spark-instrumented-optimizer/mllib/pom.xml

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<?xml version="1.0" encoding="UTF-8"?>
<!--
~ Licensed to the Apache Software Foundation (ASF) under one or more
~ contributor license agreements. See the NOTICE file distributed with
~ this work for additional information regarding copyright ownership.
~ The ASF licenses this file to You under the Apache License, Version 2.0
~ (the "License"); you may not use this file except in compliance with
~ the License. You may obtain a copy of the License at
~
~ http://www.apache.org/licenses/LICENSE-2.0
~
~ Unless required by applicable law or agreed to in writing, software
~ distributed under the License is distributed on an "AS IS" BASIS,
~ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
~ See the License for the specific language governing permissions and
~ limitations under the License.
-->
<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<parent>
<groupId>org.apache.spark</groupId>
<artifactId>spark-parent</artifactId>
<version>1.1.0-SNAPSHOT</version>
<relativePath>../pom.xml</relativePath>
</parent>
<groupId>org.apache.spark</groupId>
<artifactId>spark-mllib_2.10</artifactId>
<packaging>jar</packaging>
<name>Spark Project ML Library</name>
<url>http://spark.apache.org/</url>
<dependencies>
<dependency>
<groupId>org.apache.spark</groupId>
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<artifactId>spark-core_${scala.binary.version}</artifactId>
<version>${project.version}</version>
</dependency>
<dependency>
<groupId>org.eclipse.jetty</groupId>
<artifactId>jetty-server</artifactId>
</dependency>
<dependency>
<groupId>org.jblas</groupId>
<artifactId>jblas</artifactId>
<version>${jblas.version}</version>
</dependency>
[SPARK-1212] Adding sparse data support and update KMeans Continue our discussions from https://github.com/apache/incubator-spark/pull/575 This PR is WIP because it depends on a SNAPSHOT version of breeze. Per previous discussions and benchmarks, I switched to breeze for linear algebra operations. @dlwh and I made some improvements to breeze to keep its performance comparable to the bare-bone implementation, including norm computation and squared distance. This is why this PR needs to depend on a SNAPSHOT version of breeze. @fommil , please find the notice of using netlib-core in `NOTICE`. This is following Apache's instructions on appropriate labeling. I'm going to update this PR to include: 1. Fast distance computation: using `\|a\|_2^2 + \|b\|_2^2 - 2 a^T b` when it doesn't introduce too much numerical error. The squared norms are pre-computed. Otherwise, computing the distance between the center (dense) and a point (possibly sparse) always takes O(n) time. 2. Some numbers about the performance. 3. A released version of breeze. @dlwh, a minor release of breeze will help this PR get merged early. Do you mind sharing breeze's release plan? Thanks! Author: Xiangrui Meng <meng@databricks.com> Closes #117 from mengxr/sparse-kmeans and squashes the following commits: 67b368d [Xiangrui Meng] fix SparseVector.toArray 5eda0de [Xiangrui Meng] update NOTICE 67abe31 [Xiangrui Meng] move ArrayRDDs to mllib.rdd 1da1033 [Xiangrui Meng] remove dependency on commons-math3 and compute EPSILON directly 9bb1b31 [Xiangrui Meng] optimize SparseVector.toArray 226d2cd [Xiangrui Meng] update Java friendly methods in Vectors 238ba34 [Xiangrui Meng] add VectorRDDs with a converter from RDD[Array[Double]] b28ba2f [Xiangrui Meng] add toArray to Vector e69b10c [Xiangrui Meng] remove examples/JavaKMeans.java, which is replaced by mllib/examples/JavaKMeans.java 72bde33 [Xiangrui Meng] clean up code for distance computation 712cb88 [Xiangrui Meng] make Vectors.sparse Java friendly 27858e4 [Xiangrui Meng] update breeze version to 0.7 07c3cf2 [Xiangrui Meng] change Mahout to breeze in doc use a simple lower bound to avoid unnecessary distance computation 6f5cdde [Xiangrui Meng] fix a bug in filtering finished runs 42512f2 [Xiangrui Meng] Merge branch 'master' into sparse-kmeans d6e6c07 [Xiangrui Meng] add predict(RDD[Vector]) to KMeansModel 42b4e50 [Xiangrui Meng] line feed at the end a4ace73 [Xiangrui Meng] Merge branch 'fast-dist' into sparse-kmeans 3ed1a24 [Xiangrui Meng] add doc to BreezeVectorWithSquaredNorm 0107e19 [Xiangrui Meng] update NOTICE 87bc755 [Xiangrui Meng] tuned the KMeans code: changed some for loops to while, use view to avoid copying arrays 0ff8046 [Xiangrui Meng] update KMeans to use fastSquaredDistance f355411 [Xiangrui Meng] add BreezeVectorWithSquaredNorm case class ab74f67 [Xiangrui Meng] add fastSquaredDistance for KMeans 4e7d5ca [Xiangrui Meng] minor style update 07ffaf2 [Xiangrui Meng] add dense/sparse vector data models and conversions to/from breeze vectors use breeze to implement KMeans in order to support both dense and sparse data
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<dependency>
<groupId>org.scalanlp</groupId>
<artifactId>breeze_${scala.binary.version}</artifactId>
<version>0.7</version>
</dependency>
<dependency>
<groupId>org.scalatest</groupId>
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<artifactId>scalatest_${scala.binary.version}</artifactId>
<scope>test</scope>
</dependency>
<dependency>
<groupId>org.scalacheck</groupId>
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<artifactId>scalacheck_${scala.binary.version}</artifactId>
<scope>test</scope>
</dependency>
<dependency>
<groupId>com.novocode</groupId>
<artifactId>junit-interface</artifactId>
<scope>test</scope>
</dependency>
</dependencies>
<build>
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<outputDirectory>target/scala-${scala.binary.version}/classes</outputDirectory>
<testOutputDirectory>target/scala-${scala.binary.version}/test-classes</testOutputDirectory>
<plugins>
<plugin>
<groupId>org.scalatest</groupId>
<artifactId>scalatest-maven-plugin</artifactId>
</plugin>
</plugins>
</build>
</project>