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Reduce Dataset Size

Always start by reducing your dataset. We recommend that you try to reduce the size of your dataset as the first step when building a model. Either with a Change Columns (to reduce the number of columns) or a Filter (to reduce the number of rows) tool. Alternatively, you can use a Limit tool to reduce the dataset size while inspecting and exploring the data.

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Clear Cache and Restart Sessions

A healthy place to start if you’re running into an error that seems strange to you is to clear your cache and/or restart your sessions. Run the tools again and if you get the same error, you should reach out to our support.

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Output Tool

The Output tool can take a while to run if you’re working with large dataset that you’re storing in a database. We recommend simply saving your model and running it from the folder overview instead of running it from the Canvas

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Resource Errors

We’re automatically making a certain amount of resources available to process your data transformation. That means that you can sometimes run into resource allocation issue. These are the most common things to be aware of.

Temporary Session

The process ran out of ressources. We are getting more compute ressources ready for you - give us 30 seconds and try again!
When you open a new Canvas, you’ll see the yellow bar in the picture below. That means we’re in the process of creating a new resource allocation for you - it takes about 30 seconds for this to disappear. Click the Restart Session button in the top-rigth corner if it takes longer than a couple of minutes.

It also means that you are temporarily allocated a small amount of resources and if you run model with large datasets while being allocated this small amount of resources you will likely get the error shown below.

Simply wait and the yellow bar should disappear. Then you should be good to go.

Running Out of Resources

The process stopped unexpectedly. This is most likely due to ressource constraint. If the problem keep occurring contact support.

It can also happen that you run out of resources even after we’ve allocated the rigth amount of resources to you. Start by clearing your caching and try again. If the problem persist, write a message to our support and we’ll take a look with you.