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term_vector

Term vectors contain information about the terms produced by the analysis process, including:

  • a list of terms.
  • the position (or order) of each term.
  • the start and end character offsets mapping the term to its origin in the original string.
  • payloads (if they are available) — user-defined binary data associated with each term position.

These term vectors can be stored so that they can be retrieved for a particular document.

Refer to the term vectors API examples page for usage examples.

The term_vector setting accepts:

no
No term vectors are stored. (default)
yes
Just the terms in the field are stored.
with_positions
Terms and positions are stored.
with_offsets
Terms and character offsets are stored.
with_positions_offsets
Terms, positions, and character offsets are stored.
with_positions_payloads
Terms, positions, and payloads are stored.
with_positions_offsets_payloads
Terms, positions, offsets and payloads are stored.

The fast vector highlighter requires with_positions_offsets. The term vectors API can retrieve whatever is stored.

Warning

Setting with_positions_offsets will double the size of a field’s index.

 PUT my-index-000001 { "mappings": { "properties": { "text": { "type": "text", "term_vector": "with_positions_offsets" } } } } PUT my-index-000001/_doc/1 { "text": "Quick brown fox" } GET my-index-000001/_search { "query": { "match": { "text": "brown fox" } }, "highlight": { "fields": { "text": {} } } }
  1. The fast vector highlighter will be used by default for the text field because term vectors are enabled.