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Edge Traversal Strategies

When working with graph collections, you might need to traverse edges of a particular type. Two primary approaches can help you accomplish this.

Filtering Edges with Attributes​

One way to traverse specific edge types is by using an attribute in the edge document, such as type. This attribute can differentiate between edge categories, such as "friends", "family", "married", or "workmates". To follow only the friend edges, you can filter the edges using FILTER e.type = "friends".

Utilizing Multiple Edge Collections​

A potentially more efficient alternative is to create separate edge collections for different types of edges. For instance, you could use collection names like friend_edges, family_edges, married_edges, and workmate_edges. You can then configure several graphs that include subsets of the available edge and vertex collections. To follow only friend edges, specify friend_edges as the single edge collection.

Selecting the Right Approach​

Each method offers advantages and drawbacks:

  • Filtering edges using attributes can be CPU-intensive, as comparisons are performed on each traversed edge.
  • The multiple edge collections approach is constrained by the number of collections that can be used simultaneously in one query (max: 10 collections) to limit resource requirements.

When choosing an approach, consider your use case and data constraints. If your edges have around a dozen different types, the collection approach may be more suitable; otherwise, the FILTER approach is recommended. With the collection approach, you can still use FILTER operations on edges, eliminating the need for a FILTER on the type while keeping everything else the same.