ArangoDB v3.10 is under development and not released yet.

This documentation is not final and potentially incomplete.

Faceted Search with ArangoSearch

Combine aggregation with search queries to retrieve how often values occur overall

A popular method for filtering items in an online shop is to display product categories in a list, together with the number of items in each category. This way, users get an idea of how many items will be left after applying a certain filter before they actually enable it. This concept can be extended to any properties, also called facets.

To implement such a feature in ArangoDB, you can use a COLLECT operation to group and count how many documents share an attribute value. This is also possible with ArangoSearch Views by simply iterating over a View instead of a collection.

Dataset: IMDB movie dataset

View definition:

{
  "links": {
    "imdb_vertices": {
      "fields": {
        "genre": {
          "analyzers": [
            "identity"
          ]
        }
      }
    }
  }
}

AQL Queries:

Find out all genre values by grouping by the genre attribute and count the number of occurrences:

FOR doc IN imdb
  COLLECT genre = doc.genre WITH COUNT INTO count
  RETURN { genre, count }
genre count
null 51287
Action 2449
Adventure 312
Animation 426
British 1
Comedy 3188

The COLLECT operation is applied as a post-operation. In other words, it is not accelerated by the View index. On the other hand, the genre field does not need to be indexed for this query.

To look up a specific genre, the field needs to be indexed. The lookup itself utilizes the View index, but the COLLECT operation is still a post-operation:

FOR doc IN imdb
  SEARCH ANALYZER(doc.genre == "Action", "identity")
  COLLECT WITH COUNT INTO count
  RETURN count
[
  2690
]

For above query with a single, simple condition, there is an optimization you can enable that can accurately determine the count from index data faster than the standard COLLECT. Also see Count Approximation.

FOR doc IN imdb
  SEARCH ANALYZER(doc.genre == "Action", "identity")
  OPTIONS { countApproximate: "cost" }
  COLLECT WITH COUNT INTO count
  RETURN count

To apply this optimization to the faceted search paradigm over all genres, you can run and cache the following query that determines all unique genre values:

FOR doc IN imdb
  RETURN DISTINCT doc.genre

You may use the AQL query cache if the data does not change much, or you could execute above query periodically and store the result in a separate collection. The numbers will not be fully up to date in that case, but it is often an acceptable tradeoff for a faceted search.

You can then use the genre list to look up each genre and retrieve the count while utilizing the count approximation optimization:

LET genres = [ "Action", "Adventure", "Animation", /* ... */ ]
FOR genre IN genres
  LET count = FIRST(
    FOR doc IN imdb
      SEARCH ANALYZER(doc.genre == genre, "identity")
      OPTIONS { countApproximate: "cost" }
      COLLECT WITH COUNT INTO count
      RETURN count
  )
  RETURN { genre, count }