71 lines
1.9 KiB
Plaintext
71 lines
1.9 KiB
Plaintext
[[term-vector]]
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=== `term_vector`
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Term vectors contain information about the terms produced by the
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<<analysis,analysis>> process, including:
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* a list of terms.
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* the position (or order) of each term.
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* the start and end character offsets mapping the term to its
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origin in the original string.
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* payloads (if they are available) — user-defined binary data
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associated with each term position.
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These term vectors can be stored so that they can be retrieved for a
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particular document.
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The `term_vector` setting accepts:
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[horizontal]
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`no`:: No term vectors are stored. (default)
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`yes`:: Just the terms in the field are stored.
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`with_positions`:: Terms and positions are stored.
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`with_offsets`:: Terms and character offsets are stored.
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`with_positions_offsets`:: Terms, positions, and character offsets are stored.
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`with_positions_payloads`:: Terms, positions, and payloads are stored.
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`with_positions_offsets_payloads`:: Terms, positions, offsets and payloads are stored.
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The fast vector highlighter requires `with_positions_offsets`.
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<<docs-termvectors, The term vectors API>> can retrieve whatever is stored.
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WARNING: Setting `with_positions_offsets` will double the size of a field's
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index.
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[source,console]
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--------------------------------------------------
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PUT my-index-000001
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{
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"mappings": {
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"properties": {
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"text": {
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"type": "text",
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"term_vector": "with_positions_offsets"
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}
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}
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}
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}
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PUT my-index-000001/_doc/1
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{
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"text": "Quick brown fox"
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}
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GET my-index-000001/_search
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{
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"query": {
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"match": {
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"text": "brown fox"
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}
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},
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"highlight": {
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"fields": {
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"text": {} <1>
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}
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}
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}
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--------------------------------------------------
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<1> The fast vector highlighter will be used by default for the `text` field
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because term vectors are enabled.
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