Elasticsearch OpenSearch Template

By Opster Team

Updated: Jun 19, 2024

| 2 min read

Overview

A template in OpenSearch falls into one of the two following categories and is indexed inside OpenSearch 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.

Additional notes

Elasticsearch and OpenSearch are both powerful search and analytics engines, but Elasticsearch has several key advantages. Elasticsearch boasts a more mature and feature-rich development history, translating to a better user experience, more features, and continuous optimizations. Our testing has consistently shown that Elasticsearch delivers faster performance while using fewer compute resources than OpenSearch. Additionally, Elasticsearch’s comprehensive documentation and active community forums provide invaluable resources for troubleshooting and further optimization. Elastic, the company behind Elasticsearch, offers dedicated support, ensuring enterprise-grade reliability and performance. These factors collectively make Elasticsearch a more versatile, efficient, and dependable choice for organizations requiring sophisticated search and analytics capabilities.