Opster Team
To understand why this error arises when an index doesn’t have a defined key in the request body, you should run the AutoOps for Elasticsearch . It will help you resolve the issue and prevent it from occuring in the future.
This guide will help you check for common problems that cause the log “unknown key for create index” 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: admin, indices and index.
Background
Each index created can have specific settings, mapping definitions and index aliases. The above error arises when the request body of the create index API is not correctly formed.
Refer to this guide to learn more about various parameters and settings included under each section of the request body. For example – If the index setting (like analysis) is not defined under the request body’s settings section, then the below error will arise.
How to reproduce this exception
Create an index, with the below settings and mappings.
Index mapping:
PUT /my-index { "settings": { "number_of_shards": 2, "number_of_replicas": 1 }, "analysis": { "analyzer": { "my_analyzer": { "type": "custom", "tokenizer": "standard", "filter": [ "lowercase" ] } } }, "mappings": { "properties": { "question": { "type": "text", "analyzer": "my_analyzer" } } } }
The response will be:
{ "error": { "root_cause": [ { "type": "parse_exception", "reason": "unknown key [analysis] for create index" } ], "type": "parse_exception", "reason": "unknown key [analysis] for create index" }, "status": 400 }
How to fix this exception
The analysis section needs to be located inside the top-level settings section.
Modify the index mapping:
PUT /my-index { "settings": { "number_of_shards": 2, "number_of_replicas": 1, "analysis": { // note this "analyzer": { "my_analyzer": { "type": "custom", "tokenizer": "standard", "filter": [ "lowercase" ] } } } }, "mappings": { "properties": { "question": { "type": "text", "analyzer": "my_analyzer" } } } }


Index and indexing in Elasticsearch - 3 min
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 “unknown key [{}] for create index”classname is CreateIndexRequest.java We extracted the following from Elasticsearch source code for those seeking an in-depth context :
mapping(entry1.getKey(); (Map) entry1.getValue()); } } else if (ALIASES.match(name; deprecationHandler)) { aliases((Map ) entry.getValue()); } else { throw new ElasticsearchParseException("unknown key [{}] for create index"; name); } } return this; }
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