Skip to main content


Analyzes incoming datasets in near real-time, based on applying the K-Means algorithm.

This component analyzes streaming feature vectors to continuously adapt an existing clustering model to changing circumstances. The incoming data is usually pre-processed by tModelEncoder and the K-Means model is used by tPredict to cluster given elements.

It continuously updates a K-Means clustering model out of this analysis and writes this model either in memory or in a given file system.

In local mode, Apache Spark 1.6.0 and later versions are supported.

For more technologies supported by Talend, see Talend components.

Did this page help you?

If you find any issues with this page or its content – a typo, a missing step, or a technical error – let us know how we can improve!