164 lines
2.8 KiB
Plaintext
164 lines
2.8 KiB
Plaintext
[[normalizer]]
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=== `normalizer`
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The `normalizer` property of <<keyword,`keyword`>> fields is similar to
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<<analyzer,`analyzer`>> except that it guarantees that the analysis chain
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produces a single token.
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The `normalizer` is applied prior to indexing the keyword, as well as at
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search-time when the `keyword` field is searched via a query parser such as
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the <<query-dsl-match-query,`match`>> query.
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[source,js]
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--------------------------------
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PUT index
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{
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"settings": {
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"analysis": {
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"normalizer": {
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"my_normalizer": {
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"type": "custom",
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"char_filter": [],
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"filter": ["lowercase", "asciifolding"]
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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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"type": {
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"properties": {
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"foo": {
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"type": "keyword",
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"normalizer": "my_normalizer"
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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 index/type/1
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{
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"foo": "BÀR"
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}
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PUT index/type/2
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{
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"foo": "bar"
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}
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PUT index/type/3
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{
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"foo": "baz"
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}
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POST index/_refresh
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GET index/_search
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{
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"query": {
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"match": {
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"foo": "BAR"
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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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The above query matches documents 1 and 2 since `BÀR` is converted to `bar` at
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both index and query time.
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[source,js]
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----------------------------
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{
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"took": $body.took,
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"timed_out": false,
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"_shards": {
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"total": 5,
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"successful": 5,
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"failed": 0
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},
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"hits": {
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"total": 2,
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"max_score": 0.2876821,
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"hits": [
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{
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"_index": "index",
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"_type": "type",
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"_id": "2",
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"_score": 0.2876821,
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"_source": {
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"foo": "bar"
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}
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},
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{
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"_index": "index",
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"_type": "type",
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"_id": "1",
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"_score": 0.2876821,
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"_source": {
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"foo": "BÀR"
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}
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}
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]
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}
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}
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----------------------------
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// TESTRESPONSE[s/"took".*/"took": "$body.took",/]
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Also, the fact that keywords are converted prior to indexing also means that
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aggregations return normalized values:
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[source,js]
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----------------------------
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GET index/_search
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{
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"size": 0,
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"aggs": {
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"foo_terms": {
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"terms": {
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"field": "foo"
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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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// TEST[continued]
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returns
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[source,js]
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----------------------------
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{
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"took": 43,
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"timed_out": false,
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"_shards": {
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"total": 5,
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"successful": 5,
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"failed": 0
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},
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"hits": {
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"total": 3,
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"max_score": 0.0,
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"hits": []
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},
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"aggregations": {
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"foo_terms": {
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"doc_count_error_upper_bound": 0,
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"sum_other_doc_count": 0,
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"buckets": [
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{
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"key": "bar",
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"doc_count": 2
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},
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{
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"key": "baz",
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"doc_count": 1
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}
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]
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}
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}
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}
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----------------------------
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// TESTRESPONSE[s/"took".*/"took": "$body.took",/]
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