280 lines
8.7 KiB
Plaintext
280 lines
8.7 KiB
Plaintext
[[search-request-highlighting]]
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=== Highlighting
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Allows to highlight search results on one or more fields. The
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implementation uses either the lucene `fast-vector-highlighter` or
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`highlighter`. The search request body:
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[source,js]
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--------------------------------------------------
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{
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"query" : {...},
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"highlight" : {
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"fields" : {
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"content" : {}
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}
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}
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}
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--------------------------------------------------
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In the above case, the `content` field will be highlighted for each
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search hit (there will be another element in each search hit, called
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`highlight`, which includes the highlighted fields and the highlighted
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fragments).
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In order to perform highlighting, the actual content of the field is
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required. If the field in question is stored (has `store` set to `yes`
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in the mapping), it will be used, otherwise, the actual `_source` will
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be loaded and the relevant field will be extracted from it.
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If `term_vector` information is provided by setting `term_vector` to
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`with_positions_offsets` in the mapping then the fast vector
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highlighter will be used instead of the plain highlighter. The fast vector highlighter:
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* Is faster especially for large fields (> `1MB`)
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* Can be customized with `boundary_chars`, `boundary_max_scan`, and
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`fragment_offset` (see below)
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* Requires setting `term_vector` to `with_positions_offsets` which
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increases the size of the index
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Here is an example of setting the `content` field to allow for
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highlighting using the fast vector highlighter on it (this will cause
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the index to be bigger):
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[source,js]
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--------------------------------------------------
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{
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"type_name" : {
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"content" : {"term_vector" : "with_positions_offsets"}
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}
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}
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--------------------------------------------------
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The field name supports wildcard notation, for example,
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using `comment_*` which will cause all fields that match the expression
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to be highlighted.
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[[tags]]
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==== Highlighting Tags
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By default, the highlighting will wrap highlighted text in `<em>` and
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`</em>`. This can be controlled by setting `pre_tags` and `post_tags`,
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for example:
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[source,js]
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--------------------------------------------------
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{
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"query" : {...},
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"highlight" : {
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"pre_tags" : ["<tag1>", "<tag2>"],
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"post_tags" : ["</tag1>", "</tag2>"],
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"fields" : {
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"_all" : {}
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}
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}
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}
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--------------------------------------------------
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There can be a single tag or more, and the "importance" is ordered.
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There are also built in "tag" schemas, with currently a single schema
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called `styled` with `pre_tags` of:
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[source,js]
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--------------------------------------------------
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<em class="hlt1">, <em class="hlt2">, <em class="hlt3">,
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<em class="hlt4">, <em class="hlt5">, <em class="hlt6">,
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<em class="hlt7">, <em class="hlt8">, <em class="hlt9">,
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<em class="hlt10">
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--------------------------------------------------
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And post tag of `</em>`. If you think of more nice to have built in tag
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schemas, just send an email to the mailing list or open an issue. Here
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is an example of switching tag schemas:
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[source,js]
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--------------------------------------------------
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{
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"query" : {...},
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"highlight" : {
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"tags_schema" : "styled",
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"fields" : {
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"content" : {}
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}
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}
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}
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--------------------------------------------------
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An `encoder` parameter can be used to define how highlighted text will
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be encoded. It can be either `default` (no encoding) or `html` (will
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escape html, if you use html highlighting tags).
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==== Highlighted Fragments
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Each field highlighted can control the size of the highlighted fragment
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in characters (defaults to `100`), and the maximum number of fragments
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to return (defaults to `5`). For example:
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[source,js]
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--------------------------------------------------
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{
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"query" : {...},
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"highlight" : {
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"fields" : {
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"content" : {"fragment_size" : 150, "number_of_fragments" : 3}
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}
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}
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}
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--------------------------------------------------
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On top of this it is possible to specify that highlighted fragments are
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order by score:
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[source,js]
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--------------------------------------------------
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{
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"query" : {...},
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"highlight" : {
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"order" : "score",
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"fields" : {
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"content" : {"fragment_size" : 150, "number_of_fragments" : 3}
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}
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}
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}
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--------------------------------------------------
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It is also possible to highlight against a query other than the search
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query by setting `highlight_query`. This is especially useful if you
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use a rescore query because those are not taken into account by
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highlighting by default. Elasticsearch does not validate that
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`highlight_query` contains the search query in any way so it is possible
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to define it so legitimate query results aren't highlighted at all.
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Generally it is better to include the search query in the
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`highlight_query`. Here is an example of including both the search
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query and the rescore query in `highlight_query`.
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[source,js]
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--------------------------------------------------
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{
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"fields": [ "_id" ],
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"query" : {
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"match": {
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"content": {
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"query": "foo bar"
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}
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}
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},
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"rescore": {
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"window_size": 50,
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"query": {
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"rescore_query" : {
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"match_phrase": {
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"content": {
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"query": "foo bar",
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"phrase_slop": 1
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}
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}
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},
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"rescore_query_weight" : 10
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}
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},
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"highlight" : {
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"order" : "score",
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"fields" : {
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"content" : {
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"fragment_size" : 150,
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"number_of_fragments" : 3,
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"highlight_query": {
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"bool": {
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"must": {
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"match": {
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"content": {
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"query": "foo bar"
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}
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}
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},
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"should": {
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"match_phrase": {
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"content": {
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"query": "foo bar",
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"phrase_slop": 1,
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"boost": 10.0
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}
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}
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},
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"minimum_should_match": 0
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}
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}
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}
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}
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}
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}
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--------------------------------------------------
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Note the score of text fragment in this case is calculated by Lucene
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highlighting framework. For implementation details you can check
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`ScoreOrderFragmentsBuilder.java` class.
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If the `number_of_fragments` value is set to 0 then no fragments are
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produced, instead the whole content of the field is returned, and of
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course it is highlighted. This can be very handy if short texts (like
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document title or address) need to be highlighted but no fragmentation
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is required. Note that `fragment_size` is ignored in this case.
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[source,js]
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--------------------------------------------------
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{
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"query" : {...},
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"highlight" : {
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"fields" : {
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"_all" : {},
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"bio.title" : {"number_of_fragments" : 0}
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}
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}
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}
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--------------------------------------------------
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When using `fast-vector-highlighter` one can use `fragment_offset`
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parameter to control the margin to start highlighting from.
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[[highlighting-settings]]
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==== Global Settings
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Highlighting settings can be set on a global level and then overridden
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at the field level.
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[source,js]
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--------------------------------------------------
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{
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"query" : {...},
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"highlight" : {
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"number_of_fragments" : 3,
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"fragment_size" : 150,
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"tag_schema" : "styled",
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"fields" : {
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"_all" : { "pre_tags" : ["<em>"], "post_tags" : ["</em>"] },
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"bio.title" : { "number_of_fragments" : 0 },
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"bio.author" : { "number_of_fragments" : 0 },
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"bio.content" : { "number_of_fragments" : 5, "order" : "score" }
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}
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}
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}
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--------------------------------------------------
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[[field-match]]
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==== Require Field Match
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`require_field_match` can be set to `true` which will cause a field to
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be highlighted only if a query matched that field. `false` means that
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terms are highlighted on all requested fields regardless if the query
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matches specifically on them.
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[[boundary-characters]]
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==== Boundary Characters
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When highlighting a field that is mapped with term vectors,
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`boundary_chars` can be configured to define what constitutes a boundary
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for highlighting. It's a single string with each boundary character
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defined in it. It defaults to `.,!? \t\n`.
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The `boundary_max_scan` allows to control how far to look for boundary
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characters, and defaults to `20`.
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