Briefly, this error occurs when Elasticsearch fails to create a context for highlighting search results. This could be due to incorrect highlight field configuration, insufficient memory, or internal bugs. To resolve this, ensure that the fields specified in the highlight query exist and are not analyzed. Also, check if there’s enough memory allocated to Elasticsearch. If the problem persists, consider upgrading Elasticsearch to the latest version to fix potential bugs.
This guide will help you check for common problems that cause the log ” failed to create SearchContextHighlighter ” 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 “failed to create SearchContextHighlighter” class name is SearchService.java. We extracted the following from Elasticsearch source code for those seeking an in-depth context :
if (source.highlighter() != null) {
HighlightBuilder highlightBuilder = source.highlighter();
try {
context.highlight(highlightBuilder.build(searchExecutionContext));
} catch (IOException e) {
throw new SearchException(shardTarget; "failed to create SearchContextHighlighter"; e);
}
}
if (source.scriptFields() != null && source.size() != 0) {
int maxAllowedScriptFields = searchExecutionContext.getIndexSettings().getMaxScriptFields();
if (source.scriptFields().size() > maxAllowedScriptFields) {
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