Briefly, this error occurs when Elasticsearch cannot find the search context for a scroll request. The search context is essential for scroll operations as it maintains the state of a search for subsequent scroll requests. This could be due to the search context expiring or being cleared. To resolve this issue, you can increase the scroll timeout value to prevent the search context from expiring too quickly. Alternatively, ensure that the scroll ID used in the request is correct and hasn’t been cleared. Lastly, avoid making too many concurrent scroll requests to prevent overloading the system.
This guide will help you check for common problems that cause the log ” [{}] Search context missing; falling back to normal search. ” to appear. To understand the issues related to this log, read the explanation below about the following Elasticsearch concepts: search, plugin.
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 “[{}] Search context missing; falling back to normal search.” classname is ClientTransformIndexer.java.
We extracted the following from Elasticsearch source code for those seeking an in-depth context :
// check if the error has been caused by a missing search context; which could be a timed out pit
// re-try this search without pit; if it fails again the normal failure handler is called; if it
// succeeds a new pit gets created at the next run
Throwable unwrappedException = ExceptionsHelper.findSearchExceptionRootCause(e);
if (unwrappedException instanceof SearchContextMissingException) {
logger.warn(new ParameterizedMessage("[{}] Search context missing; falling back to normal search."; getJobId()); e);
pit = null;
searchRequest.source().pointInTimeBuilder(null);
ClientHelper.executeWithHeadersAsync(
transformConfig.getHeaders();
ClientHelper.TRANSFORM_ORIGIN;
