For example, you can remotely debug by using the open source Remote Debugger instead of using P圜harm Professional documented here. There are many other ways of debugging PySpark applications. Setting PySpark with IDEs is documented here.
If you are running locally, you can directly debug the driver side via using your IDE without the remote debug feature. Profiling and debugging JVM is described at Useful Developer Tools. This page focuses on debugging Python side of PySpark on both driver and executor sides instead of focusing on debugging Before you get started, remote debugging is a feature that is only available with P圜harm Professional.
Ill show you what you need to do to connect P圜harm to Maya so that P圜harm can monitor your code as it runs. Python native functions or data have to be handled, for example, when you execute pandas UDFs or Connecting P圜harms debugger to Maya will help you efficiently introspect your code as it runs, find your bugs, and fix them. They are not launched ifĪ PySpark application does not require interaction between Python workers and JVMs. On the executor side, Python workers execute and handle Python native functions or data. Breakpoints are intentional stopping place or the place where the code is paused.
To start a debug session of your Django application, simply click the green Bug button on the P圜harm toolbar. A must have feature for tracking down problems in your code. When or pyspark.SparkContext is created and initialized, PySpark launches a JVM While debugging a particular script, it is intentional to create a breakpoint. Debugging your Django application with P圜harm enables you to set breakpoints, view variable values and step through your code line-by-line. On the driver side, PySpark communicates with the driver on JVM by using Py4J. PySpark uses Py4J to leverage Spark to submit and computes the jobs. In P圜harm you can set up Python Remote Debug just like in their documentation, however, rather than pointing at a different machine, you can point at localhost.PySpark uses Spark as an engine. Open up the same app code in an existing project or as a new project in P圜harm. Set your Toolkit configuration to point to your local copy of the app/engine/framework, by modifying the location descriptor to become a path/dev descriptor. Make sure that you’re working in a sandbox configuration and that the code for the app, engine, or framework you want to debug is local to your machine.
Here is an example of how to get this up and running with P圜harm. Two IDEs that do support remote debugging are P圜harm (professional edition only) and Visual Studio Code (Free). You should check out your IDE’s documentation to find out what’s possible. How you approach remote debugging will depend entirely on what IDE you’re using, and some may not support it at all. Please note that this isn’t something that Shotgun directly supports, I’ve added it here as a hopefully useful suggestion. Typically this is used when you want to debug code that is running on another computer, but we can also use it to debug code that is running in a different process. That’s where remote debugging can come in. If you’re running your code through an IDE, then you can usually make use of the IDE’s debugger, however, it’s not so easy to debug your code when you need to run it in a DCC such as Maya or Nuke.