If you have questions or suggestions for other utility UDFs, we’d like to hear from you: create an issue directly in GitHub repo, or ask away in our Stack Overflow forum. As a technical artifact of your pipeline deployment, the UDF is a component of your infrastructure, and so we recommend you follow Infrastructure-as-Code (IaC) best practices including version-controlling your UDF. We hope this helps you get started with customizing some of the off-the-shelf Google-provided Dataflow templates using one of the above utility UDFs or writing your own UDF function. Refer to Dataflow user docs to learn more about Dataflow worker service account. Note: The Dataflow worker service account used must have access to the GCS object (JavaScript file) containing your UDF function. JavascriptTextTransformFunctionName: Name of JavaScript function to call as your UDFĪs a Dataflow user or operator, you simply reference a pre-existing template URL (Google-hosted), and your custom UDF (Customer-hosted) without the requirement to have a Beam developer environment setup or to maintain the template code itself. JavascriptTextTransformGcsPath: GCS location path to JavaScript file with your UDF code Gcs-location: GCS location path to the Dataflow template In Cloud Shell, you can launch Nashorn in interactive mode as follows: Let’s assume your UDF is saved in dataflow_udf_transform.js JavaScript file and that you’re using UDF example 1.1 above which appends new inputSubscription field. That said, using the utility UDFs provided above without major code changes should be sufficient for most use cases.Īn easy way to test your UDF on Nashorn engine is by launching Cloud Shell where JDK 11 is pre-installed, including jjs command-line tool to invoke Nashorn engine. For more details, see this introduction to using Oracle Nashorn. A common pitfall is using console.log() or Number.isNaN() for example, neither of which are defined in the Nashorn engine. In addition, it’s important to note that Nashorn engine is a slightly different JavaScript implementation than Node.js. By default, Nashorn engine is only ECMAScript 5.1 (ES5) compliant so a lot of newer ES6 JavaScript keywords like let or const will cause syntax errors. This will cause a pipeline outage as the UDF is unable to process those messages in-flight.Īt the time of this writing, Google-provided Dataflow templates run on JDK 11 environment with the corresponding Nashorn engine v11 release. Before pipeline deployment, it is highly recommended to test your UDF on Nashorn engine: any JavaScript syntax error will throw an exception, potentially on every message. Pattern 1: Enrich eventsīesides ensuring functional correctness, you must verify your UDF code is syntactically correct JavaScript on Oracle Nashorn JavaScript engine which is shipped as part of JDK (8 through 14) pre-installed in Dataflow workers. They are grouped below by common patterns. The following code snippets are example transformation logic to be inserted in the above UDF process function. For more context, see includePubsubMessage parameter in Pub/Sub to Splunk template documentation. The statement setting data variable is needed to normalize the UDF input payload in order to simplify your subsequent transformation logic in the UDF, consistent with the examples below. Note: The variable includePubsubMessage is required if the UDF is applied to Pub/Sub to Splunk Dataflow template since it supports two possible element formats: that specific template can be configured to process the full Pub/Sub message payload or only the underlying Pub/Sub message data payload (default behavior). In the next section, we provide you with utility UDF samples from real-world use cases. Where highlighted, you add your custom element transformation logic depending on your use case. Using JavaScript’s standard built-in JSON object, the UDF first parses the stringified element inJson into a variable obj, and, at the end, it must return a stringified version outJson of the modified element obj.
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