Failed to load analyzer for name – How to solve this Elasticsearch exception

Opster Team

August-23, Version: 6.8-8.9

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 is unable to load the specified analyzer for a particular field. This could be due to a misconfiguration or the analyzer not being available in the Elasticsearch instance. To resolve this issue, you can check the Elasticsearch configuration to ensure the analyzer is correctly defined. If it’s a custom analyzer, ensure it’s properly installed. Alternatively, you can change the field mapping to use a different analyzer that is available in your Elasticsearch instance.

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 ” failed to load analyzer for name ” to appear. To understand the issues related to this log, read the explanation below about the following Elasticsearch concepts: index, analysis.

 
 

index

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
 
 

analysis

 
 

Log Context

Log “failed to load analyzer for name” class name is AnalysisRegistry.java. We extracted the following from Elasticsearch source code for those seeking an in-depth context :

 AnalysisModule.AnalysisProvider> provider = analyzers.get(analyzer);
 return provider == null ? null : cachedAnalyzer.computeIfAbsent(analyzer; (key) -> {
 try {
 return provider.get(environment; key).get();
 } catch (IOException ex) {
 throw new ElasticsearchException("failed to load analyzer for name " + key; ex);
 }
 });
 }
 return analyzerProvider.get(environment; analyzer).get();
 }

 

How helpful was this guide?

We are sorry that this post was not useful for you!

Let us improve this post!

Tell us how we can improve this post?

Get expert answers on Elasticsearch/OpenSearch

Try OpsGPT Now

Related Articles

Back to all articles