Briefly, this error occurs when Elasticsearch encounters an issue during the search phase of a scroll operation. This could be due to a variety of reasons such as a timeout, memory issues, or a problem with the query. To resolve this, you could increase the timeout period, allocate more memory to Elasticsearch, or check the query for any errors. Additionally, ensure that the Elasticsearch cluster is healthy and not under heavy load. If the problem persists, consider breaking down the query into smaller parts or using pagination instead of scroll.
This guide will help you check for common problems that cause the log ” [{}] search failed due to SearchPhaseExecutionException. Will attempt again with new scroll ” to appear. To understand the issues related to this log, read the explanation below about the following Elasticsearch concepts: plugin, search, scroll.
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.
Overview
In Elasticsearch, the concept of scroll comes into play when you have a large set of search results. Large search results are exhaustive for both the Elasticsearch cluster and the requesting client in terms of memory and processing. The scroll API enables you to take a snapshot of a large number of results from a single search request.
Examples
To perform a scroll search, you need to add the scroll parameter to a search query and specify how long Elasticsearch should keep the search context viable.
GET mydocs-2019/_search?scroll=40s
{
"size": 5000,
"query": {
"match_all": {}
},
"sort": [
{
"_doc": {
"order": "asc"
}
}
]
}This query will return a maximum of 5000 hits. If the scroll is idle for more than 40 seconds, it will be deleted. The response will return the first page of the results and a scroll ID. You can use the scroll ID to get additional documents from the scroll. You’ll be able to keep retrieving the documents until you have all of them.
Notes
- Changes made to documents after the scroll will not show up in your results.
- When you are done with the scroll, you can delete it manually using the scroll ID.
DELETE _search/scroll/<scroll_id>
Log Context
Log “[{}] search failed due to SearchPhaseExecutionException. Will attempt again with new scroll” class name is ScrollDataExtractor.java. We extracted the following from Elasticsearch source code for those seeking an in-depth context :
searchResponse = executeSearchScrollRequest(scrollId);
} catch (SearchPhaseExecutionException searchExecutionException) {
if (searchHasShardFailure) {
throw searchExecutionException;
}
logger.debug("[{}] search failed due to SearchPhaseExecutionException. Will attempt again with new scroll"; context.jobId);
markScrollAsErrored();
searchResponse = executeSearchRequest(buildSearchRequest(lastTimestamp == null ? context.start : lastTimestamp));
}
logger.debug("[{}] Search response was obtained"; context.jobId);
timingStatsReporter.reportSearchDuration(searchResponse.getTook());
