Before you begin reading this guide, we recommend you run the AutoOps for Elasticsearch. It will help you detect configuration issues prior to errors appearing that harm your system’s performance.
This guide will help you check for common problems that cause the log “No type specified for field ” + fieldName + “” to appear. It’s important to understand the issues related to the log, so to get started, read the general overview on common issues and tips related to the Elasticsearch concepts: index.
Background
Fields and mapping types in Elasticsearch do not need to be defined before being used if you are using dynamic mapping (in dynamic mapping, based on the field value, Elasticsearch determines the data-type). However, when you are creating a new index with an explicit mapping, you need to define what kind of data the field contains. You cannot just add the field name without mentioning the field data type in the index mapping. It is necessary to add the field data type if you are including the field name in the index mapping.
The below exception arises if you do not specify the field data type for the field name included in the index mapping. You will not be able to add index mapping in Elasticsearch.
How to reproduce this exception
To recreate this exception, create an index with this mapping:
Index Mapping
PUT /my-index
{
"mappings": {
"properties": {
"user": {
}
}
}
}
Response
{
"error": {
"root_cause": [
{
"type": "mapper_parsing_exception",
"reason": "No type specified for field [user]"
}
],
"type": "mapper_parsing_exception",
"reason": "Failed to parse mapping [_doc]: No type specified for field [user]",
"caused_by": {
"type": "mapper_parsing_exception",
"reason": "No type specified for field [user]"
}
},
"status": 400
}
How to fix this exception
Mapping defines the property of each field in the index. These properties may contain the data type of each field and how fields are going to be tokenized and indexed. Refer to this Elasticsearch official documentation on field data type for more information.
Here is an option for the modified index mapping (you can change the field data type according to your use case):
Modify the index mapping
PUT /my-index
{
"mappings": {
"properties": {
"user": {
"type":"text"
}
}
}
}
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 “No type specified for field [” + fieldName + “]”classname is ObjectMapper.java We extracted the following from Elasticsearch source code for those seeking an in-depth context :
// flag on it; make it an object
// (usually; setting enabled to false to not index
// any type; including core values; which
type = ObjectMapper.CONTENT_TYPE;
} else {
throw new MapperParsingException("No type specified for field [" + fieldName + "]");
}
}
Mapper.TypeParser typeParser = parserContext.typeParser(type);
if (typeParser == null) {
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