Initializing a StreamingKmeans model with static training data
<p>I can construct a Spark Kmeans model using a training dataset. I would like to make my model adapt to new data, so Spark StreamingKmeans seems great for me.</p>

<p>However, it appears that Spark's StreamingKmeans can only be trained on streamed in data. There is no way to initialize it with a default kmeans model, trained on some static training data, and then train the model on new streamed-in data over time.</p>

<p>Does there exist a way to initialize a KMeans model in Spark using static training data, AND train it over time on new data using StreamingKmeans?</p>