# tKMeansStrModel

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](https://help.qlik.com/talend/r/en-US/7.3/components/machine-learning).

### In this section

* [tKMeansStrModel properties for Apache Spark Streaming](https://help.qlik.com/talend/en-US/components/7.3/machine-learning/tkmeansstrmodel-properties-for-apache-spark-streaming)