[[mapping-core-types]]
=== Core Types

Each JSON field can be mapped to a specific core type. JSON itself
already provides us with some typing, with its support for `string`,
`integer`/`long`, `float`/`double`, `boolean`, and `null`.

The following sample tweet JSON document will be used to explain the
core types:

[source,js]
--------------------------------------------------
{
    "tweet" {
        "user" : "kimchy",
        "message" : "This is a tweet!",
        "postDate" : "2009-11-15T14:12:12",
        "priority" : 4,
        "rank" : 12.3
    }
}
--------------------------------------------------

Explicit mapping for the above JSON tweet can be:

[source,js]
--------------------------------------------------
{
    "tweet" : {
        "properties" : {
            "user" : {"type" : "string", "index" : "not_analyzed"},
            "message" : {"type" : "string", "null_value" : "na"},
            "postDate" : {"type" : "date"},
            "priority" : {"type" : "integer"},
            "rank" : {"type" : "float"}
        }
    }
}
--------------------------------------------------

[float]
[[string]]
==== String

The text based string type is the most basic type, and contains one or
more characters. An example mapping can be:

[source,js]
--------------------------------------------------
{
    "tweet" : {
        "properties" : {
            "message" : {
                "type" : "string",
                "store" : true,
                "index" : "analyzed",
                "null_value" : "na"
            },
            "user" : {
                "type" : "string",
                "index" : "not_analyzed",
                "norms" : {
                    "enabled" : false
                }
            }
        }
    }
}
--------------------------------------------------

The above mapping defines a `string` `message` property/field within the
`tweet` type. The field is stored in the index (so it can later be
retrieved using selective loading when searching), and it gets analyzed
(broken down into searchable terms). If the message has a `null` value,
then the value that will be stored is `na`. There is also a `string` `user`
which is indexed as-is (not broken down into tokens) and has norms
disabled (so that matching this field is a binary decision, no match is
better than another one).

The following table lists all the attributes that can be used with the
`string` type:

[cols="<,<",options="header",]
|=======================================================================
|Attribute |Description
|`index_name` |deprecated[1.5.0,Use <<copy-to,`copy_to`>> instead] The name of the field that will be stored in the index.
Defaults to the property/field name.

|`store` |Set to `true` to actually store the field in the index, `false` to not
store it. Since by default Elasticsearch stores all fields of the source
document in the special `_source` field, this option is primarily useful when
the `_source` field has been disabled in the type definition. Defaults to
`false`.

|`index` |Set to `analyzed` for the field to be indexed and searchable
after being broken down into token using an analyzer. `not_analyzed`
means that its still searchable, but does not go through any analysis
process or broken down into tokens. `no` means that it won't be
searchable at all (as an individual field; it may still be included in
`_all`). Setting to `no` disables `include_in_all`. Defaults to
`analyzed`.

|`doc_values` |Set to `true` to store field values in a column-stride fashion.
Automatically set to `true` when the <<fielddata-formats,`fielddata` format>> is `doc_values`.

|`term_vector` |Possible values are `no`, `yes`, `with_offsets`,
`with_positions`, `with_positions_offsets`. Defaults to `no`.

|`boost` |The boost value. Defaults to `1.0`.

|`null_value` |When there is a (JSON) null value for the field, use the
`null_value` as the field value. Defaults to not adding the field at
all.

|`norms: {enabled: <value>}` |Boolean value if norms should be enabled or
not. Defaults to `true` for `analyzed` fields, and to `false` for
`not_analyzed` fields. See the <<norms,section about norms>>.

|`norms: {loading: <value>}` |Describes how norms should be loaded, possible values are
`eager` and `lazy` (default). It is possible to change the default value to
eager for all fields by configuring the index setting `index.norms.loading`
to `eager`.

|`index_options` | Allows to set the indexing
options, possible values are `docs` (only doc numbers are indexed),
`freqs` (doc numbers and term frequencies), and `positions` (doc
numbers, term frequencies and positions). Defaults to `positions` for
`analyzed` fields, and to `docs` for `not_analyzed` fields. It
is also possible to set it to `offsets` (doc numbers, term
frequencies, positions and offsets).

|`analyzer` |The analyzer used to analyze the text contents when
`analyzed` during indexing and when searching using a query string.
Defaults to the globally configured analyzer.

|`index_analyzer` |The analyzer used to analyze the text contents when
`analyzed` during indexing.

|`search_analyzer` |The analyzer used to analyze the field when part of
a query string. Can be updated on an existing field.

|`include_in_all` |Should the field be included in the `_all` field (if
enabled). If `index` is set to `no` this defaults to `false`, otherwise,
defaults to `true` or to the parent `object` type setting.

|`ignore_above` |The analyzer will ignore strings larger than this size.
Useful for generic `not_analyzed` fields that should ignore long text.

This option is also useful for protecting against Lucene's term byte-length
limit of `32766`. Note: the value for `ignore_above` is the _character count_,
but Lucene counts bytes, so if you have UTF-8 text, you may want to set the
limit to `32766 / 3 = 10922` since UTF-8 characters may occupy at most 3
bytes.

|`position_offset_gap` |Position increment gap between field instances
with the same field name. Defaults to 0.
|=======================================================================

The `string` type also support custom indexing parameters associated
with the indexed value. For example:

[source,js]
--------------------------------------------------
{
    "message" : {
        "_value":  "boosted value",
        "_boost":  2.0
    }
}
--------------------------------------------------

The mapping is required to disambiguate the meaning of the document.
Otherwise, the structure would interpret "message" as a value of type
"object". The key `_value` (or `value`) in the inner document specifies
the real string content that should eventually be indexed. The `_boost`
(or `boost`) key specifies the per field document boost (here 2.0).

[float]
[[norms]]
===== Norms

Norms store various normalization factors that are later used (at query time)
in order to compute the score of a document relatively to a query.

Although useful for scoring, norms also require quite a lot of memory
(typically in the order of one byte per document per field in your index,
even for documents that don't have this specific field). As a consequence, if
you don't need scoring on a specific field, it is highly recommended to disable
norms on it. In  particular, this is the case for fields that are used solely
for filtering or aggregations.

In case you would like to disable norms after the fact, it is possible to do so
by using the <<indices-put-mapping,PUT mapping API>>, like this:

[source,json]
------------
PUT my_index/_mapping/my_type
{
  "properties": {
    "title": {
      "type": "string",
      "norms": {
        "enabled": false
      }
    }
  }
}
------------

Please however note that norms won't be removed instantly, but will be removed
as old segments are merged into new segments as you continue indexing new documents.
Any score computation on a field that has had
norms removed might return inconsistent results since some documents won't have
norms anymore while other documents might still have norms.

[float]
[[number]]
==== Number

A number based type supporting `float`, `double`, `byte`, `short`,
`integer`, and `long`. It uses specific constructs within Lucene in
order to support numeric values. The number types have the same ranges
as corresponding
http://docs.oracle.com/javase/tutorial/java/nutsandbolts/datatypes.html[Java
types]. An example mapping can be:

[source,js]
--------------------------------------------------
{
    "tweet" : {
        "properties" : {
            "rank" : {
                "type" : "float",
                "null_value" : 1.0
            }
        }
    }
}
--------------------------------------------------

The following table lists all the attributes that can be used with a
numbered type:

[cols="<,<",options="header",]
|=======================================================================
|Attribute |Description
|`type` |The type of the number. Can be `float`, `double`, `integer`,
`long`, `short`, `byte`. Required.

|`index_name` |deprecated[1.5.0,Use <<copy-to,`copy_to`>> instead] The name of the field that will be stored in the index.
Defaults to the property/field name.

|`store` |Set to `true` to store actual field in the index, `false` to not
store it. Defaults to `false` (note, the JSON document itself is stored,
and it can be retrieved from it).

|`index` |Set to `no` if the value should not be indexed. Setting to
`no` disables `include_in_all`. If set to `no` the field should be either stored
in `_source`, have `include_in_all` enabled, or `store` be set to
`true` for this to be useful.

|`doc_values` |Set to `true` to store field values in a column-stride fashion.
Automatically set to `true` when the fielddata format is `doc_values`.

|`precision_step` |The precision step (influences the number of terms
generated for each number value). Defaults to `16` for `long`, `double`,
`8` for `short`, `integer`, `float`, and `2147483647` for `byte`.

|`boost` |The boost value. Defaults to `1.0`.

|`null_value` |When there is a (JSON) null value for the field, use the
`null_value` as the field value. Defaults to not adding the field at
all.

|`include_in_all` |Should the field be included in the `_all` field (if
enabled). If `index` is set to `no` this defaults to `false`, otherwise,
defaults to `true` or to the parent `object` type setting.

|`ignore_malformed` |Ignored a malformed number. Defaults to `false`.

|`coerce` |Try convert strings to numbers and truncate fractions for integers. Defaults to `true`.

|=======================================================================

[float]
[[token_count]]
==== Token Count
The `token_count` type maps to the JSON string type but indexes and stores
the number of tokens in the string rather than the string itself.  For
example:

[source,js]
--------------------------------------------------
{
    "tweet" : {
        "properties" : {
            "name" : {
                "type" : "string",
                "fields" : {
                    "word_count": {
                        "type" : "token_count",
                        "store" : "yes",
                        "analyzer" : "standard"
                    }
                }
            }
        }
    }
}
--------------------------------------------------

All the configuration that can be specified for a number can be specified
for a token_count.  The only extra configuration is the required
`analyzer` field which specifies which analyzer to use to break the string
into tokens.  For best performance, use an analyzer with no token filters.

[NOTE]
===================================================================
Technically the `token_count` type sums position increments rather than
counting tokens. This means that even if the analyzer filters out stop
words they are included in the count.
===================================================================

[float]
[[date]]
==== Date

The date type is a special type which maps to JSON string type. It
follows a specific format that can be explicitly set. All dates are
`UTC`. Internally, a date maps to a number type `long`, with the added
parsing stage from string to long and from long to string. An example
mapping:

[source,js]
--------------------------------------------------
{
    "tweet" : {
        "properties" : {
            "postDate" : {
                "type" : "date",
                "format" : "YYYY-MM-dd"
            }
        }
    }
}
--------------------------------------------------

The date type will also accept a long number representing UTC
milliseconds since the epoch, regardless of the format it can handle.

The following table lists all the attributes that can be used with a
date type:

[cols="<,<",options="header",]
|=======================================================================
|Attribute |Description
|`index_name` |deprecated[1.5.0,Use <<copy-to,`copy_to`>> instead] The name of the field that will be stored in the index.
Defaults to the property/field name.

|`format` |The <<mapping-date-format,date
format>>. Defaults to `dateOptionalTime`.

|`store` |Set to `true` to store actual field in the index, `false` to not
store it. Defaults to `false` (note, the JSON document itself is stored,
and it can be retrieved from it).

|`index` |Set to `no` if the value should not be indexed. Setting to
`no` disables `include_in_all`. If set to `no` the field should be either stored
in `_source`, have `include_in_all` enabled, or `store` be set to
`true` for this to be useful.

|`doc_values` |Set to `true` to store field values in a column-stride fashion.
Automatically set to `true` when the fielddata format is `doc_values`.

|`precision_step` |The precision step (influences the number of terms
generated for each number value). Defaults to `16`.

|`boost` |The boost value. Defaults to `1.0`.

|`null_value` |When there is a (JSON) null value for the field, use the
`null_value` as the field value. Defaults to not adding the field at
all.

|`include_in_all` |Should the field be included in the `_all` field (if
enabled). If `index` is set to `no` this defaults to `false`, otherwise,
defaults to `true` or to the parent `object` type setting.

|`ignore_malformed` |Ignored a malformed number. Defaults to `false`.

|`numeric_resolution` |The unit to use when passed in a numeric values. Possible
values include `seconds` and  `milliseconds` (default).

|=======================================================================

[float]
[[boolean]]
==== Boolean

The boolean type Maps to the JSON boolean type. It ends up storing
within the index either `T` or `F`, with automatic translation to `true`
and `false` respectively.

[source,js]
--------------------------------------------------
{
    "tweet" : {
        "properties" : {
            "has_my_special_tweet" : {
                "type" : "boolean"
            }
        }
    }
}
--------------------------------------------------

The boolean type also supports passing the value as a number or a string
(in this case `0`, an empty string, `false`, `off` and `no` are
`false`, all other values are `true`).

The following table lists all the attributes that can be used with the
boolean type:

[cols="<,<",options="header",]
|=======================================================================
|Attribute |Description
|`index_name` |deprecated[1.5.0,Use <<copy-to,`copy_to`>> instead] The name of the field that will be stored in the index.
Defaults to the property/field name.

|`store` |Set to `true` to store actual field in the index, `false` to not
store it. Defaults to `false` (note, the JSON document itself is stored,
and it can be retrieved from it).

|`index` |Set to `no` if the value should not be indexed. Setting to
`no` disables `include_in_all`. If set to `no` the field should be either stored
in `_source`, have `include_in_all` enabled, or `store` be set to
`true` for this to be useful.

|`boost` |The boost value. Defaults to `1.0`.

|`null_value` |When there is a (JSON) null value for the field, use the
`null_value` as the field value. Defaults to not adding the field at
all.
|=======================================================================

[float]
[[binary]]
==== Binary

The binary type is a base64 representation of binary data that can be
stored in the index. The field is not stored by default and not indexed at
all.

[source,js]
--------------------------------------------------
{
    "tweet" : {
        "properties" : {
            "image" : {
                "type" : "binary"
            }
        }
    }
}
--------------------------------------------------

The following table lists all the attributes that can be used with the
binary type:

[horizontal]

`index_name`::

    deprecated[1.5.0,Use <<copy-to,`copy_to`>> instead] The name of the field that will be stored in the index.
    Defaults to the property/field name.

`store`::

    Set to `true` to store actual field in the index, `false` to not store it.
    Defaults to `false` (note, the JSON document itself is already stored, so
    the binary field can be retrieved from there).

`doc_values`::

    Set to `true` to store field values in a column-stride fashion.

`compress`::

    Set to `true` to compress the stored binary value.

`compress_threshold`::

    Compression will only be applied to stored binary fields that are greater
    than this size. Defaults to `-1`

NOTE: Enabling compression on stored binary fields only makes sense on large
and highly-compressible values. Otherwise per-field compression is usually not
worth doing as the space savings do not compensate for the overhead of the
compression format. Normally, you should not configure any compression and
just rely on the block compression of stored fields (which is enabled by
default and can't be disabled).

[float]
[[fielddata-filters]]
==== Fielddata filters

It is possible to control which field values are loaded into memory,
which is particularly useful for aggregating on string fields, using
fielddata filters, which are explained in detail in the
<<index-modules-fielddata,Fielddata>> section.

Fielddata filters can exclude terms which do not match a regex, or which
don't fall between a `min` and `max` frequency range:

[source,js]
--------------------------------------------------
{
    tweet: {
        type:      "string",
        analyzer:  "whitespace"
        fielddata: {
            filter: {
                regex: {
                    "pattern":        "^#.*"
                },
                frequency: {
                    min:              0.001,
                    max:              0.1,
                    min_segment_size: 500
                }
            }
        }
    }
}
--------------------------------------------------

These filters can be updated on an existing field mapping and will take
effect the next time the fielddata for a segment is loaded. Use the
<<indices-clearcache,Clear Cache>> API
to reload the fielddata using the new filters.

[float]
==== Similarity

Elasticsearch allows you to configure a similarity (scoring algorithm) per field.
The `similarity` setting provides a simple way of choosing a similarity algorithm
other than the default TF/IDF, such as `BM25`.

You can configure similarities via the
<<index-modules-similarity,similarity module>>

[float]
===== Configuring Similarity per Field

Defining the Similarity for a field is done via the `similarity` mapping
property, as this example shows:

[source,js]
--------------------------------------------------
{
   "book":{
      "properties":{
         "title":{
            "type":"string", "similarity":"BM25"
         }
      }
   }
}
--------------------------------------------------

The following Similarities are configured out-of-box:

`default`::
        The Default TF/IDF algorithm used by Elasticsearch and
        Lucene in previous versions.

`BM25`::
        The BM25 algorithm.
        http://en.wikipedia.org/wiki/Okapi_BM25[See Okapi_BM25] for more
        details.


[[copy-to]]
[float]
===== Copy to field

Adding `copy_to` parameter to any field mapping will cause all values of this field to be copied to fields specified in
the parameter. In the following example all values from fields `title` and `abstract` will be copied to the field
`meta_data`.


[source,js]
--------------------------------------------------
{
  "book" : {
    "properties" : {
      "title" : { "type" : "string", "copy_to" : "meta_data" },
      "abstract" : { "type" : "string", "copy_to" : "meta_data" },
      "meta_data" : { "type" : "string" }
    }
}
--------------------------------------------------

Multiple fields are also supported:

[source,js]
--------------------------------------------------
{
  "book" : {
    "properties" : {
      "title" : { "type" : "string", "copy_to" : ["meta_data", "article_info"] }
    }
}
--------------------------------------------------

[float]
===== Multi fields

The `fields` options allows to map several core types fields into a single
json source field. This can be useful if a single field need to be
used in different ways. For example a single field is to be used for both
free text search and sorting.

[source,js]
--------------------------------------------------
{
  "tweet" : {
    "properties" : {
      "name" : {
        "type" : "string",
        "index" : "analyzed",
        "fields" : {
          "raw" : {"type" : "string", "index" : "not_analyzed"}
        }
      }
    }
  }
}
--------------------------------------------------

In the above example the field `name` gets processed twice. The first time it gets
processed as an analyzed string and this version is accessible under the field name
`name`, this is the main field and is in fact just like any other field. The second time
it gets processed as a not analyzed string and is accessible under the name `name.raw`.

[float]
==== Include in All

The `include_in_all` setting is ignored on any field that is defined in
the `fields` options. Setting the `include_in_all` only makes sense on
the main field, since the raw field value is copied to the `_all` field,
the tokens aren't copied.

[float]
==== Updating a field

In the essence a field can't be updated. However multi fields can be
added to existing fields. This allows for example to have a different
`index_analyzer` configuration in addition to the already configured
`index_analyzer` configuration specified in the main and other multi fields.

Also the new multi field will only be applied on document that have been
added after the multi field has been added and in fact the new multi field
doesn't exist in existing documents.

Another important note is that new multi fields will be merged into the
list of existing multi fields, so when adding new multi fields for a field
previous added multi fields don't need to be specified.

[float]
==== Accessing Fields

The multi fields defined in the `fields` are prefixed with the
name of the main field and can be accessed by their full path using the
navigation notation: `name.raw`, or using the typed navigation notation
`tweet.name.raw`. 

deprecated[1.0.0,The `path` option below is deprecated.  Use <<copy-to,`copy_to`>> instead for setting up custom _all fields]

In older releases, the `path` option allows to control how fields are accessed.
If the `path` option is set to `full`, then the full path of the main field
is prefixed, but if the `path` option is set to `just_name` the actual
multi field name without any prefix is used. The default value for
the `path` option is `full`.

The `just_name` setting, among other things, allows indexing content of multiple
fields under the same name (commonly used to set up custom _all fields in the past). 
In the example below the content of both fields `first_name` and `last_name` 
can be accessed by using `any_name` or `tweet.any_name`.

[source,js]
--------------------------------------------------
{
  "tweet" : {
    "properties": {
      "first_name": {
        "type": "string",
        "index": "analyzed",
        "path": "just_name",
        "fields": {
          "any_name": {"type": "string","index": "analyzed"}
        }
      },
      "last_name": {
        "type": "string",
        "index": "analyzed",
        "path": "just_name",
        "fields": {
          "any_name": {"type": "string","index": "analyzed"}
        }
      }
    }
  }
}
--------------------------------------------------


