How To Solve Issues Related to Log – OnNewScrollContext listener failed

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Troubleshooting background

To troubleshoot Elasticsearch log “OnNewScrollContext listener failed” it’s important to know common problems related to Elasticsearch concepts: index, scroll, search, shard. See below-detailed explanations complete with common problems, examples and useful tips.

Index in Elasticsearch

What it is

In Elasticsearch, an index (indices in plural) can be thought of as a table inside a database that has a schema and can have one or more shards and replicas. An Elasticsearch index is divided into shards and each shard is an instance of a Lucene index.

Indices are used to store the documents in dedicated data structures corresponding to the data type of fields. For example, text fields are stored inside an inverted index whereas numeric and geo fields are stored inside BKD trees.

Examples
Create Index

The following example is based on Elasticsearch version 5.x onwards. An index with two shards, each having one replica will be created with the name test_index1

PUT /test_index1?pretty
{
    "settings" : {
        "number_of_shards" : 2,
        "number_of_replicas" : 1
    },
    "mappings" : {
        "properties" : {
            "tags" : { "type" : "keyword" },
            "updated_at" : { "type" : "date" }
        }
    }
}
List Indices

All the index names and their basic information can be retrieved using the following command:

GET _cat/indices?v
Index a document

Let’s add a document in the index with below command:

PUT test_index1/_doc/1
{
  "tags": [
    "opster",
    "elasticsearch"
  ],
  "date": "01-01-2020"
}
Query an index
GET test_index1/_search
{
  "query": {
    "match_all": {}
  }
}
Query Multiple Indices

It is possible to search multiple indices with a single request. If it is a raw HTTP request, Index names should be sent in comma-separated format, as shown in the example below, and in the case of a query via a programming language client such as python or Java, index names are to be sent in a list format.

GET test_index1,test_index2/_search
Delete Indices
DELETE test_index1
Common Problems
  • It is good practice to define the settings and mapping of an Index wherever possible because if this is not done, Elasticsearch tries to automatically guess the data type of fields at the time of indexing. This automatic process may have disadvantages, such as mapping conflicts, duplicate data and incorrect data types being set in the index. If the fields are not known in advance, it’s better to use dynamic index templates.
  • Elasticsearch supports wildcard patterns in Index names, which sometimes aids with querying multiple indices, but can also be very destructive too. For example, It is possible to delete all the indices in a single command using the following commands:
DELETE /*

To disable this, you can add the following lines in the elasticsearch.yml:

action.destructive_requires_name: true

Scroll in Elasticsearch

What it is

In Elasticsearch, the concept of scroll comes into play when you have a large set of search results. Large search results are exhaustive for both the Elasticsearch cluster and the requesting client in terms of memory and processing. The scroll API enables you  to take a snapshot of a large number of results from a single search request.

Examples

To perform a scroll search, you need to add the scroll parameter to search query and specify how long Elasticsearch should keep the search context viable.

GET mydocs-2019/_search?scroll=40s
{
"size": 5000,
"query": {
"match_all": {}
},
"sort": [
 {
 "_doc": {
  "order": "asc"
   }
  }
 ]
}

This query will return a maximum of  5000 hits and if the scroll is idle for more than 40  seconds, then it will be deleted. The response will return the first page of the results and a scroll id, you can use the scroll id to get additional documents from the scroll. You’re able to keep retrieving the documents until you have all of them.

Notes
  • Changes made to documents after the scroll will not show up in your results.
  • When you are done with the scroll, you can delete it manually using the scroll id.
DELETE _search/scroll/<sroll_id>

Search in Elasticsearch

What it is

Search refers to the searching of documents in an index or multiple indices. The simple search is just a GET request to _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 will mean the request completed successfully.

{
"took" : 1,
"timed_out" : false,
"_shards" : {
"total" : 2,
"successful" : 2,
"failed" : 0
},
"hits" : {
"total" : 2,
"max_score" : 1.0,
"hits" : [
...
]
}
}
Notes
  • 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.


To help troubleshoot related issues we have gathered selected Q&A from the community and issues from Github , please review the following for further information :

Github Issue Number 42661
github.com/elastic/elasticsearch/issues/42661

 

Github Issue Number 25244
github.com/elastic/elasticsearch/issues/25244

 


Log Context

Log ”OnNewScrollContext listener failed” classname is SearchOperationListener.java
We have extracted the following from Elasticsearch source code to get an in-depth context :

         public void onNewScrollContext(SearchContext context) {
            for (SearchOperationListener listener : listeners) {
                try {
                    listener.onNewScrollContext(context);
                } catch (Exception e) {
                    logger.warn(() -> new ParameterizedMessage("onNewScrollContext listener [{}] failed"; listener); e);
                }
            }
        }

        
Override





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