Upgrading index template for from version to version – How to solve this Elasticsearch error

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

DELETE /*

action.destructive_requires_name: true

Overview

A version corresponds to the Elasticsearch built-in tracking system that tracks the changes in each document’s update. When a document is indexed for the first time, it is assigned a version 1 using _version key. When the same document gets a subsequent update, the _version is incremented by 1 with every index, update or delete API call.

What it is used for

A version is used to handle the concurrency issues in Elasticsearch which come into play during simultaneous accessing of an index by multiple users. Elasticsearch handles this issue with an optimistic locking concept using the _version parameter to avoid letting multiple users edit the same document at the same time and protects users from generating incorrect data.

Notes

You cannot see the history of the document using _version. That means Elasticsearch does not use _version to keep a track of original changes that had been performed on the document. For example, if a document has been updated 10 times, it’s _version would be marked by Elasticsearch as 11, but you cannot go back and see what version 5 of the document looked like. This has to be implemented independently.

Common problems

If optimistic locking is not implemented while making updates to a document, Elasticsearch may return a conflict error with the 409 status code, which means that multiple users are trying to update the same version of the document at the same time.

POST /ratings/123?version=50
{
    "name": "Joker",
    "rating": 50
}

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: 

1. 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.
2. 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.