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Learn how to create a Gremlin query to summarize edges by vertex labels and their counts in Azure Cosmos DB's Gremlin API.
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Summarizing Edges in Gremlin with Vertex Label Counts

If you're working with the Azure Cosmos DB Gremlin API, you may encounter a scenario where you need to summarize edges in your graph database by counting occurrences based on vertex labels. This can be a bit tricky if you're primarily familiar with basic Graph Traversal Language (Gremlin) queries that don't include aggregating functions. Well, fear not! In this post, we will walk you through the solution step-by-step.

The Challenge: Counting Edges by Vertex Labels

You might have a Gremlin query at hand that fetches edges with their corresponding in and out vertex labels, but it stops short of tallying the edge counts. For example, the output of your current query may look something like this:

[[See Video to Reveal this Text or Code Snippet]]

If you're looking for output that includes counts, such as:

[[See Video to Reveal this Text or Code Snippet]]

you're in the right place! Let's dive into how you can achieve that.

The Solution: Using groupCount()

The key to this solution involves using the groupCount() function in combination with the project() step. This method allows you to encapsulate your edge and vertex labeling into a single count, enabling summary statistics for your graph data.

Step 1: Write the Query

Here’s a Gremlin query that summarizes edges by counting how many times each combination of edge, in, and out occurs:

[[See Video to Reveal this Text or Code Snippet]]

Breakdown of the Query:

g.E(): This initiates the query by accessing all edges in the graph.

groupCount(): This function groups edges and counts occurrences of the defined key.

project(): This step constructs a new map that includes keys for edge, in, and out labels.

by(label()): Retrieves the label of the edge.

by(inV().label()): Gets the label of the incoming vertex.

by(outV().label()): Gets the label of the outgoing vertex.

unfold(): This flattens the grouped output to a more readable format.

Step 2: Handling Database Constraints

In cases where your graph database may not support keys as maps, you might need to adjust the output further to retrieve a more manageable structure. For instance, you could use the following query:

[[See Video to Reveal this Text or Code Snippet]]

Expected Results

Upon running either of these queries, you should expect an output structured like this:

[[See Video to Reveal this Text or Code Snippet]]

This output clearly indicates the edge labels, the corresponding in and out vertex labels, and the counts of each edge configuration.

Conclusion

By harnessing the power of groupCount() and project(), you can effectively summarize edges in Gremlin by their vertex labels and counts. With these techniques, your data analysis in Azure Cosmos DB will become more insightful and actionable. If you have any further questions or need clarification on any of these steps, feel free to leave a comment below!