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Mappings use cases

Mappings provide control over how data is indexed and queried, enabling optimized performance and efficient storage for a range of use cases.


Example: Ignoring malformed IP addresses

The following example shows you how to create a mapping specifying that OpenSearch should ignore any documents containing malformed IP addresses that do not conform to the ip data type. You can accomplish this by setting the ignore_malformed parameter to true.

Create an index with an ip mapping

To create an index with an ip mapping, use a PUT request:

PUT /test-index 
{
  "mappings" : {
    "properties" :  {
      "ip_address" : {
        "type" : "ip",
        "ignore_malformed": true
      }
    }
  }
}

Then add a document with a malformed IP address:

PUT /test-index/_doc/1 
{
  "ip_address" : "malformed ip address"
}

When you query the index, the ip_address field will be ignored. You can query the index using the following request:

GET /test-index/_search

Response

{
  "took": 14,
  "timed_out": false,
  "_shards": {
    "total": 1,
    "successful": 1,
    "skipped": 0,
    "failed": 0
  },
  "hits": {
    "total": {
      "value": 1,
      "relation": "eq"
    },
    "max_score": 1,
    "hits": [
      {
        "_index": "test-index",
        "_id": "1",
        "_score": 1,
        "_ignored": [
          "ip_address"
        ],
        "_source": {
          "ip_address": "malformed ip address"
        }
      }
    ]
  }
}


Mapping string fields to text and keyword types

To create an index named movies1 with a dynamic template that maps all string fields to both the text and keyword types, you can use the following request:

PUT movies1
{
  "mappings": {
    "dynamic_templates": [
      {
        "strings": {
          "match_mapping_type": "string",
          "mapping": {
            "type": "text",
            "fields": {
              "keyword": {
                "type":  "keyword",
                "ignore_above": 256
              }
            }
          }
        }
      }
    ]
  }
}

This dynamic template ensures that any string fields in your documents will be indexed as both a full-text text type and a keyword type.

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