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

This documentation is not final and potentially incomplete.

Index Utilization

In most cases ArangoDB will use a single index per collection in a given query. AQL queries can use more than one index per collection when multiple FILTER conditions are combined with a logical OR and these can be covered by indexes. AQL queries will use a single index per collection when FILTER conditions are combined with logical AND.

Creating multiple indexes on different attributes of the same collection may give the query optimizer more choices when picking an index. Creating multiple indexes on different attributes can also help in speeding up different queries, with FILTER conditions on different attributes.

It is often beneficial to create an index on more than just one attribute. By adding more attributes to an index, an index can become more selective and thus reduce the number of documents that queries need to process.

ArangoDB’s primary indexes, edges indexes and hash indexes will automatically provide selectivity estimates. Index selectivity estimates are provided in the web interface, the indexes() return value and in the explain() output for a given query.

The more selective an index is, the more documents it will filter on average. The index selectivity estimates are therefore used by the optimizer when creating query execution plans when there are multiple indexes the optimizer can choose from. The optimizer will then select a combination of indexes with the lowest estimated total cost. In general, the optimizer will pick the indexes with the highest estimated selectivity.

Sparse indexes may or may not be picked by the optimizer in a query. As sparse indexes do not contain null values, they will not be used for queries if the optimizer cannot safely determine whether a FILTER condition includes null values for the index attributes. The optimizer policy is to produce correct results, regardless of whether or which index is used to satisfy FILTER conditions. If it is unsure about whether using an index will violate the policy, it will not make use of the index.

Troubleshooting

When in doubt about whether and which indexes will be used for executing a given AQL query, click the Explain button in the web interface in the Queries view or use the explain() method for the statement as follows (from the ArangoShell):

var query = "FOR doc IN collection FILTER doc.value > 42 RETURN doc";
var stmt = db._createStatement(query);
stmt.explain();

The explain() command will return a detailed JSON representation of the query’s execution plan. The JSON explain output is intended to be used programmatically. To get a human-readable and much more compact explanation of the query, there use db._explain(query):

var query = "FOR doc IN collection FILTER doc.value > 42 RETURN doc";
db._explain(query);

If any of the explain methods shows that a query is not using indexes, the following steps may help:

  • check if the attribute names in the query are correctly spelled. In a schema-free database, documents in the same collection can have varying structures. There is no such thing as a non-existing attribute error. A query that refers to attribute names not present in any of the documents will not return an error, and obviously will not benefit from indexes.

  • check the return value of the indexes() method for the collections used in the query and validate that indexes are actually present on the attributes used in the query’s filter conditions.

  • if indexes are present but not used by the query, the query’s FILTER condition may not be adequate: an index will be used only for comparison operators ==, <, <=, >, >= and IN.

  • using indexed attributes as function parameters or in arbitrary expressions will likely lead to the index on the attribute not being used. For example, the following queries will not use an index on value:

    FOR doc IN collection FILTER TO_NUMBER(doc.value) == 42 RETURN doc
    FOR doc IN collection FILTER doc.value - 1 == 42 RETURN doc
    

    In these cases the queries should be rewritten so that only the index attribute is present on one side of the operator, or additional filters and indexes should be used to restrict the amount of documents otherwise.

  • certain AQL functions such as WITHIN() or FULLTEXT() do utilize indexes internally, but their use is not mentioned in the query explanation for functions in general. These functions will raise query errors (at runtime) if no suitable index is present for the collection in question.

  • the query optimizer will generally pick one index per collection in a query. It can pick more than one index per collection if the FILTER condition contains multiple branches combined with logical OR. For example, the following queries can use indexes:

    FOR doc IN collection FILTER doc.value1 == 42 || doc.value1 == 23 RETURN doc
    FOR doc IN collection FILTER doc.value1 == 42 || doc.value2 == 23 RETURN doc
    FOR doc IN collection FILTER doc.value1 < 42 || doc.value2 > 23 RETURN doc
    

    The two ORs in the first query will be converted to an IN lookup, and if there is a suitable index on value1, it will be used. The second query requires two separate indexes on value1 and value2 and will use them if present. The third query can use the indexes on value1 and value2 when they are sorted.

  • for indexes on multiple attributes (combined indexes), the index attribute order is also important. For example, when creating an index on ["value1", "value2"] (in this order), the index can be used to satisfy the following FILTER conditions:

    FILTER doc.value1 == ...
    FILTER doc.value1 > ...
    FILTER doc.value1 >= ...
    FILTER doc.value1 < ...
    FILTER doc.value1 <= ...
    FILTER doc.value1 > ... && doc.value1 < ...
    FILTER doc.value1 >= ... && doc.value1 < ...
    FILTER doc.value1 > ... && doc.value1 <= ...
    FILTER doc.value1 >= ... && doc.value1 <= ...
    FILTER doc.value1 IN ...
    
    FILTER doc.value1 == ... && doc.value2 == ...
    FILTER doc.value1 == ... && doc.value2 > ...
    FILTER doc.value1 == ... && doc.value2 >= ...
    FILTER doc.value1 == ... && doc.value2 < ...
    FILTER doc.value1 == ... && doc.value2 <= ...
    FILTER doc.value1 == ... && doc.value2 > ... && doc.value2 < ...
    FILTER doc.value1 == ... && doc.value2 >= ... && doc.value2 < ...
    FILTER doc.value1 == ... && doc.value2 > ... && doc.value2 <= ...
    FILTER doc.value1 == ... && doc.value2 >= ... && doc.value2 <= ...
    FILTER doc.value1 == ... && doc.value2 IN ...
    

    The index cannot be used to satisfy FILTER conditions on value2 alone.

    For a combined index to be used in a query, the following algorithm is applied:

    • the index attributes are checked in order, from left to right (e.g. value1, value2).
    • if there is a FILTER condition on an index attribute, the index is considered a valid candidate for the query.
    • if the FILTER condition on the current attribute does not use == or IN, the following index attributes are not considered anymore. Otherwise, they will be considered and the algorithm will check the next index attribute.