lazy-linalg (homepage)

Linear algebra operators for Apache Spark MLlib's linalg package

@brkyvz / (1)

It is somewhat cumbersome to write code where you have to convert the MLlib representation of a
vector or matrix to Breeze perform the simplest arithmetic operations like addition, subtraction, etc.
This package aims to lift that burden, and provide efficient implementations for some of these methods.
By keeping operations lazy, this package provides some of the optimizations that you would see
in C++ libraries like Armadillo, Eigen, etc.


Tags

  • 1|machine learning
  • 1|linear algebra
  • 1|lazy

How to

Include this package in your Spark Applications using:

spark-shell, pyspark, or spark-submit

> $SPARK_HOME/bin/spark-shell --packages brkyvz:lazy-linalg:0.1.0

sbt

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

spDependencies += "brkyvz/lazy-linalg:0.1.0"

Otherwise,

resolvers += "Spark Packages Repo" at "http://dl.bintray.com/spark-packages/maven"

libraryDependencies += "brkyvz" % "lazy-linalg" % "0.1.0"

Maven

In your pom.xml, add:
<dependencies>
  <!-- list of dependencies -->
  <dependency>
    <groupId>brkyvz</groupId>
    <artifactId>lazy-linalg</artifactId>
    <version>0.1.0</version>
  </dependency>
</dependencies>
<repositories>
  <!-- list of other repositories -->
  <repository>
    <id>SparkPackagesRepo</id>
    <url>http://dl.bintray.com/spark-packages/maven</url>
  </repository>
</repositories>

Releases

Version: 0.1.0 ( 7de7ac | zip | jar ) / Date: 2015-09-09 / License: Apache-2.0 / Scala version: 2.10

Spark Scala/Java API compatibility: - 18% , - 100% , - 53% , - 19% , - 61% , - 37%