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.
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"]);
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();
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();