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What's new in RapidMiner Server 9.6

Dear RapidMiner User,

This release has very interesting new features, both for better queue control and more functionality added with the integration of Dashboards (in Docker deployments).

Stop all the jobs in a queue in case you need to completely reset it

Some times, especially after tests, you may find yourself in a situation where one of the queues in your Server is completely overloaded by tens or hundreds of thousands of jobs that were sent, maybe by mistake, or maybe just for testing. The new purge button saves you in that situation, as it can reset the queue and stop all pending jobs, leaving the Server in a clean state, ready to accept new jobs.

Purge queue

Use Dashboards to easily create visualizations from your RapidMiner results (Docker deployments only).

As an alternative to web apps, a Dashboards tool is included, to be deployed together with RapidMiner Server, but in a separate Docker container. Some standard plugins, like Plotly and Multistat, are pre-installed.

It will also be included by default in our RapidMiner Server Cloud VMs for Amazon AWS and Microsoft Azure.

Dashboards 1

Dashboards 2

Significantly improved and streamlined deployment documentation, complete with deployment templates

New and re-factored documentation about the initial step when working with RapidMiner: the deployment of the platform. Focusing especially on Docker-based environments, the documentation offers templates, best practices and recommendations for the most typical cases. Find your case and get started!

New shared default folder in RapidMiner Server

Sharing work among users is a key part in any Data Science project. RapidMiner Server now automatically adds a new "shared" folder during installation with open permissions as a standard, pre-configured way for users to exchange their work or results.

Manage your custom jdbc driver modules from the home directory

If you are using custom JDBC driver modules, this will be helpful for you. From RapidMiner Server 9.6, driver modules are part of the home folder and they remain there after migration, making it simpler and more robust.

Enhancements and bug fixes