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Field datatypes

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Field datatypes

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Elasticsearch supports a number of different datatypes for the fields in a document:

Core datatypes

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String datatype: string
Numeric datatypes: long, integer, short, byte, double, float
Date datatype: date
Boolean datatype: boolean
Binary datatype: binary

Complex datatypes

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Array datatype: Array support does not require a dedicated type
Object datatype: object for single JSON objects
Nested datatype: nested for arrays of JSON objects

Geo datatypes

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Geo-point datatype: geo_point for lat/lon points
Geo-Shape datatype: geo_shape for complex shapes like polygons

Specialised datatypes

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IPv4 datatype: ip for IPv4 addresses
Completion datatype: completion to provide auto-complete suggestions
Token count datatype: token_count to count the number of tokens in a string
mapper-murmur3: murmur3 to compute hashes of values at index-time and store them in the index
Attachment datatype: See the mapper-attachments plugin which supports indexing attachments like Microsoft Office formats, Open Document formats, ePub, HTML, etc. into an attachment datatype.

Multi-fields

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It is often useful to index the same field in different ways for different purposes. For instance, a string field could be indexed as an analyzed field for full-text search, and as a not_analyzed field for sorting or aggregations. Alternatively, you could index a string field with the standard analyzer, the english analyzer, and the french analyzer.

This is the purpose of multi-fields. Most datatypes support multi-fields via the fields parameter.

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