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.
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": {}
}
}
}
- The fast vector highlighter will be used by default for the
text
field because term vectors are enabled.