This log is related to search problems, in addition to reading the guide below you can use the free Search Log Analyzer. With Opster’s Analyzer, you can easily locate slow searches and understand what led to them adding additional load to your system. The tool is free and takes just 2 minutes to run.
Overview
Delete-by-query is an Elasticsearch API, which was introduced in version 5.0 and provides functionality to delete all documents that match the provided query. In lower versions, users had to install the Delete-By-Query plugin and use the DELETE /_query endpoint for this same use case.
What it is used for
This API is used for deleting all the documents from indices based on a query. Once the query is executed, Elasticsearch runs the process in the background to delete all the matching documents so you don’t have to wait for the process to be completed.
Examples
Delete all the documents of an index without deleting the mapping and settings:
POST /my_index/_delete_by_query?conflicts=proceed&pretty
{
"query": {
"match_all": {}
}
}The conflict parameter in the request is used to proceed with the request even in the case of version conflicts for some documents. The default conflict behavior is to abort the request altogether.
Notes
- A long-running delete_by_query can be terminated using _task API.
- Inside the query body, you can use the same syntax for queries that are available under the _search API.
Common problems
Elasticsearch takes a snapshot of the index when you hit delete by query request and uses the _version of the documents to process the request. If a document gets updated in the meantime, it will result in a version conflict error and the delete operation will fail.
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 “[{}] Failed to execute progress listener on query failure” classname is SearchProgressListener.java.
We extracted the following from Elasticsearch source code for those seeking an in-depth context :
final void notifyQueryFailure(int shardIndex; Exception exc) {
try {
onQueryFailure(shardIndex; exc);
} catch (Exception e) {
logger.warn(() -> new ParameterizedMessage("[{}] Failed to execute progress listener on query failure";
shards.get(shardIndex)); e);
}
}
final void notifyPartialReduce(List shards; TotalHits totalHits; InternalAggregations aggs; int version) {
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