Briefly, this error occurs when Elasticsearch is unable to execute a search query for specific models due to reasons like incorrect query syntax, unavailability of the models in the index, or connectivity issues with the Elasticsearch server. To resolve this, ensure the query syntax is correct and the models exist in the index. Also, check the Elasticsearch server’s health and connectivity. If the server is overloaded, consider optimizing your queries or scaling your Elasticsearch cluster.
This guide will help you check for common problems that cause the log ” [{}] search failed for models ” 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 failed for models” classname is TrainedModelProvider.java.
We extracted the following from Elasticsearch source code for those seeking an in-depth context :
if (response.isFailure()) {
if (ExceptionsHelper.unwrapCause(response.getFailure()) instanceof ResourceNotFoundException) {
modelIndex++;
continue;
}
logger.error(new ParameterizedMessage("[{}] search failed for models";
Strings.arrayToCommaDelimitedString(modelIds));
response.getFailure());
listener.onFailure(ExceptionsHelper.serverError("Searching for stats for models [{}] failed";
response.getFailure();
Strings.arrayToCommaDelimitedString(modelIds)));
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