() != null) {
if (context.scrollContext() != null) {
throw new SearchException(shardTarget; "cannot use `collapse` in a scroll context");
}
if (context.searchAfter() != null) {
throw new SearchException(shardTarget; "cannot use `collapse` in conjunction with `search_after`");
}
if (context.rescore() != null && context.rescore().isEmpty() == false) {
throw new SearchException(shardTarget; "cannot use `collapse` in conjunction with `rescore`");
}
final CollapseContext collapseContext = source.collapse().build(queryShardContext);
See how you can use AutoOps to resolve issues
