108 lines
3.6 KiB
Plaintext
108 lines
3.6 KiB
Plaintext
[[analyzer]]
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=== `analyzer`
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[IMPORTANT]
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====
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Only <<text,`text`>> fields support the `analyzer` mapping parameter.
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====
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The `analyzer` parameter specifies the <<analyzer-anatomy,analyzer>> used for
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<<analysis,text analysis>> when indexing or searching a `text` field.
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Unless overridden with the <<search-analyzer,`search_analyzer`>> mapping
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parameter, this analyzer is used for both <<analysis-index-search-time,index and
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search analysis>>. See <<specify-analyzer>>.
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[TIP]
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====
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We recommend testing analyzers before using them in production. See
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<<test-analyzer>>.
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====
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[[search-quote-analyzer]]
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==== `search_quote_analyzer`
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The `search_quote_analyzer` setting allows you to specify an analyzer for phrases, this is particularly useful when dealing with disabling
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stop words for phrase queries.
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To disable stop words for phrases a field utilising three analyzer settings will be required:
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1. An `analyzer` setting for indexing all terms including stop words
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2. A `search_analyzer` setting for non-phrase queries that will remove stop words
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3. A `search_quote_analyzer` setting for phrase queries that will not remove stop words
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[source,console]
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--------------------------------------------------
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PUT my-index-000001
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{
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"settings":{
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"analysis":{
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"analyzer":{
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"my_analyzer":{ <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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]
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},
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"my_stop_analyzer":{ <2>
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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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"english_stop"
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]
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}
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},
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"filter":{
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"english_stop":{
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"type":"stop",
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"stopwords":"_english_"
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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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"properties":{
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"title": {
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"type":"text",
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"analyzer":"my_analyzer", <3>
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"search_analyzer":"my_stop_analyzer", <4>
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"search_quote_analyzer":"my_analyzer" <5>
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}
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}
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}
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}
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PUT my-index-000001/_doc/1
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{
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"title":"The Quick Brown Fox"
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}
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PUT my-index-000001/_doc/2
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{
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"title":"A Quick Brown Fox"
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}
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GET my-index-000001/_search
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{
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"query":{
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"query_string":{
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"query":"\"the quick brown fox\"" <6>
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}
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}
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}
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--------------------------------------------------
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<1> `my_analyzer` analyzer which tokens all terms including stop words
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<2> `my_stop_analyzer` analyzer which removes stop words
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<3> `analyzer` setting that points to the `my_analyzer` analyzer which will be used at index time
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<4> `search_analyzer` setting that points to the `my_stop_analyzer` and removes stop words for non-phrase queries
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<5> `search_quote_analyzer` setting that points to the `my_analyzer` analyzer and ensures that stop words are not removed from phrase queries
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<6> Since the query is wrapped in quotes it is detected as a phrase query therefore the `search_quote_analyzer` kicks in and ensures the stop words
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are not removed from the query. The `my_analyzer` analyzer will then return the following tokens [`the`, `quick`, `brown`, `fox`] which will match one
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of the documents. Meanwhile term queries will be analyzed with the `my_stop_analyzer` analyzer which will filter out stop words. So a search for either
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`The quick brown fox` or `A quick brown fox` will return both documents since both documents contain the following tokens [`quick`, `brown`, `fox`].
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Without the `search_quote_analyzer` it would not be possible to do exact matches for phrase queries as the stop words from phrase queries would be
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removed resulting in both documents matching.
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