Briefly, this error occurs when the rescore window size in Elasticsearch is set too high. The rescore window is the number of top documents that Elasticsearch will ‘rescore’ to get more accurate results. If the window size is too large, it can consume excessive memory and slow down the search performance. To resolve this issue, you can reduce the rescore window size to a more manageable number. Alternatively, you can increase the heap size of your Elasticsearch nodes, but this should be done cautiously to avoid out-of-memory errors.
This guide will help you check for common problems that cause the log ” Rescore window [” + rescoreContext.getWindowSize() + “] is too large. ” 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 “Rescore window [” + rescoreContext.getWindowSize() + “] is too large. ” class name is DefaultSearchContext.java. We extracted the following from Elasticsearch source code for those seeking an in-depth context :
throw new QueryPhaseExecutionException(this; "Cannot use [sort] option in conjunction with [rescore].");
}
int maxWindow = indexService.getIndexSettings().getMaxRescoreWindow();
for (RescoreContext rescoreContext: rescore) {
if (rescoreContext.getWindowSize() > maxWindow) {
throw new QueryPhaseExecutionException(this; "Rescore window [" + rescoreContext.getWindowSize() + "] is too large. "
+ "It must be less than [" + maxWindow + "]. This prevents allocating massive heaps for storing the results "
+ "to be rescored. This limit can be set by changing the [" + IndexSettings.MAX_RESCORE_WINDOW_SETTING.getKey()
+ "] index level setting."); }
