anchor.diff:  // CONSOLE
   // TEST[setup:twitter]
   
  -Using the fast vector highlighter there can be more tags, and the "importance"
  -is ordered.
  +When using the fast vector highlighter, you can specify additional tags and the
  +"importance" is ordered.
   
   [source,js]
   --------------------------------------------------
  
positive.code: --------------------------------------------------
  // CONSOLE
  
  [[plain-highlighter]]
  ==== Plain highlighter
  
  This highlighter of type `plain` uses the standard Lucene highlighter.
  It tries hard to reflect the query matching logic in terms of understanding word importance and any word positioning criteria in phrase queries.
  
  [WARNING]
  If you want to highlight a lot of fields in a lot of documents with complex queries this highlighter will not be fast.
  In its efforts to accurately reflect query logic it creates a tiny in-memory index and re-runs the original query criteria through
  Lucene's query execution planner to get access to low-level match information on the current document.
  This is repeated for every field and every document that needs highlighting. If this presents a performance issue in your system consider using an alternative highlighter.
  
  [[fast-vector-highlighter]]
  ==== Fast vector highlighter
  
  This highlighter of type `fvh` uses the Lucene Fast Vector highlighter.
  This highlighter can be used on fields with `term_vector` set to
  `with_positions_offsets` in the mapping.
  The fast vector highlighter:
  
  * Is faster especially for large fields (> `1MB`)
  * Can be customized with `boundary_scanner` (see <<boundary-scanners,below>>)
  * Requires setting `term_vector` to `with_positions_offsets` which
    increases the size of the index
  * Can combine matches from multiple fields into one result.  See
    `matched_fields`
  * Can assign different weights to matches at different positions allowing
    for things like phrase matches being sorted above term matches when
    highlighting a Boosting Query that boosts phrase matches over term matches
  
  Here is an example of setting the `comment` field to allow for
  highlighting using the fast vector highlighter on it (this will cause
  the index to be bigger):
  
  [source,js]
  --------------------------------------------------
  PUT /example
  {
    "mappings": {
      "doc" : {
        "properties": {
          "comment" : {
            "type": "text",
            "term_vector" : "with_positions_offsets"
          }
        }
      }
    }
  }
  --------------------------------------------------
  // CONSOLE
  
  ==== Force highlighter type
  
  The `type` field allows to force a specific highlighter type.
  The allowed values are: `unified`, `plain` and `fvh`.
  
negative.code: [[search-request-highlighting]]
  === Highlighting
  
  Highlighters enable you to get highlighted snippets from one or more fields
  in your search results so you can show users where the query matches are.
  When you request highlights, the response contains an additional `highlight`
  element for each search hit that includes the highlighted fields and the
  highlighted fragments.
  
  Highlighting requires the actual content of a field. If the field is not
  stored (the mapping does not set `store` to `true`), the actual `_source` is
  loaded and the relevant field is extracted from `_source`.
  
  NOTE: The `_all` field cannot be extracted from `_source`, so it can only
  be used for highlighting if it is explicitly stored.
  
  For example, to get highlights for the `content` field in each search hit
  using the default highlighter, include a `highlight` object in
  the request body that specifies the `content` field:
  
  [source,js]
  --------------------------------------------------
  