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Imagine searching for a recipe and seeing 'chicken' highlighted exactly where it appears in the ingredients and steps. That's highlighting!

It visually emphasizes the matching terms in your search results, making it much easier for users to quickly scan and find relevant information.

• Improved User Experience: Users quickly spot why a document is relevant.
• Contextual Clues: Provides snippets of text around the match, giving context.
• Faster Information Retrieval: Reduces time spent reading irrelevant parts.

Adding basic highlighting to your Elasticsearch search is straightforward. You just need to include a highlight block in your search request.

This block specifies which fields you want to highlight. By default, Elasticsearch wraps the matching terms with <em> and </em> tags.

In the previous example, we told Elasticsearch to highlight matches found in the description field.

The highlight.fields object is where you list all the fields you want to apply highlighting to. For each field, you can provide an empty object {} for default behavior, or specify custom options.

Only fields that are indexed for full-text search (like text fields) can be highlighted effectively.

Often, you'll want to highlight matching terms across several fields within the same document, such as a product's title and its content.

Simply add more fields to the fields object in your highlight section. Elasticsearch will process each field independently.

The default <em> tags are fine, but you might want to use different HTML tags or CSS classes for styling your highlighted terms.

You can change these using the pre_tags and post_tags parameters within your highlight block. These parameters accept arrays of strings.

When a document is very long, you usually don't want to return the entire field with highlights. Instead, you want short, relevant snippets.

The fragment_size parameter controls the maximum length (in characters) of the highlighted fragments. Elasticsearch tries to break fragments at sentence boundaries or natural breaks.

You can also control the number of snippets returned per field using number_of_fragments. Set it to 0 to return the entire field content as a single fragment (if fragment_size is also 0).

What if there are no matches in a field, but you still want to see its content? Use no_match_size to specify the length of the fragment to return if no matches are found. By default, if there's no match, no fragment is returned for that field.

For even more precise control over how fragments are generated, you can use boundary_scanner, boundary_chars, and boundary_max_scan.

• boundary_scanner: Defines how fragments are split (e.g., sentence, word, chars).
• boundary_chars: Custom characters to use as fragment boundaries when boundary_scanner is chars.
• boundary_max_scan: How far to scan for boundary characters.

These are useful for languages without clear sentence structures or for specific content types.

Sometimes, your search query matches in one field (e.g., content), but you want to highlight the corresponding terms in another field (e.g., a shorter summary or title) for display.

The matched_fields parameter allows you to specify a list of fields that will be used to generate highlights for the current field. This is powerful for showing concise, highlighted snippets from a related, more prominent field.

You've learned how to bring your search results to life with highlighting! This powerful feature is crucial for improving user experience by visually emphasizing matching terms.

• We started with basic highlighting using the highlight block.
• You can specify fields to highlight and customize pre_tags/post_tags.
• fragment_size and number_of_fragments give you control over snippet length and count.
• Advanced options like boundary_scanner and matched_fields provide fine-grained control for complex scenarios.

Go forth and make your search results sparkle!