MLlib supports streaming linear models:
http://spark.apache.org/docs/latest/mllib-linear-methods.html#streaming-linear-regression
and k-means:
http://spark.apache.org/docs/latest/mllib-clustering.html#k-means
With an iteration parameter of 1, this amounts to mini-batch SGD where the
mini-batch is
I wanted to ask a basic question about the types of algorithms that are
possible to apply to a DStream with Spark streaming. With Spark it is possible
to perform iterative computations on RDDs like in the gradient descent example
val points = spark.textFile(...).map(parsePoint).cache()
