224 lines
4.9 KiB
Plaintext
224 lines
4.9 KiB
Plaintext
[[mixing-exact-search-with-stemming]]
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=== Mixing exact search with stemming
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When building a search application, stemming is often a must as it is desirable
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for a query on `skiing` to match documents that contain `ski` or `skis`. But
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what if a user wants to search for `skiing` specifically? The typical way to do
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this would be to use a <<multi-fields,multi-field>> in order to have the same
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content indexed in two different ways:
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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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"analyzer": {
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"english_exact": {
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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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}
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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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"body": {
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"type": "text",
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"analyzer": "english",
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"fields": {
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"exact": {
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"type": "text",
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"analyzer": "english_exact"
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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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}
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PUT index/type/1
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{
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"body": "Ski resort"
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}
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PUT index/type/2
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{
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"body": "A pair of skis"
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}
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POST index/_refresh
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--------------------------------------------------
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// CONSOLE
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With such a setup, searching for `ski` on `body` would return both documents:
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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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"query": {
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"simple_query_string": {
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"fields": [ "body" ],
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"query": "ski"
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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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[source,js]
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--------------------------------------------------
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{
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"took": 2,
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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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"skipped" : 0,
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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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"body": "A pair of skis"
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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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"body": "Ski resort"
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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": 2,/"took": "$body.took",/]
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On the other hand, searching for `ski` on `body.exact` would only return
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document `1` since the analysis chain of `body.exact` does not perform
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stemming.
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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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"query": {
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"simple_query_string": {
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"fields": [ "body.exact" ],
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"query": "ski"
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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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[source,js]
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--------------------------------------------------
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{
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"took": 1,
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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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"skipped" : 0,
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"failed": 0
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},
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"hits": {
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"total": 1,
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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": "1",
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"_score": 0.2876821,
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"_source": {
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"body": "Ski resort"
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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": 1,/"took": "$body.took",/]
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This is not something that is easy to expose to end users, as we would need to
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have a way to figure out whether they are looking for an exact match or not and
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redirect to the appropriate field accordingly. Also what to do if only parts of
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the query need to be matched exactly while other parts should still take
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stemming into account?
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Fortunately, the `query_string` and `simple_query_string` queries have a feature
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that solve this exact problem: `quote_field_suffix`. This tell Elasticsearch
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that the words that appear in between quotes are to be redirected to a different
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field, see below:
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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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"query": {
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"simple_query_string": {
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"fields": [ "body" ],
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"quote_field_suffix": ".exact",
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"query": "\"ski\""
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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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[source,js]
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--------------------------------------------------
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{
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"took": 2,
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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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"skipped" : 0,
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"failed": 0
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},
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"hits": {
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"total": 1,
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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": "1",
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"_score": 0.2876821,
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"_source": {
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"body": "Ski resort"
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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": 2,/"took": "$body.took",/]
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In the above case, since `ski` was in-between quotes, it was searched on the
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`body.exact` field due to the `quote_field_suffix` parameter, so only document
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`1` matched. This allows users to mix exact search with stemmed search as they
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like.
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