Briefly, this error occurs when Elasticsearch encounters an unrecognized key in the index template. This could be due to a typo, incorrect syntax, or usage of a key that is not supported in the current version of Elasticsearch. To resolve this issue, you should first verify the keys used in your index template against the Elasticsearch documentation for your version. Ensure that all keys are spelled correctly and are in the correct format. If the error persists, consider upgrading your Elasticsearch version to one that supports the key in question.
This guide will help you check for common problems that cause the log ” unknown key [{}] for index template ” to appear. To understand the issues related to this log, read the explanation below about the following Elasticsearch concepts: index, metadata, template, cluster.
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
Overview
Metadata in Elasticsearch refers to additional information stored for each document. This is achieved using the specific metadata fields available in Elasticsearch. The default behavior of some of these metadata fields can be customized during mapping creation.
Examples
Using _meta meta-field for storing application-specific information with the mapping:
PUT /my_index?pretty
{
"mappings": {
"_meta": {
"domain": "security",
"release_information": {
"date": "18-01-2020",
"version": "7.5"
}
}
}
}Notes
- In version 2.x, Elasticsearch had a total 13 meta fields available, which are: _index, _uid, _type, _id, _source, _size, _all, _field_names, _timestamp, _ttl, _parent, _routing, _meta
- In version 5.x, _timestamp and _ttl meta fields were removed.
- In version 6.x, the _parent meta field was removed.
- In version 7.x, _uid and _all meta fields were removed.
If you want to learn more about Elasticsearch templates, check out this guide.
Overview
A template in Elasticsearch falls into one of the two following categories and is indexed inside Elasticsearch using its dedicated endpoint:
- Index templates, which are a way to define a set of rules including index settings, mappings and an index pattern. The template is applied automatically whenever a new index is created with the matching pattern. Templates are also used to dynamically apply custom mapping for the fields which are not predefined inside existing mapping.
- Search templates, which help in defining templates for search queries using mustache scripting language. These templates act as a placeholder for variables defined inside the search queries.
Examples
Create a dynamic index template
PUT /_template/template_1?pretty
{
"index_patterns": [
"logs*",
"api*"
],
"settings": {
"number_of_shards": 2
},
"mappings": {
"dynamic_templates": [
{
"strings": {
"match_mapping_type": "string",
"mapping": {
"type": "keyword"
}
}
}
],
"properties": {
"host_name": {
"type": "keyword"
},
"created_at": {
"type": "date"
}
}
}
}Create a search template
POST /_scripts/search_template_1?pretty
{
"script": {
"lang": "mustache",
"source": {
"query": {
"match": {
"description": "{{query_string}}"
}
}
}
}
}Executing a search query using search template
GET /_search/template?pretty
{
"id": "search_template_1",
"params": {
"query_string": "hello world"
}
}The search request will be executed by default on all the indices available in the cluster and can be limited to particular indices using an index parameter.
Notes
- A dynamic index template is always useful when you do not know the field names in advance and want to control their mapping as per the business use case.
Log Context
Log “unknown key [{}] for index template” class name is IndexTemplateMetadata.java. We extracted the following from Elasticsearch source code for those seeking an in-depth context :
} else if ("aliases".equals(currentFieldName)) {
while ((token = parser.nextToken()) != XContentParser.Token.END_OBJECT) {
builder.putAlias(AliasMetadata.Builder.fromXContent(parser));
}
} else {
throw new ElasticsearchParseException("unknown key [{}] for index template"; currentFieldName);
}
} else if (token == XContentParser.Token.START_ARRAY) {
if ("mappings".equals(currentFieldName)) {
while ((token = parser.nextToken()) != XContentParser.Token.END_ARRAY) {
Map mapping = parser.mapOrdered();
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