83 lines
2.1 KiB
Plaintext
83 lines
2.1 KiB
Plaintext
[[search-analyzer]]
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=== `search_analyzer`
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Usually, the same <<analyzer,analyzer>> should be applied at index time and at
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search time, to ensure that the terms in the query are in the same format as
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the terms in the inverted index.
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Sometimes, though, it can make sense to use a different analyzer at search
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time, such as when using the <<analysis-edgengram-tokenizer,`edge_ngram`>>
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tokenizer for autocomplete.
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By default, queries will use the `analyzer` defined in the field mapping, but
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this can be overridden with the `search_analyzer` setting:
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[source,js]
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--------------------------------------------------
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PUT my_index?include_type_name=true
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{
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"settings": {
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"analysis": {
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"filter": {
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"autocomplete_filter": {
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"type": "edge_ngram",
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"min_gram": 1,
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"max_gram": 20
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}
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},
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"analyzer": {
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"autocomplete": { <1>
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"type": "custom",
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"tokenizer": "standard",
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"filter": [
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"lowercase",
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"autocomplete_filter"
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]
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}
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}
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}
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},
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"mappings": {
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"_doc": {
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"properties": {
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"text": {
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"type": "text",
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"analyzer": "autocomplete", <2>
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"search_analyzer": "standard" <2>
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}
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}
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}
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}
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}
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PUT my_index/_doc/1
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{
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"text": "Quick Brown Fox" <3>
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}
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GET my_index/_search
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{
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"query": {
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"match": {
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"text": {
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"query": "Quick Br", <4>
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"operator": "and"
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}
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}
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}
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}
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--------------------------------------------------
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// CONSOLE
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<1> Analysis settings to define the custom `autocomplete` analyzer.
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<2> The `text` field uses the `autocomplete` analyzer at index time, but the `standard` analyzer at search time.
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<3> This field is indexed as the terms: [ `q`, `qu`, `qui`, `quic`, `quick`, `b`, `br`, `bro`, `brow`, `brown`, `f`, `fo`, `fox` ]
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<4> The query searches for both of these terms: [ `quick`, `br` ]
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See {defguide}/_index_time_search_as_you_type.html[Index time search-as-you-
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type] for a full explanation of this example.
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TIP: The `search_analyzer` setting can be updated on existing fields
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using the <<indices-put-mapping,PUT mapping API>>.
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