ArangoDB v3.13 is under development and not released yet. This documentation is not final and potentially incomplete.

Search highlighting with ArangoSearch

You can retrieve the positions of matches within strings when querying Views with ArangoSearch, to highlight what was found in search results

ArangoDB Enterprise Edition ArangoGraph

ArangoSearch lets you search for terms and phrases in full-text, and more. It only returns matching documents, however. With search highlighting, you can get the exact locations of the matches.

A common use case is to emphasize the matching parts in client applications, for example, with a background color or an underline, so that users can easily see and understand the matches.

How to use search highlighting

To use search highlighting, you need to index the respective attributes with Analyzers that have the offset feature enabled. The built-in text Analyzers don’t have this feature enabled, you need to create custom Analyzers.

You can get the substring offsets of matches by calling the OFFSET_INFO() function in search queries. It takes the document emitted by the View (FOR doc IN viewName) and a list of paths like "field.nested" or "array[0].field", defining for what attributes or array elements you want to retrieve the offsets for. For every path, it returns a list comprised of a name and offsets.

The name is the path of the value, but in a different form than you passed to the function, like ["field", "nested"] or ["array", 0, "field"]. You can look up the value with the VALUE() function using this path description.

The offsets are a list of offset pairs, one for every match. Each pair is an array with two numbers, with the start offset and length of the match. There can be multiple matches per path. You can optionally cap how many matches are collected per path by setting limits when calling the OFFSET_INFO() function.

The start offsets and lengths describe the positions in bytes, not characters. You may need to account for characters encoded using multiple bytes.

Term and phrase search with highlighting

Dataset

A collection called food with the following documents:

{ "name": "avocado", "description": { "en": "The avocado is a medium-sized, evergreen tree, native to the Americas." } }
{ "name": "carrot", "description": { "en": "The carrot is a root vegetable, typically orange in color, native to Europe and Southwestern Asia." } }
{ "name": "chili pepper", "description": { "en": "Chili peppers are varieties of the berry-fruit of plants from the genus Capsicum, cultivated for their pungency." } }
{ "name": "tomato", "description": { "en": "The tomato is the edible berry of the tomato plant." } }

Custom Analyzer

If you want to use an arangosearch View, create a text Analyzer in arangosh to tokenize text, like the built-in text_en Analyzer, but additionally set the offset feature, enabling search highlighting:

var analyzers = require("@arangodb/analyzers");
analyzers.save("text_en_offset", "text", { locale: "en", stopwords: [] }, ["frequency", "position", "offset"]);
Show output

The frequency, position, and offset Analyzer features are set because the examples on this page require them for the OFFSET_INFO() search highlighting function to work, and the PHRASE() filter function also requires the former two.

You can skip this step if you want to use a search-alias View, because the Analyzer features can be overwritten in the inverted index definition.

View definition

db.food.ensureIndex({
  name: "inv-text-offset",
  type: "inverted",
  fields: [
    { name: "description.en", analyzer: "text_en", features: ["frequency", "position", "offset"] }
  ]
});

db._createView("food_view", "search-alias", { indexes: [ { collection: "food", index: "inv-text-offset" } ] });
{
  "links": {
    "food": {
      "fields": {
        "description": {
          "fields": {
            "en": {
              "analyzers": [
                "text_en_offset"
              ]
            }
          }
        }
      }
    }
  }
}

AQL queries

Search the View for descriptions that contain the tokens avocado or tomato, the phrase cultivated ... pungency with two arbitrary tokens between the two words, and for words that start with cap. Get the matching positions, and use this information to extract the substrings with the SUBSTRING_BYTES() function.

The OFFSET_INFO() function returns a name that describes the path of the attribute or array element with the match. You can use the VALUE() function to dynamically get the respective value.

var coll = db._create("food");
var docs = db.food.save([
  { name: "avocado", description: { en: "The avocado is a medium-sized, evergreen tree, native to the Americas." } },
  { name: "carrot", description: { en: "The carrot is a root vegetable, typically orange in color, native to Europe and Southwestern Asia." } },
  { name: "chili pepper", description: { en: "Chili peppers are varieties of the berry-fruit of plants from the genus Capsicum, cultivated for their pungency." } },
  { name: "tomato", description: { en: "The tomato is the edible berry of the tomato plant." } }
]);
var idx = db.food.ensureIndex({ name: "inv-text-offset", type: "inverted", fields: [ { name: "description.en", analyzer: "text_en", features: ["frequency", "position", "offset"] } ] });
var view = db._createView("food_view", "search-alias", { indexes: [ { collection: "food", index: "inv-text-offset" } ] });
db._query(`FOR doc IN food_view
  SEARCH
    TOKENS("avocado tomato", "text_en") ANY == doc.description.en OR
    PHRASE(doc.description.en, "cultivated", 2, "pungency") OR
    STARTS_WITH(doc.description.en, "cap")
  FOR offsetInfo IN OFFSET_INFO(doc, ["description.en"])
    RETURN {
      description: doc.description,
      name: offsetInfo.name,
      matches: offsetInfo.offsets[* RETURN {
        offset: CURRENT,
        match: SUBSTRING_BYTES(VALUE(doc, offsetInfo.name), CURRENT[0], CURRENT[1])
      }]
    }`).toArray();
Show output

var coll = db._create("food");
var docs = db.food.save([
  { name: "avocado", description: { en: "The avocado is a medium-sized, evergreen tree, native to the Americas." } },
  { name: "carrot", description: { en: "The carrot is a root vegetable, typically orange in color, native to Europe and Southwestern Asia." } },
  { name: "chili pepper", description: { en: "Chili peppers are varieties of the berry-fruit of plants from the genus Capsicum, cultivated for their pungency." } },
  { name: "tomato", description: { en: "The tomato is the edible berry of the tomato plant." } }
]);
var analyzers = require("@arangodb/analyzers");
var analyzer = analyzers.save("text_en_offset", "text", { locale: "en", stopwords: [] }, ["frequency", "position", "offset"]);
var view = db._createView("food_view", "arangosearch", { links: { food: { fields: { description: { fields: { en: { analyzers: ["text_en_offset"] } } } } } } });
db._query(`FOR doc IN food_view
  SEARCH ANALYZER(
    TOKENS("avocado tomato", "text_en_offset") ANY == doc.description.en OR
    PHRASE(doc.description.en, "cultivated", 2, "pungency") OR
    STARTS_WITH(doc.description.en, "cap")
  , "text_en_offset")
  FOR offsetInfo IN OFFSET_INFO(doc, ["description.en"])
    RETURN {
      description: doc.description,
      name: offsetInfo.name,
      matches: offsetInfo.offsets[* RETURN {
        offset: CURRENT,
        match: SUBSTRING_BYTES(VALUE(doc, offsetInfo.name), CURRENT[0], CURRENT[1])
      }]
    }`).toArray();
Show output