SmartGraphs

SmartGraphs are only available in the Enterprise Edition, also available as managed service.

This chapter describes the smart-graph module, which enables you to manage graphs at scale. It will give a vast performance benefit for all graphs sharded in an ArangoDB Cluster. On a single server this feature is pointless, hence it is only available in cluster mode.

In terms of querying there is no difference between SmartGraphs and General Graphs. The former is a transparent replacement for the latter. For graph querying please refer to AQL Graph Operations and General Graph Functions sections. The optimizer is clever enough to identify whether it is a SmartGraph or not.

The difference is only in the management section: creating and modifying the underlying collections of the graph. For a detailed API reference please refer to SmartGraph Management.

Do the hands-on ArangoDB SmartGraphs Tutorial to learn more.

What makes a graph smart?

Most graphs have one feature that divides the entire graph into several smaller subgraphs. These subgraphs have a large amount of edges that only connect vertices in the same subgraph and only have few edges connecting vertices from other subgraphs.

Examples for these graphs are:

  • Social Networks
    Typically the feature here is the region/country users live in. Every user typically has more contacts in the same region/country then she has in other regions/countries

  • Transport Systems
    For those also the feature is the region/country. You have many local transportation but only few across countries.

  • E-Commerce
    In this case probably the category of products is a good feature. Often products of the same category are bought together.

If this feature is known, SmartGraphs can make use if it.

When creating a SmartGraph you have to define a smartAttribute, which is the name of an attribute stored in every vertex. The graph will than be automatically sharded in such a way that all vertices with the same value are stored on the same physical machine, all edges connecting vertices with identical smartAttribute values are stored on this machine as well. During query time the query optimizer and the query executor both know for every document exactly where it is stored and can thereby minimize network overhead. Everything that can be computed locally will be computed locally.

Benefits of SmartGraphs

Because of the above described guaranteed sharding, the performance of queries that only cover one subgraph have a performance almost equal to an only local computation. Queries that cover more than one subgraph require some network overhead. The more subgraphs are touched the more network cost will apply. However the overall performance is never worse than the same query using a General Graph.

Getting started

First of all, SmartGraphs cannot use existing collections. When switching to SmartGraph from an existing dataset you have to import the data into a fresh SmartGraph. This switch can be easily achieved with arangodump and arangorestore. The only thing you have to change in this pipeline is that you create the new collections with the SmartGraph module before starting arangorestore.

Create a graph

In contrast to General Graphs we have to add more options when creating the graph. The two options smartGraphAttribute and numberOfShards are required and cannot be modified later.

arangosh> var graph_module = require("@arangodb/smart-graph");
arangosh> var graph = graph_module._create("myGraph", [], [], {smartGraphAttribute: "region", numberOfShards: 9});
arangosh> graph_module._graph("myGraph");
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{[SmartGraph] 
}
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Add vertex collections

This is analogous to General Graphs. Unlike with General Graphs, the collections must not exist when creating the SmartGraph. The SmartGraph module will create them for you automatically to set up the sharding for all these collections correctly. If you create collections via the SmartGraph module and remove them from the graph definition, then you may re-add them without trouble however, as they will have the correct sharding.

arangosh> graph._addVertexCollection("shop");
arangosh> graph._addVertexCollection("customer");
arangosh> graph._addVertexCollection("pet");
arangosh> graph_module._graph("myGraph");
Show execution results
{[SmartGraph] 
  "customer" : [ArangoCollection 2010167, "customer" (type document, status loaded)], 
  "pet" : [ArangoCollection 2010177, "pet" (type document, status loaded)], 
  "shop" : [ArangoCollection 2010157, "shop" (type document, status loaded)] 
}
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Define relations on the Graph

Adding edge collections works the same as with General Graphs, but again, the collections are created by the SmartGraph module to set up sharding correctly so they must not exist when creating the SmartGraph (unless they have the correct sharding already).

arangosh> var rel = graph_module._relation("isCustomer", ["shop"], ["customer"]);
arangosh> graph._extendEdgeDefinitions(rel);
arangosh> graph_module._graph("myGraph");
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{[SmartGraph] 
  "isCustomer" : [ArangoCollection 2010217, "isCustomer" (type edge, status loaded)], 
  "shop" : [ArangoCollection 2010187, "shop" (type document, status loaded)], 
  "customer" : [ArangoCollection 2010197, "customer" (type document, status loaded)], 
  "pet" : [ArangoCollection 2010207, "pet" (type document, status loaded)] 
}
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