ArangoDB v3.13 is under development and not released yet. This documentation is not final and potentially incomplete.
Vertex-Centric Indexes
You can create indexes over the _from
or _to
attribute and one or more additional edge attributes to improve certain graph traversals
All edge collections in ArangoDB have a special edge index that enables fast
graph operations. If you have graphs that contain supernodes (vertices that have
an exceptionally high amount of connected edges) and you apply filters in graph
traversal queries, you can create so-called vertex-centric indexes that can
perform better than the default edge indexes. You can use the persistent
and
mdi-prefixed
index types for this purpose.
Motivation
The idea of a vertex-centric index is to index a combination of a vertex, the
direction, and an arbitrary set of attributes on the edges. This can be achieved
by indexing the _from
or _to
attribute of an edge as the first field,
which contains the document identifier of a vertex and implicitly captures the
direction, followed by any number of other attributes of an edge.
To support traversals in OUTBOUND
direction, you need to index the _from
attribute as the first attribute. For the INBOUND
direction, you need to use
the _to
attribute. To support both (ANY
or mixed INBOUND
and OUTBOUND
directions), you need to create two indexes, using _from
in one and _to
in
the other as the first attribute the index is over.
For example, if you have an attribute called type
on the edges and traverse
in OUTBOUND
direction, you can create a vertex-centric persistent
index over
["_from", "type"]
to find all edges attached to a vertex with a given type
.
The following query can benefit from such an index:
FOR v, e, p IN 3..5 OUTBOUND @start GRAPH @graphName
FILTER p.edges[*].type ALL == "friend"
RETURN v
Using the built-in edge-index, ArangoDB can find the list of all edges attached
to the vertex fast but it still it has to walk through this list and check if
all of them have the attribute type == "friend"
. A vertex-centric index allows
ArangoDB to find all edges with the attribute type == "friend"
for the vertex
in one go, saving the iteration to verify the condition.
If you have numeric attributes on edges and want to filter by them using value
ranges, perhaps in addition to filtering by a type
using an equality check,
you can create a vertex-centric mdi-prefixed
index. Assuming the numeric
attributes are called x
and y
, a possible query could look like this:
FOR v, e, p in 0..3 INBOUND @start GRAPH @graphName
OPTIONS { order: "bfs", uniqueVertices: "path" }
FILTER p.edges[*].type ALL == "friend"
AND p.edges[*].x ALL >= 5
AND p.edges[*].y ALL <= 7
RETURN p
Index creation
A vertex-centric has to be of the type Persistent Index
or prefixed Multi-dimensional index
and is created like any other index of the respective type. However, in the list
of fields used to create the index over, you need to use either _from
or _to
as the first field.
For example, if you want to create a vertex-centric index on the type
attribute
that supports traversing in the OUTBOUND
direction, you would create the index
in the following way:
db.edgeCollection.ensureIndex({ type: "persistent", fields: [ "_from", "type" ] });
If you want to create a vertex-centric index on multi-dimensional data in the
x
and y
attributes with a type
attribute as prefix and support traversing
in the INBOUND
direction, you would create an index as follows:
db.edgeCollection.ensureIndex({
type: "mdi-prefixed",
prefixFields: ["_to", "type"],
fields: [ "x", "y" ],
fieldValueTypes: "double"
});
All options that are supported by persistent or multi-dimensional indexes are supported by the vertex-centric index as well.
Index usage
The AQL optimizer can decide to use a vertex-centric whenever suitable. However, it is not guaranteed that this index is used. The optimizer may estimate that another index, in particular the built-in edge index, is a better fit.
The optimizer considers vertex-centric indexes in pattern matching queries:
FOR v, e, p IN 3..5 OUTBOUND @start GRAPH @graphName
FILTER p.edges[*].type ALL == "friend"
RETURN v
It also considers them when you iterate over an edge collection directly and
explicitly filter on _from
respectively _to
and the other indexed attributes:
FOR edge IN edgeCollection
FILTER edge._from == "vertices/123456" AND edge.type == "friend"
RETURN edge