Briefly, this error occurs when Elasticsearch tries to add a query parser that returns null. This could be due to a faulty or missing query parser plugin. To resolve this issue, you can try the following: 1) Check if the required query parser plugin is installed and functioning correctly. 2) If the plugin is missing, install it. 3) If the plugin is faulty, try updating or reinstalling it. 4) Check your query syntax to ensure it’s correct.
This guide will help you check for common problems that cause the log ” failed to add query [{}] – parser returned null ” to appear. To understand the issues related to this log, read the explanation below about the following Elasticsearch concepts: delete-by-query, index, parser and percolator.
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
In Elasticsearch, an index (plural: indices) contains 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 the command below:
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
Log Context
Log “failed to add query [{}] – parser returned null” classname is QueriesLoaderCollector.java.
We extracted the following from Elasticsearch source code for those seeking an in-depth context :
// id is only used for logging; if we fail we log the id in the catch statement
final Query parseQuery = percolator.parsePercolatorDocument(null; fieldsVisitor.source());
if (parseQuery != null) {
queries.put(BytesRef.deepCopyOf(id); parseQuery);
} else {
logger.warn("failed to add query [{}] - parser returned null"; id);
}
} catch (Exception e) {
logger.warn("failed to add query [{}]"; e; id.utf8ToString());
}
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