Failed to derive type – How to solve this Elasticsearch exception

Opster Team

August-23, Version: 6.8-8.9

Briefly, this error occurs when Elasticsearch is unable to determine the data type of a field during indexing. This could be due to incorrect mapping or incompatible data types. To resolve this issue, you can explicitly define the mapping for the field in question, ensuring the data type matches the data you’re trying to index. Alternatively, you can modify the data to match the existing mapping. If the error persists, consider reindexing your data with the correct mapping.

This guide will help you check for common problems that cause the log ” Failed to derive type ” to appear. To understand the issues related to this log, read the explanation below about the following Elasticsearch concepts: index.

 
 

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
 
 

 
 

Log Context

Log “Failed to derive type” class name is MappingParser.java. We extracted the following from Elasticsearch source code for those seeking an in-depth context :

 type = rootName;
 mapping = (Map) mapping.get(rootName);
 }
 }
 if (type == null) {
 throw new MapperParsingException("Failed to derive type");
 }
 if (type.isEmpty()) {
 throw new MapperParsingException("type cannot be an empty string");
 }
 return parse(type; mapping);

 

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