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Elastic Docs ›Elasticsearch Guide [2.4] ›Mapping ›Dynamic Mapping

Dynamic templates

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Dynamic templates

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Dynamic templates allow you to define custom mappings that can be applied to dynamically added fields based on:

The original field name {name} and the detected datatype {dynamic_type} template variables can be used in the mapping specification as placeholders.

Dynamic field mappings are only added when a field contains a concrete value — not null or an empty array. This means that if the null_value option is used in a dynamic_template, it will only be applied after the first document with a concrete value for the field has been indexed.

Dynamic templates are specified as an array of named objects:

  "dynamic_templates": [
    {
      "my_template_name": { 
        ...  match conditions ... 
        "mapping": { ... } 
      }
    },
    ...
  ]

The template name can be any string value.

The match conditions can include any of : match_mapping_type, match, match_pattern, unmatch, path_match, path_unmatch.

The mapping that the matched field should use.

Templates are processed in order — the first matching template wins. New templates can be appended to the end of the list with the PUT mapping API. If a new template has the same name as an existing template, it will replace the old version.

match_mapping_type

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The match_mapping_type matches on the datatype detected by dynamic field mapping, in other words, the datatype that Elasticsearch thinks the field should have. Only the following datatypes can be automatically detected: boolean, date, double, long, object, string. It also accepts * to match all datatypes.

For example, if we wanted to map all integer fields as integer instead of long, and all string fields as both analyzed and not_analyzed, we could use the following template:

PUT my_index
{
  "mappings": {
    "my_type": {
      "dynamic_templates": [
        {
          "integers": {
            "match_mapping_type": "long",
            "mapping": {
              "type": "integer"
            }
          }
        },
        {
          "strings": {
            "match_mapping_type": "string",
            "mapping": {
              "type": "string",
              "fields": {
                "raw": {
                  "type":  "string",
                  "index": "not_analyzed",
                  "ignore_above": 256
                }
              }
            }
          }
        }
      ]
    }
  }
}

PUT my_index/my_type/1
{
  "my_integer": 5, 
  "my_string": "Some string" 
}

The my_integer field is mapped as an integer.

The my_string field is mapped as an analyzed string, with a not_analyzed multi field.

match and unmatch

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The match parameter uses a pattern to match on the fieldname, while unmatch uses a pattern to exclude fields matched by match.

The following example matches all string fields whose name starts with long_ (except for those which end with _text) and maps them as long fields:

PUT my_index
{
  "mappings": {
    "my_type": {
      "dynamic_templates": [
        {
          "longs_as_strings": {
            "match_mapping_type": "string",
            "match":   "long_*",
            "unmatch": "*_text",
            "mapping": {
              "type": "long"
            }
          }
        }
      ]
    }
  }
}

PUT my_index/my_type/1
{
  "long_num": "5", 
  "long_text": "foo" 
}

The long_num field is mapped as a long.

The long_text field uses the default string mapping.

match_pattern

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The match_pattern parameter adjusts the behavior of the match parameter such that it supports full Java regular expression matching on the field name instead of simple wildcards, for instance:

  "match_pattern": "regex",
  "match": "^profit_\d+$"

path_match and path_unmatch

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The path_match and path_unmatch parameters work in the same way as match and unmatch, but operate on the full dotted path to the field, not just the final name, e.g. some_object.*.some_field.

This example copies the values of any fields in the name object to the top-level full_name field, except for the middle field:

PUT my_index
{
  "mappings": {
    "my_type": {
      "dynamic_templates": [
        {
          "full_name": {
            "path_match":   "name.*",
            "path_unmatch": "*.middle",
            "mapping": {
              "type":       "string",
              "copy_to":    "full_name"
            }
          }
        }
      ]
    }
  }
}

PUT my_index/my_type/1
{
  "name": {
    "first":  "Alice",
    "middle": "Mary",
    "last":   "White"
  }
}

{name} and {dynamic_type}

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The {name} and {dynamic_type} placeholders are replaced in the mapping with the field name and detected dynamic type. The following example sets all string fields to use an analyzer with the same name as the field, and disables doc_values for all non-string fields:

PUT my_index
{
  "mappings": {
    "my_type": {
      "dynamic_templates": [
        {
          "named_analyzers": {
            "match_mapping_type": "string",
            "match": "*",
            "mapping": {
              "type": "string",
              "analyzer": "{name}"
            }
          }
        },
        {
          "no_doc_values": {
            "match_mapping_type":"*",
            "mapping": {
              "type": "{dynamic_type}",
              "doc_values": false
            }
          }
        }
      ]
    }
  }
}

PUT my_index/my_type/1
{
  "english": "Some English text", 
  "count":   5 
}

The english field is mapped as a string field with the english analyzer.

The count field is mapped as a long field with doc_values disabled
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