spark-IS-streaming (homepage)

A Nearest Neighbor Classifier for High-Speed Big Data Streams with Instance Selection

@sramirez / (0)

Here we present an efficient nearest neighbor solution to classify fast and massive data streams using Apache Spark. It is formed by a distributed case-base and an instance selection method that enhances its performance and effectiveness. A distributed metric tree (based on M-trees) has been designed to organize the case-base and consequently to speed up the neighbor searches. This distributed tree consists of a top-tree (in the master node) that routes the searches in the first levels and several leaf nodes (in the slaves nodes) that solve the searches in next levels through a completely parallel scheme.


  • 1|streaming
  • 1|machine learning
  • 1|instance selection
  • 1|reduction

How to

Include this package in your Spark Applications using:

spark-shell, pyspark, or spark-submit

> $SPARK_HOME/bin/spark-shell --packages sramirez:spark-IS-streaming:0.8


If you use the sbt-spark-package plugin, in your sbt build file, add:

spDependencies += "sramirez/spark-IS-streaming:0.8"


resolvers += "Spark Packages Repo" at ""

libraryDependencies += "sramirez" % "spark-IS-streaming" % "0.8"


In your pom.xml, add:
  <!-- list of dependencies -->
  <!-- list of other repositories -->


Version: 0.8 ( 581a5e | zip | jar ) / Date: 2017-01-27 / License: Apache-2.0 / Scala version: 2.10