Highlighting

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Highlighters enable you to retrieve the best-matching 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.

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:

				GET /_search
					{
  "query": {
    "match": { "content": "kimchy" }
  },
  "highlight": {
    "fields": {
      "content": {}
    }
  }
}
		

Elasticsearch supports three highlighters: unified, plain, and fvh (fast vector highlighter) for text and keyword fields and the semantic highlighter for semantic_text fields. You can specify the highlighter type you want to use for each field or rely on the field type’s default highlighter.

The unified highlighter uses the Lucene Unified Highlighter. This highlighter breaks the text into sentences and uses the BM25 algorithm to score individual sentences as if they were documents in the corpus. It also supports accurate phrase and multi-term (fuzzy, prefix, regex) highlighting. The unified highlighter can combine matches from multiple fields into one result (see matched_fields).

This is the default highlighter for all text and keyword fields.

The semantic highlighter is specifically designed for use with the semantic_text field. It identifies and extracts the most relevant fragments from the field based on semantic similarity between the query and each fragment.

By default, semantic_text fields use the semantic highlighter.

The plain highlighter uses the standard Lucene highlighter. It attempts to reflect the query matching logic in terms of understanding word importance and any word positioning criteria in phrase queries.

The fvh highlighter 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:

• Can be customized with a boundary_scanner.
• 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

To create meaningful search snippets from the terms being queried, the highlighter needs to know the start and end character offsets of each word in the original text. These offsets can be obtained from:

• The postings list. If index_options is set to offsets in the mapping, the unified highlighter uses this information to highlight documents without re-analyzing the text. It re-runs the original query directly on the postings and extracts the matching offsets from the index, limiting the collection to the highlighted documents. This is important if you have large fields because it doesn’t require reanalyzing the text to be highlighted. It also requires less disk space than using term_vectors.
• Term vectors. If term_vector information is provided by setting term_vector to with_positions_offsets in the mapping, the unified highlighter automatically uses the term_vector to highlight the field. It’s fast especially for large fields (> 1MB) and for highlighting multi-term queries like prefix or wildcard because it can access the dictionary of terms for each document. The fvh highlighter always uses term vectors.
• Plain highlighting. This mode is used by the unified when there is no other alternative. 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. The plain highlighter always uses plain highlighting.