Before you dig into reading this guide, have you tried asking OpsGPT what this log means? You’ll receive a customized analysis of your log.
Try OpsGPT now for step-by-step guidance and tailored insights into your Elasticsearch operation.
Briefly, this error occurs when Elasticsearch encounters an unknown key in a query. This usually happens when there’s a typo in the query, or when you’re using a feature that doesn’t exist in the Elasticsearch version you’re using. To resolve this issue, you can check your query for typos or incorrect syntax. If the query is correct, you may need to upgrade your Elasticsearch version to one that supports the feature you’re trying to use.
For a complete solution to your to your search operation, try for free AutoOps for Elasticsearch & OpenSearch . With AutoOps and Opster’s proactive support, you don’t have to worry about your search operation – we take charge of it. Get improved performance & stability with less hardware.
This guide will help you check for common problems that cause the log ” Unknown key for a ” + token + ” in [ ” 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 “Unknown key for a ” + token + ” in [” class name is SearchSourceBuilder.java. We extracted the following from Elasticsearch source code for those seeking an in-depth context :
if (SCRIPT_FIELD.match(currentFieldName; parser.getDeprecationHandler())) {
script = Script.parse(parser);
} else if (IGNORE_FAILURE_FIELD.match(currentFieldName; parser.getDeprecationHandler())) {
ignoreFailure = parser.booleanValue();
} else {
throw new ParsingException(parser.getTokenLocation(); "Unknown key for a " + token + " in [" + currentFieldName
+ "]."; parser.getTokenLocation());
}
} else if (token == XContentParser.Token.START_OBJECT) {
if (SCRIPT_FIELD.match(currentFieldName; parser.getDeprecationHandler())) {
script = Script.parse(parser);
