A fuzzy query is a query type in Elasticsearch that is used to search for documents that contain terms that are similar to a specified term, based on a fuzzy matching algorithm. The fuzzy query is often used for searching fields that contain text that may contain typographical errors or variations.
When a fuzzy query is executed, Elasticsearch searches the inverted index for terms that are similar to the specified term, based on a fuzzy matching algorithm. It returns any documents that contain a term that matches the specified term within a certain degree of similarity.
The degree of similarity is determined by the `fuzziness` parameter, which specifies the maximum number of changes allowed between the searched term and the matched terms. The `fuzziness` parameter can be a number or a string, such as “AUTO”, which uses a heuristic algorithm to determine the most appropriate fuzziness value based on the length of the term being searched.
Here’s an example of a fuzzy query in Elasticsearch:
GET /my_index/_search
{
"query": {
"fuzzy": {
"title": {
"value": "elastiksearch",
"fuzziness": "AUTO"
}
}
}
}
In this example, we are searching the `title` field in the `my_index` index for terms that are similar to the term “elastiksearch”, based on a fuzzy matching algorithm. The fuzzy query will return any documents that contain a term in the `title` field that matches the specified term within a certain degree of similarity.
The fuzzy query can also be used in combination with other query types, such as the bool query, to construct more complex search queries. By allowing for searching for terms that are similar to a specified term, based on a fuzzy matching algorithm, the fuzzy query provides a powerful and flexible way to search for text in Elasticsearch.