Analyzer and search_analyzer on field – How to solve this Elasticsearch error

Average Read Time

3 Mins

Analyzer and search_analyzer on field – How to solve this Elasticsearch error

Opster Team

February-21, Version: 1.7-8.0

Before you begin reading this guide, we recommend you run the Elasticsearch Error Check-Up which can resolve issues that cause many errors.

This guide will help you understand why the log “analyzer and search_analyzer on field” appears. It’s important to understand the relevant basic information as well, so see the concept definition of index below.

Background

Analysis is the process that Elasticsearch performs on the body of a document before the document is sent off to be added to the inverted index. Elasticsearch goes through a number of steps for every analyzed field before the document is added to the index. These steps are:

  1. Character filtering
  2. Breaking text into tokens
  3. Token filtering

Analyzers are a clever mix of these three components added together. By default, queries will use the analyzer defined in the field mapping, but this can be overridden with the search_analyzer setting. search_analyzer is defined when you want to use a different analyzer at the search time. 

Note that this behaviour is different in ES 7.10 version. Elasticsearch no longer expects you to give both analyzer and search_analyzer when you use search_quote_analyzer in the mapping, hence this error is valid only in Elasticsearch versions below 7.10.

How to reproduce this exception

To recreate this exception, create an index with the following mapping:

PUT /my-index
{
  "settings":{
     "analysis":{
        "analyzer":{
           "my_analyzer":{
              "type":"custom",
              "tokenizer":"standard",
              "filter":[
                 "lowercase"
              ]
           },
           "my_stop_analyzer":{
              "type":"custom",
              "tokenizer":"standard",
              "filter":[
                 "lowercase",
                 "english_stop"
              ]
           }
        },
        "filter":{
           "english_stop":{
              "type":"stop",
              "stopwords":"_english_"
           }
        }
     }
  },
  "mappings":{
      "properties":{
         "title": {
            "type":"text",
            "search_quote_analyzer":"my_analyzer"
        }
     }
  }
}

The response will be:

{
 "error": {
   "root_cause": [
     {
       "type": "mapper_parsing_exception",
       "reason": "analyzer and search_analyzer on field [title] must be set when search_quote_analyzer is set"
     }
   ],
   "type": "mapper_parsing_exception",
   "reason": "Failed to parse mapping [_doc]: analyzer and search_analyzer on field [title] must be set when search_quote_analyzer is set",
   "caused_by": {
     "type": "mapper_parsing_exception",
     "reason": "analyzer and search_analyzer on field [title] must be set when search_quote_analyzer is set"
   }
 },
 "status": 400
}

How to fix this exception

The exception clearly states that you need to set both the analyzer and search analyzer, when search_quote_analyzer is set. The search_quote_analyzer setting points to the my_analyzer analyzer, as it allows you to specify an analyzer for phrases.

To fix this exception, modify the index mapping:

PUT /my-index
{
  "settings":{
     "analysis":{
        "analyzer":{
           "my_analyzer":{
              "type":"custom",
              "tokenizer":"standard",
              "filter":[
                 "lowercase"
              ]
           },
           "my_stop_analyzer":{
              "type":"custom",
              "tokenizer":"standard",
              "filter":[
                 "lowercase",
                 "english_stop"
              ]
           }
        },
        "filter":{
           "english_stop":{
              "type":"stop",
              "stopwords":"_english_"
           }
        }
     }
  },
  "mappings":{
      "properties":{
         "title": {
            "type":"text",
            "analyzer":"my_analyzer",
            "search_analyzer":"my_stop_analyzer",
            "search_quote_analyzer":"my_analyzer"
        }
     }
  }
}

Log Context

Log “analyzer and search_analyzer on field [“classname  is TypeParsers.java We extracted the following from Elasticsearch source code for those seeking an in-depth context :

if (indexAnalyzer == null && searchAnalyzer != null) {
 throw new MapperParsingException("analyzer on field [" + name + "] must be set when search_analyzer is set");
 } 
 if (searchAnalyzer == null && searchQuoteAnalyzer != null) {
 throw new MapperParsingException("analyzer and search_analyzer on field [" + name +
 "] must be set when search_quote_analyzer is set");
 } 
 if (searchAnalyzer == null) {
 searchAnalyzer = indexAnalyzer;

 

Watch a demo of the Check-Up:

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 “analyzer and search_analyzer on field [“classname  is TypeParsers.java We extracted the following from Elasticsearch source code for those seeking an in-depth context :

if (indexAnalyzer == null && searchAnalyzer != null) {
 throw new MapperParsingException("analyzer on field [" + name + "] must be set when search_analyzer is set");
 } 
 if (searchAnalyzer == null && searchQuoteAnalyzer != null) {
 throw new MapperParsingException("analyzer and search_analyzer on field [" + name +
 "] must be set when search_quote_analyzer is set");
 } 
 if (searchAnalyzer == null) {
 searchAnalyzer = indexAnalyzer;

 

Watch a demo of the Check-Up:

Analyze your cluster