Visualizing DSE Graph

DataStax Enterprise (DSE) Graph is a scale-out OLTP graph database for managing complex and highly connected data. DSE Graph is designed for enterprise cloud applications. Enterprise users wanted a Cassandra-based high-performance back end to handle huge volumes of evolving graph data. Able to deliver continuous uptime and predictable performance, DSE Graph is great at discovering commonalities and anomalies among dynamic and constantly changing datasets. One advantage is that DSE Graph uses TinkerPop3 and Gremlin, so existing open source Titan database applications should migrate seamlessly. The DSE Graph bundle also comes with the Gremlin Server and Console, so there’s no need to download them separately.

Visualization architecture

KeyLines is a database agnostic visualization solution that integrates particularly well with graph databases like DSE Graph.

The simplest way to visualize the DSE Graph with KeyLines is using the bundled TinkerPop interface. In this scenario, KeyLines files are hosted on a web server and presented to users in the web browser. Every time a user interacts with nodes and links on their KeyLines chart, they query the DSE Graph database. Queries are sent to TinkerPop using WebSockets, and data is returned as JSON objects for KeyLines to visualize.

Integrate DSE Graph & KeyLines

This tutorial walks you through the steps to connect KeyLines to your DSE Graph database. If you’re not using KeyLines already, sign up for a free trial. You’ll also get access to the KeyLines SDK site featuring demos and a live-coding playground.

Step 1: Configure the DSE Graph & load data

For full configuration and loading details, see the DataStax documentation.

Step 2: Connect to the Gremlin Server

By default, the Gremlin Server uses the WebSocket channel. This makes it ideal for real-time or data streaming scenarios, but as it has a custom sub-protocol, it is unlikely to work in its default state. Drivers already exist for many different languages. There’s a client library for JavaScript and NodeJS called gremlin-javascript. It uses ES2015/ES6 features including JavaScript Promises for better flow control, and template strings for easier-to-read Gremlin query generation. To use the gremlin-javascript library in your browser, follow their instructions, and then include the resulting gremlin.js file in the HTML page. In the app file, create and configure the client:

          let client = null;
          const connectClient = () => {
            // create a gremlin client
            client = new gremlin.driver.Client(configs.endpoint, {
              traversalSource: 'movies.g',
              mimeType: 'application/vnd.gremlin-v2.0+json',
            });
          }
          connectClient();

Next, submit the query:

          async function submitQuery(client, statement, bindings) {
          // if client still doesn't exist, reject immidiatly with the last error
          return new Promise((resolve, reject) => {
            if (client === null) {
              reject(error);
            } else {
              // resolve the promise if submit is successful, set a new error otherwise
              client.submit(statement, bindings)
              .then(resolve)
            }
          });
        }

        async function returnResponse(client) {
          const response = await submitQuery(client, 'g.V().hasLabel("Movie").has("title", querySearch).inE("ACTED_IN").outV().hasLabel("Person").project("degree").by(outE("ACTED_IN").count()).path().unfold()', { "querySearch": "The Matrix" });
          return response;
        }

        const items = await returnResponse(client);

        // turn the response into KeyLines

        const keyLinesItems = toKeyLinesFormat(items._items);

Step 3: Convert to KeyLines JSON

To display our graph, KeyLines needs the data in its own JSON format. Let’s write a toKeyLinesFormat function to create a JSON object of nodes and links that KeyLines can recognize:

          function toKeyLinesFormat(rawItems) {
          const items = [];
          while (rawItems.length) {
            // the response format is subject to the sent query format
            const [v1, edge, v2, degree] = rawItems.splice(0, 4);
            items.push(makeNode(v1), makeLink(edge), makeNode(v2, degree.degree));
          }

          return items;
        }

Step 4: Load the graph in KeyLines

The final step is to load the data in our KeyLines chart:

       chart.load({
       type: 'LinkChart',
       items,
     });

And that’s it! You’ll see a KeyLines chart that can pull data from your DataStax DSE Graph database.

Next steps: Extend the UI

Every object type, function, event and option is documented in the KeyLines SDK’s API Reference library. Use this, together with the live-coding playground, to create customized tools that’ll help your users explore and understand the data in their own DataStax DSE Graph databases.

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