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 context type in the mapping of a context suggester. This could be due to a typo or unsupported context type. To resolve this issue, you should verify the context type in your mapping. Ensure it’s either ‘category’ or ‘geo’. If it’s a custom type, make sure it’s properly defined and supported. Also, check for any spelling or syntax errors in your mapping.
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 context type[” + type + “] ” 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 context type[” + type + “]” class name is ContextMappings.java. We extracted the following from Elasticsearch source code for those seeking an in-depth context :
break;
case GEO:
contextMapping = GeoContextMapping.load(name; contextConfig);
break;
default:
throw new ElasticsearchParseException("unknown context type[" + type + "]");
}
MappingParser.checkNoRemainingFields(name; contextConfig);
return contextMapping;
}
