Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/2942#discussion_r19490145
--- Diff: docs/mllib-clustering.md ---
@@ -153,3 +153,75 @@ provided in the [Self-Contained
Applications](quick-start.html#self-contained-ap
section of the Spark
Quick Start guide. Be sure to also include *spark-mllib* to your build
file as
a dependency.
+
+## Streaming clustering
+
+When data arrive in a stream, we may want to estimate clusters
dynamically, updating them as new data arrive. MLlib provides support for
streaming KMeans clustering, with parameters to control the decay (or
"forgetfulness") of the estimates. The algorithm uses a generalization of the
mini-batch KMeans update rule. For each batch of data, we assign all points to
their nearest cluster, compute new cluster centers, then update each cluster
using:
--- End diff --
1. line too wide
2. `KMeans` -> `k-means`
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