CODEWITHSUNDEEP
elasticsearch
user3683474
user3683474

Reputation: 263

Elasticsearch Map case insensitive to not_analyzed documents

I have a type with following mapping

PUT /testindex
{
    "mappings" : {
        "products" : {
            "properties" : {
                "category_name" : {
                    "type" : "string",
                    "index" : "not_analyzed" 
                }
            }
        }
    }

}

I wanted to search for an exact word.Thats why i set this as not_analyzed. But the problem is i want to search that with lower case or upper case[case insensitive].

I searched for it and found a way to set case insensitive.

curl -XPOST localhost:9200/testindex -d '{
  "mappings" : {
    "products" : {
      "properties" : {        
        "category_name":{"type": "string", "index": "analyzed", "analyzer":"lowercase_keyword"}
      }
    }
  }
}'

Is there any way to do these two mappings to same field.?

Thanks..

Upvotes: 25

Views: 24830

Answers (8)

Rakesh Jaligama
Rakesh Jaligama

Reputation: 11

it is so simple, just create mapping as follows

{
    "mappings" : {
        "products" : {
            "properties" : {
                "category_name" : {
                    "type" : "string" 
                }
            }
        }
    }

}

No Need of giving index if you want to work with case insensitive because the default index will be "standard" that will take care of case insensitive.

Upvotes: 1

geekprogrammer
geekprogrammer

Reputation: 1123

We could achieve case insensitive searching on non-analyzed strings using ElasticSearch scripting.

Example Query Using Inline Scripting:

{
    "query" : {
        "bool" : {

            "must" : [{
                    "query_string" : {
                        "query" : "\"apache\"",
                        "default_field" : "COLLECTOR_NAME"
                    }
                }, {
                    "script" : {
                        "script" : "if(doc['verb'].value != null) {doc['verb'].value.equalsIgnoreCase(\"geT\")}"
                    }
                }
            ]

        }
    }
}

You need to enable scripting in the elasticsearch.yml file. Using scripts in search queries could reduce your overall search performance. If you want scripts to perform better, then you should make them "native" using java plugin.

Example Plugin Code:

public class MyNativeScriptPlugin extends Plugin {

    @Override
    public String name() {
        return "Indexer scripting Plugin";
    }


    public void onModule(ScriptModule scriptModule) {
        scriptModule.registerScript("my_script", MyNativeScriptFactory.class);

    }

    public static class MyNativeScriptFactory implements NativeScriptFactory {

        @Override
        public ExecutableScript newScript(@Nullable Map<String, Object> params) {
            return new MyNativeScript(params);
        }

        @Override
        public boolean needsScores() {
            return false;
        }
    }

    public static class MyNativeScript extends AbstractSearchScript {
        Map<String, Object> params;

        MyNativeScript(Map<String, Object> params) {
            this.params = params;
        }

        @Override
        public Object run() {
            ScriptDocValues<?> docValue = (ScriptDocValues<?>) doc().get(params.get("key"));
            if (docValue instanceof Strings) {
                return ((String) params.get("value")).equalsIgnoreCase(((Strings) docValue).getValue());
            }
            return false;
        }
    }
}

Example Query Using Native Script:

{
    "query" : {
        "bool" : {

            "must" : [{
                    "query_string" : {
                        "query" : "\"apache\"",
                        "default_field" : "COLLECTOR_NAME"
                    }
                }, {
                    "script" : {
                        "script" : "my_script",
                        "lang" : "native",
                        "params" : {
                            "key" : "verb",
                            "value" : "GET"
                        }
                    }
                }
            ]

        }
    }
}

Upvotes: 1

Ryan Chou
Ryan Chou

Reputation: 1132

To this scenarios, I suggest that you could combine lowercase filter and keyword tokenizer into your custom analyzer. And lowercase your search-input keywords.

1.Create index with the analyzer combined with lowercase filter and keyword tokenizer

curl -XPUT localhost:9200/test/ -d '
{
  "settings":{
     "index":{
        "analysis":{
           "analyzer":{
              "your_custom_analyzer":{
                 "tokenizer":"keyword",
                 "filter": ["lowercase"]
              }
           }
        }
    }
}'

2.Put mappings and set the field properties with the analyzer

curl -XPUT localhost:9200/test/_mappings/twitter -d '
{
    "twitter": {
        "properties": {
            "content": {"type": "string", "analyzer": "your_custom_analyzer" }
        }
    }
}'

3.You could search what you want in wildcard query.

curl -XPOST localhost:9200/test/twitter/ -d '{

    "query": {
        "wildcard": {"content": "**the words you want to search**"}
    }  
}'

Another way for search a filed in different way. I offser a suggestion for U was that using the multi_fields type.

You could set the field in multi_field

curl -XPUT localhost:9200/test/_mapping/twitter -d '
{
    "properties": {
        "content": {
            "type": "multi_field",
            "fields": {
                "default": {"type": "string"},
                "search": {"type": "string", "analyzer": "your_custom_analyzer"}
            }
        }
    }
}'

So you could index data with above mappings properties. and finally search it in two way (default/your_custom_analyzer)

Upvotes: 3

Mike S.
Mike S.

Reputation: 4879

I believe this Gist answers your question best: * https://gist.github.com/mtyaka/2006966

You can index a field several times during mapping and we do this all the time where one is not_analyzed and another is. We typically set the not_analyzed version to .raw

Like John P. wrote, you can set up analyzer during runtime, or you can set one up in the config at server start like in link above:

# Register the custom 'lowercase_keyword' analyzer. It doesn't do anything else
# other than changing everything to lower case.
index.analysis.analyzer.lowercase_keyword.type: custom
index.analysis.analyzer.lowercase_keyword.tokenizer: keyword
index.analysis.analyzer.lowercase_keyword.filter: [lowercase]

Then you define your mapping for your field(s) with both the not_analyzed version and the analyzed one:

# Map the 'tags' property to two fields: one that isn't analyzed,
# and one that is analyzed with the 'lowercase_keyword' analyzer.
curl -XPUT 'http://localhost:9200/myindex/images/_mapping' -d '{
  "images": {
    "properties": {
      "tags": {
        "type": "multi_field",
        "fields": {
          "tags": {
            "index": "not_analyzed",
            "type": "string"
          },
          "lowercased": {
            "index": "analyzed",
            "analyzer": "lowercase_keyword",
            "type": "string"
          }
        }
      }
    }
  }
}'

And finally your query (note lowercased values before building query to help find match):

# Issue queries against the index. The search query must be manually lowercased.
curl -XPOST 'http://localhost:9200/myindex/images/_search?pretty=true' -d '{
  "query": {
    "terms": {
      "tags.lowercased": [
        "event:battle at the boardwalk"
      ]
    }
  },
  "facets": {
    "tags": {
      "terms": {
        "field": "tags",
        "size": "500",
        "regex": "^team:.*"
      }
    }
  }
}'

Upvotes: 4

MuchMore
MuchMore

Reputation: 168

If you want case insensitive queries ONLY, consider changing both your data AND your query to either of lower/upper case before you go about doing your business.

That would mean you keep your field not_analyzed and enter data/query in only one of the cases.

Upvotes: 6

wuzer
wuzer

Reputation: 97

I wish I could add a comment, but I can't. So the answer to this question is "this is not possible".

Analyzers are composed of a single Tokenizer and zero or more TokenFilters.

I wish I could tell you something else, but spending 4 hours researching, that's the answer. I'm in the same situation. You can't skip tokenization. It's either all on or all off.

Upvotes: -1

John Petrone
John Petrone

Reputation: 27487

I think this example meets your needs:

$ curl -XPUT localhost:9200/testindex/ -d '
{
  "settings":{
     "index":{
        "analysis":{
           "analyzer":{
              "analyzer_keyword":{
                 "tokenizer":"keyword",
                 "filter":"lowercase"
              }
           }
        }
     }
  },
  "mappings":{
     "test":{
        "properties":{
           "title":{
              "analyzer":"analyzer_keyword",
              "type":"string"
           }
        }
     }
  }
}'

taken from here: How to setup a tokenizer in elasticsearch

it uses both the keyword tokenizer and the lowercase filter on a string field which I believe does what you want.

Upvotes: 38

Alex
Alex

Reputation: 1210

just create your custom analyzer with keyword tokenizer and lowercase token filter.

Upvotes: 3

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