fields
editfields
editIt is often useful to index the same field in different ways for different
purposes. This is the purpose of multi-fields. For instance, a string
field could be mapped as a text
field for full-text
search, and as a keyword
field for sorting or aggregations:
response = client.indices.create( index: 'my-index-000001', body: { mappings: { properties: { city: { type: 'text', fields: { raw: { type: 'keyword' } } } } } } ) puts response response = client.indices.create( index: 'my-index-000001', id: 1, body: { city: 'New York' } ) puts response response = client.indices.create( index: 'my-index-000001', id: 2, body: { city: 'York' } ) puts response response = client.indices.create( index: 'my-index-000001', body: { query: { match: { city: 'york' } }, sort: { "city.raw": 'asc' }, aggregations: { "Cities": { terms: { field: 'city.raw' } } } } ) puts response
{ res, err := es.Indices.Create( "my-index-000001", es.Indices.Create.WithBody(strings.NewReader(`{ "mappings": { "properties": { "city": { "type": "text", "fields": { "raw": { "type": "keyword" } } } } } }`)), ) fmt.Println(res, err) } { res, err := es.Index( "my-index-000001", strings.NewReader(`{ "city": "New York" }`), es.Index.WithDocumentID("1"), es.Index.WithPretty(), ) fmt.Println(res, err) } { res, err := es.Index( "my-index-000001", strings.NewReader(`{ "city": "York" }`), es.Index.WithDocumentID("2"), es.Index.WithPretty(), ) fmt.Println(res, err) } { res, err := es.Search( es.Search.WithIndex("my-index-000001"), es.Search.WithBody(strings.NewReader(`{ "query": { "match": { "city": "york" } }, "sort": { "city.raw": "asc" }, "aggs": { "Cities": { "terms": { "field": "city.raw" } } } }`)), es.Search.WithPretty(), ) fmt.Println(res, err) }
PUT my-index-000001 { "mappings": { "properties": { "city": { "type": "text", "fields": { "raw": { "type": "keyword" } } } } } } PUT my-index-000001/_doc/1 { "city": "New York" } PUT my-index-000001/_doc/2 { "city": "York" } GET my-index-000001/_search { "query": { "match": { "city": "york" } }, "sort": { "city.raw": "asc" }, "aggs": { "Cities": { "terms": { "field": "city.raw" } } } }
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You can add multi-fields to an existing field using the update mapping API.
If an index (or data stream) contains documents when you add a multi-field, those documents will not have values for the new multi-field. You can populate the new multi-field with the update by query API.
A multi-field mapping is completely separate from the parent field’s mapping. A
multi-field doesn’t inherit any mapping options from its parent field.
Multi-fields don’t change the original _source
field.
Multi-fields with multiple analyzers
editAnother use case of multi-fields is to analyze the same field in different
ways for better relevance. For instance we could index a field with the
standard
analyzer which breaks text up into
words, and again with the english
analyzer
which stems words into their root form:
response = client.indices.create( index: 'my-index-000001', body: { mappings: { properties: { text: { type: 'text', fields: { english: { type: 'text', analyzer: 'english' } } } } } } ) puts response response = client.indices.create( index: 'my-index-000001', id: 1, body: { text: 'quick brown fox' } ) puts response response = client.indices.create( index: 'my-index-000001', id: 2, body: { text: 'quick brown foxes' } ) puts response response = client.indices.create( index: 'my-index-000001', body: { query: { multi_match: { query: 'quick brown foxes', fields: [ 'text', 'text.english' ], type: 'most_fields' } } } ) puts response
{ res, err := es.Indices.Create( "my-index-000001", es.Indices.Create.WithBody(strings.NewReader(`{ "mappings": { "properties": { "text": { "type": "text", "fields": { "english": { "type": "text", "analyzer": "english" } } } } } }`)), ) fmt.Println(res, err) } { res, err := es.Index( "my-index-000001", strings.NewReader(`{ "text": "quick brown fox" } `), es.Index.WithDocumentID("1"), es.Index.WithPretty(), ) fmt.Println(res, err) } { res, err := es.Index( "my-index-000001", strings.NewReader(`{ "text": "quick brown foxes" } `), es.Index.WithDocumentID("2"), es.Index.WithPretty(), ) fmt.Println(res, err) } { res, err := es.Search( es.Search.WithIndex("my-index-000001"), es.Search.WithBody(strings.NewReader(`{ "query": { "multi_match": { "query": "quick brown foxes", "fields": [ "text", "text.english" ], "type": "most_fields" } } }`)), es.Search.WithPretty(), ) fmt.Println(res, err) }
PUT my-index-000001 { "mappings": { "properties": { "text": { "type": "text", "fields": { "english": { "type": "text", "analyzer": "english" } } } } } } PUT my-index-000001/_doc/1 { "text": "quick brown fox" } PUT my-index-000001/_doc/2 { "text": "quick brown foxes" } GET my-index-000001/_search { "query": { "multi_match": { "query": "quick brown foxes", "fields": [ "text", "text.english" ], "type": "most_fields" } } }
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Index two documents, one with |
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Query both the |
The text
field contains the term fox
in the first document and foxes
in
the second document. The text.english
field contains fox
for both
documents, because foxes
is stemmed to fox
.
The query string is also analyzed by the standard
analyzer for the text
field, and by the english
analyzer for the text.english
field. The
stemmed field allows a query for foxes
to also match the document containing
just fox
. This allows us to match as many documents as possible. By also
querying the unstemmed text
field, we improve the relevance score of the
document which matches foxes
exactly.