rewrite parameter

Elasticsearch uses Apache Lucene internally to power indexing and searching. In their original form, Lucene cannot execute the following queries:

• fuzzy
• prefix
• query_string
• regexp
• wildcard

To execute them, Lucene changes these queries to a simpler form, such as a bool query or a bit set.

The rewrite parameter determines:

• How Lucene calculates the relevance scores for each matching document
• Whether Lucene changes the original query to a bool query or bit set
• If changed to a bool query, which term query clauses are included

constant_score_blended (Default)

Assigns each document a relevance score equal to the boost parameter.

This method maintains a bool query like implementation over the most costly terms while pre-processing the less costly terms into a filter bitset.

This method can cause the generated bool query to exceed the clause limit in the indices.query.bool.max_clause_count setting. If the query exceeds this limit, Elasticsearch returns an error.

constant_score

Uses the constant_score_boolean method for fewer matching terms. Otherwise, this method finds all matching terms in sequence and returns matching documents using a bit set.

constant_score_boolean

Assigns each document a relevance score equal to the boost parameter.

This method changes the original query to a bool query. This bool query contains a should clause and term query for each matching term.

This method can cause the final bool query to exceed the clause limit in the indices.query.bool.max_clause_count setting. If the query exceeds this limit, Elasticsearch returns an error.

scoring_boolean

Calculates a relevance score for each matching document.

This method changes the original query to a bool query. This bool query contains a should clause and term query for each matching term.

This method can cause the final bool query to exceed the clause limit in the indices.query.bool.max_clause_count setting. If the query exceeds this limit, Elasticsearch returns an error.

top_terms_blended_freqs_N

Calculates a relevance score for each matching document as if all terms had the same frequency. This frequency is the maximum frequency of all matching terms.

This method changes the original query to a bool query. This bool query contains a should clause and term query for each matching term.

The final bool query only includes term queries for the top N scoring terms.

You can use this method to avoid exceeding the clause limit in the indices.query.bool.max_clause_count setting.

top_terms_boost_N

Assigns each matching document a relevance score equal to the boost parameter.

This method changes the original query to a bool query. This bool query contains a should clause and term query for each matching term.

The final bool query only includes term queries for the top N terms.

You can use this method to avoid exceeding the clause limit in the indices.query.bool.max_clause_count setting.

top_terms_N

Calculates a relevance score for each matching document.

This method changes the original query to a bool query. This bool query contains a should clause and term query for each matching term.

The final bool query only includes term queries for the top N scoring terms.

You can use this method to avoid exceeding the clause limit in the indices.query.bool.max_clause_count setting.

For most uses, we recommend using the constant_score_blended, constant_score, constant_score_boolean, or top_terms_boost_N rewrite methods.

Other methods calculate relevance scores. These score calculations are often expensive and do not improve query results.