Adding source code for the tutorial tracked under BAEL-3203. (#7600)
This commit is contained in:
Kumar Chandrakant
Grzegorz Piwowarek
parent
7bcfd6bfa4
commit
8e190c76af
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@ -0,0 +1,150 @@
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5.1,3.5,1.4,0.2,Iris-setosa
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4.9,3.0,1.4,0.2,Iris-setosa
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4.7,3.2,1.3,0.2,Iris-setosa
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4.6,3.1,1.5,0.2,Iris-setosa
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5.0,3.6,1.4,0.2,Iris-setosa
|
||||
5.4,3.9,1.7,0.4,Iris-setosa
|
||||
4.6,3.4,1.4,0.3,Iris-setosa
|
||||
5.0,3.4,1.5,0.2,Iris-setosa
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||||
4.4,2.9,1.4,0.2,Iris-setosa
|
||||
4.9,3.1,1.5,0.1,Iris-setosa
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5.4,3.7,1.5,0.2,Iris-setosa
|
||||
4.8,3.4,1.6,0.2,Iris-setosa
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||||
4.8,3.0,1.4,0.1,Iris-setosa
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||||
4.3,3.0,1.1,0.1,Iris-setosa
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||||
5.8,4.0,1.2,0.2,Iris-setosa
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5.7,4.4,1.5,0.4,Iris-setosa
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||||
5.4,3.9,1.3,0.4,Iris-setosa
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5.1,3.5,1.4,0.3,Iris-setosa
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5.7,3.8,1.7,0.3,Iris-setosa
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5.1,3.8,1.5,0.3,Iris-setosa
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||||
5.4,3.4,1.7,0.2,Iris-setosa
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5.1,3.7,1.5,0.4,Iris-setosa
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4.6,3.6,1.0,0.2,Iris-setosa
|
||||
5.1,3.3,1.7,0.5,Iris-setosa
|
||||
4.8,3.4,1.9,0.2,Iris-setosa
|
||||
5.0,3.0,1.6,0.2,Iris-setosa
|
||||
5.0,3.4,1.6,0.4,Iris-setosa
|
||||
5.2,3.5,1.5,0.2,Iris-setosa
|
||||
5.2,3.4,1.4,0.2,Iris-setosa
|
||||
4.7,3.2,1.6,0.2,Iris-setosa
|
||||
4.8,3.1,1.6,0.2,Iris-setosa
|
||||
5.4,3.4,1.5,0.4,Iris-setosa
|
||||
5.2,4.1,1.5,0.1,Iris-setosa
|
||||
5.5,4.2,1.4,0.2,Iris-setosa
|
||||
4.9,3.1,1.5,0.1,Iris-setosa
|
||||
5.0,3.2,1.2,0.2,Iris-setosa
|
||||
5.5,3.5,1.3,0.2,Iris-setosa
|
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4.9,3.1,1.5,0.1,Iris-setosa
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4.4,3.0,1.3,0.2,Iris-setosa
|
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5.1,3.4,1.5,0.2,Iris-setosa
|
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5.0,3.5,1.3,0.3,Iris-setosa
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4.5,2.3,1.3,0.3,Iris-setosa
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4.4,3.2,1.3,0.2,Iris-setosa
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5.0,3.5,1.6,0.6,Iris-setosa
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5.1,3.8,1.9,0.4,Iris-setosa
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4.8,3.0,1.4,0.3,Iris-setosa
|
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5.1,3.8,1.6,0.2,Iris-setosa
|
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4.6,3.2,1.4,0.2,Iris-setosa
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||||
5.3,3.7,1.5,0.2,Iris-setosa
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5.0,3.3,1.4,0.2,Iris-setosa
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7.0,3.2,4.7,1.4,Iris-versicolor
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6.4,3.2,4.5,1.5,Iris-versicolor
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6.9,3.1,4.9,1.5,Iris-versicolor
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5.5,2.3,4.0,1.3,Iris-versicolor
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6.5,2.8,4.6,1.5,Iris-versicolor
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5.7,2.8,4.5,1.3,Iris-versicolor
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6.3,3.3,4.7,1.6,Iris-versicolor
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4.9,2.4,3.3,1.0,Iris-versicolor
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6.6,2.9,4.6,1.3,Iris-versicolor
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5.2,2.7,3.9,1.4,Iris-versicolor
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5.0,2.0,3.5,1.0,Iris-versicolor
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5.9,3.0,4.2,1.5,Iris-versicolor
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6.0,2.2,4.0,1.0,Iris-versicolor
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6.1,2.9,4.7,1.4,Iris-versicolor
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5.6,2.9,3.6,1.3,Iris-versicolor
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6.7,3.1,4.4,1.4,Iris-versicolor
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5.6,3.0,4.5,1.5,Iris-versicolor
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5.8,2.7,4.1,1.0,Iris-versicolor
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6.2,2.2,4.5,1.5,Iris-versicolor
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5.6,2.5,3.9,1.1,Iris-versicolor
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5.9,3.2,4.8,1.8,Iris-versicolor
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6.1,2.8,4.0,1.3,Iris-versicolor
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6.3,2.5,4.9,1.5,Iris-versicolor
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6.1,2.8,4.7,1.2,Iris-versicolor
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6.4,2.9,4.3,1.3,Iris-versicolor
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6.6,3.0,4.4,1.4,Iris-versicolor
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6.8,2.8,4.8,1.4,Iris-versicolor
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6.7,3.0,5.0,1.7,Iris-versicolor
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6.0,2.9,4.5,1.5,Iris-versicolor
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5.7,2.6,3.5,1.0,Iris-versicolor
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5.5,2.4,3.8,1.1,Iris-versicolor
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5.5,2.4,3.7,1.0,Iris-versicolor
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5.8,2.7,3.9,1.2,Iris-versicolor
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6.0,2.7,5.1,1.6,Iris-versicolor
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5.4,3.0,4.5,1.5,Iris-versicolor
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6.0,3.4,4.5,1.6,Iris-versicolor
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6.7,3.1,4.7,1.5,Iris-versicolor
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6.3,2.3,4.4,1.3,Iris-versicolor
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5.6,3.0,4.1,1.3,Iris-versicolor
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5.5,2.5,4.0,1.3,Iris-versicolor
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5.5,2.6,4.4,1.2,Iris-versicolor
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6.1,3.0,4.6,1.4,Iris-versicolor
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5.8,2.6,4.0,1.2,Iris-versicolor
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5.0,2.3,3.3,1.0,Iris-versicolor
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5.6,2.7,4.2,1.3,Iris-versicolor
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5.7,3.0,4.2,1.2,Iris-versicolor
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5.7,2.9,4.2,1.3,Iris-versicolor
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6.2,2.9,4.3,1.3,Iris-versicolor
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5.1,2.5,3.0,1.1,Iris-versicolor
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5.7,2.8,4.1,1.3,Iris-versicolor
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6.3,3.3,6.0,2.5,Iris-virginica
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5.8,2.7,5.1,1.9,Iris-virginica
|
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7.1,3.0,5.9,2.1,Iris-virginica
|
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6.3,2.9,5.6,1.8,Iris-virginica
|
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6.5,3.0,5.8,2.2,Iris-virginica
|
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7.6,3.0,6.6,2.1,Iris-virginica
|
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4.9,2.5,4.5,1.7,Iris-virginica
|
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7.3,2.9,6.3,1.8,Iris-virginica
|
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6.7,2.5,5.8,1.8,Iris-virginica
|
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7.2,3.6,6.1,2.5,Iris-virginica
|
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6.5,3.2,5.1,2.0,Iris-virginica
|
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6.4,2.7,5.3,1.9,Iris-virginica
|
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6.8,3.0,5.5,2.1,Iris-virginica
|
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5.7,2.5,5.0,2.0,Iris-virginica
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5.8,2.8,5.1,2.4,Iris-virginica
|
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6.4,3.2,5.3,2.3,Iris-virginica
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6.5,3.0,5.5,1.8,Iris-virginica
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7.7,3.8,6.7,2.2,Iris-virginica
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7.7,2.6,6.9,2.3,Iris-virginica
|
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6.0,2.2,5.0,1.5,Iris-virginica
|
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6.9,3.2,5.7,2.3,Iris-virginica
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5.6,2.8,4.9,2.0,Iris-virginica
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7.7,2.8,6.7,2.0,Iris-virginica
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6.3,2.7,4.9,1.8,Iris-virginica
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6.7,3.3,5.7,2.1,Iris-virginica
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7.2,3.2,6.0,1.8,Iris-virginica
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6.2,2.8,4.8,1.8,Iris-virginica
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6.1,3.0,4.9,1.8,Iris-virginica
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6.4,2.8,5.6,2.1,Iris-virginica
|
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7.2,3.0,5.8,1.6,Iris-virginica
|
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7.4,2.8,6.1,1.9,Iris-virginica
|
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7.9,3.8,6.4,2.0,Iris-virginica
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6.4,2.8,5.6,2.2,Iris-virginica
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6.3,2.8,5.1,1.5,Iris-virginica
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6.1,2.6,5.6,1.4,Iris-virginica
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7.7,3.0,6.1,2.3,Iris-virginica
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6.3,3.4,5.6,2.4,Iris-virginica
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6.4,3.1,5.5,1.8,Iris-virginica
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6.0,3.0,4.8,1.8,Iris-virginica
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6.9,3.1,5.4,2.1,Iris-virginica
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6.7,3.1,5.6,2.4,Iris-virginica
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6.9,3.1,5.1,2.3,Iris-virginica
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5.8,2.7,5.1,1.9,Iris-virginica
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6.8,3.2,5.9,2.3,Iris-virginica
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6.7,3.3,5.7,2.5,Iris-virginica
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6.7,3.0,5.2,2.3,Iris-virginica
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6.3,2.5,5.0,1.9,Iris-virginica
|
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6.5,3.0,5.2,2.0,Iris-virginica
|
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6.2,3.4,5.4,2.3,Iris-virginica
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5.9,3.0,5.1,1.8,Iris-virginica
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@ -0,0 +1 @@
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{"class":"org.apache.spark.mllib.classification.LogisticRegressionModel","version":"1.0","numFeatures":4,"numClasses":3}
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@ -1,31 +1,32 @@
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<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
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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>
|
||||
<groupId>com.baeldung</groupId>
|
||||
<artifactId>apache-spark</artifactId>
|
||||
<version>1.0-SNAPSHOT</version>
|
||||
<name>apache-spark</name>
|
||||
<packaging>jar</packaging>
|
||||
<url>http://maven.apache.org</url>
|
||||
<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>
|
||||
<groupId>com.baeldung</groupId>
|
||||
<artifactId>apache-spark</artifactId>
|
||||
<version>1.0-SNAPSHOT</version>
|
||||
<name>apache-spark</name>
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<packaging>jar</packaging>
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||||
<url>http://maven.apache.org</url>
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|
||||
<parent>
|
||||
<groupId>com.baeldung</groupId>
|
||||
<artifactId>parent-modules</artifactId>
|
||||
<version>1.0.0-SNAPSHOT</version>
|
||||
</parent>
|
||||
<parent>
|
||||
<groupId>com.baeldung</groupId>
|
||||
<artifactId>parent-modules</artifactId>
|
||||
<version>1.0.0-SNAPSHOT</version>
|
||||
</parent>
|
||||
|
||||
<dependencies>
|
||||
<dependency>
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||||
<groupId>org.apache.spark</groupId>
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||||
<artifactId>spark-core_2.11</artifactId>
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||||
<version>${org.apache.spark.spark-core.version}</version>
|
||||
<scope>provided</scope>
|
||||
</dependency>
|
||||
<dependencies>
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||||
<dependency>
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<groupId>org.apache.spark</groupId>
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<artifactId>spark-sql_2.11</artifactId>
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||||
<version>${org.apache.spark.spark-sql.version}</version>
|
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<scope>provided</scope>
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<groupId>org.apache.spark</groupId>
|
||||
<artifactId>spark-core_2.11</artifactId>
|
||||
<version>${org.apache.spark.spark-core.version}</version>
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<scope>provided</scope>
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</dependency>
|
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<dependency>
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<groupId>org.apache.spark</groupId>
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||||
<artifactId>spark-sql_2.11</artifactId>
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<version>${org.apache.spark.spark-sql.version}</version>
|
||||
<scope>provided</scope>
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</dependency>
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<dependency>
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<groupId>org.apache.spark</groupId>
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@ -33,6 +34,12 @@
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<version>${org.apache.spark.spark-streaming.version}</version>
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<scope>provided</scope>
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</dependency>
|
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<dependency>
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||||
<groupId>org.apache.spark</groupId>
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||||
<artifactId>spark-mllib_2.11</artifactId>
|
||||
<version>${org.apache.spark.spark-mllib.version}</version>
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||||
<scope>provided</scope>
|
||||
</dependency>
|
||||
<dependency>
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<groupId>org.apache.spark</groupId>
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<artifactId>spark-streaming-kafka-0-10_2.11</artifactId>
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@ -48,46 +55,47 @@
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<artifactId>spark-cassandra-connector-java_2.11</artifactId>
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<version>${com.datastax.spark.spark-cassandra-connector-java.version}</version>
|
||||
</dependency>
|
||||
</dependencies>
|
||||
</dependencies>
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||||
|
||||
<build>
|
||||
<plugins>
|
||||
<plugin>
|
||||
<groupId>org.apache.maven.plugins</groupId>
|
||||
<artifactId>maven-compiler-plugin</artifactId>
|
||||
<version>${maven-compiler-plugin.version}</version>
|
||||
<configuration>
|
||||
<source>${java.version}</source>
|
||||
<target>${java.version}</target>
|
||||
</configuration>
|
||||
</plugin>
|
||||
<plugin>
|
||||
<artifactId>maven-assembly-plugin</artifactId>
|
||||
<executions>
|
||||
<execution>
|
||||
<phase>package</phase>
|
||||
<goals>
|
||||
<goal>single</goal>
|
||||
</goals>
|
||||
</execution>
|
||||
</executions>
|
||||
<configuration>
|
||||
<descriptorRefs>
|
||||
<descriptorRef>jar-with-dependencies</descriptorRef>
|
||||
</descriptorRefs>
|
||||
</configuration>
|
||||
</plugin>
|
||||
</plugins>
|
||||
</build>
|
||||
<plugins>
|
||||
<plugin>
|
||||
<groupId>org.apache.maven.plugins</groupId>
|
||||
<artifactId>maven-compiler-plugin</artifactId>
|
||||
<version>${maven-compiler-plugin.version}</version>
|
||||
<configuration>
|
||||
<source>${java.version}</source>
|
||||
<target>${java.version}</target>
|
||||
</configuration>
|
||||
</plugin>
|
||||
<plugin>
|
||||
<artifactId>maven-assembly-plugin</artifactId>
|
||||
<executions>
|
||||
<execution>
|
||||
<phase>package</phase>
|
||||
<goals>
|
||||
<goal>single</goal>
|
||||
</goals>
|
||||
</execution>
|
||||
</executions>
|
||||
<configuration>
|
||||
<descriptorRefs>
|
||||
<descriptorRef>jar-with-dependencies</descriptorRef>
|
||||
</descriptorRefs>
|
||||
</configuration>
|
||||
</plugin>
|
||||
</plugins>
|
||||
</build>
|
||||
|
||||
<properties>
|
||||
<org.apache.spark.spark-core.version>2.3.0</org.apache.spark.spark-core.version>
|
||||
<org.apache.spark.spark-sql.version>2.3.0</org.apache.spark.spark-sql.version>
|
||||
<org.apache.spark.spark-streaming.version>2.3.0</org.apache.spark.spark-streaming.version>
|
||||
<org.apache.spark.spark-streaming-kafka.version>2.3.0</org.apache.spark.spark-streaming-kafka.version>
|
||||
<com.datastax.spark.spark-cassandra-connector.version>2.3.0</com.datastax.spark.spark-cassandra-connector.version>
|
||||
<com.datastax.spark.spark-cassandra-connector-java.version>1.5.2</com.datastax.spark.spark-cassandra-connector-java.version>
|
||||
<properties>
|
||||
<org.apache.spark.spark-core.version>2.3.0</org.apache.spark.spark-core.version>
|
||||
<org.apache.spark.spark-sql.version>2.3.0</org.apache.spark.spark-sql.version>
|
||||
<org.apache.spark.spark-streaming.version>2.3.0</org.apache.spark.spark-streaming.version>
|
||||
<org.apache.spark.spark-mllib.version>2.3.0</org.apache.spark.spark-mllib.version>
|
||||
<org.apache.spark.spark-streaming-kafka.version>2.3.0</org.apache.spark.spark-streaming-kafka.version>
|
||||
<com.datastax.spark.spark-cassandra-connector.version>2.3.0</com.datastax.spark.spark-cassandra-connector.version>
|
||||
<com.datastax.spark.spark-cassandra-connector-java.version>1.5.2</com.datastax.spark.spark-cassandra-connector-java.version>
|
||||
<maven-compiler-plugin.version>3.2</maven-compiler-plugin.version>
|
||||
</properties>
|
||||
</properties>
|
||||
|
||||
</project>
|
||||
|
|
|
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|
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@ -0,0 +1,111 @@
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|||
package com.baeldung.ml;
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||||
import java.util.HashMap;
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import java.util.Map;
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import org.apache.log4j.Level;
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||||
import org.apache.log4j.Logger;
|
||||
import org.apache.spark.SparkConf;
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||||
import org.apache.spark.api.java.JavaPairRDD;
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||||
import org.apache.spark.api.java.JavaRDD;
|
||||
import org.apache.spark.api.java.JavaSparkContext;
|
||||
import org.apache.spark.mllib.classification.LogisticRegressionModel;
|
||||
import org.apache.spark.mllib.classification.LogisticRegressionWithLBFGS;
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||||
import org.apache.spark.mllib.evaluation.MulticlassMetrics;
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import org.apache.spark.mllib.linalg.Matrix;
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import org.apache.spark.mllib.linalg.Vector;
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||||
import org.apache.spark.mllib.linalg.Vectors;
|
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import org.apache.spark.mllib.regression.LabeledPoint;
|
||||
import org.apache.spark.mllib.stat.MultivariateStatisticalSummary;
|
||||
import org.apache.spark.mllib.stat.Statistics;
|
||||
|
||||
import scala.Tuple2;
|
||||
|
||||
public class MachineLearningApp {
|
||||
|
||||
public static void main(String[] args) {
|
||||
|
||||
// 1. Setting the Spark Context
|
||||
SparkConf conf = new SparkConf().setAppName("Main")
|
||||
.setMaster("local[2]")
|
||||
.set("spark.executor.memory", "3g")
|
||||
.set("spark.driver.memory", "3g");
|
||||
JavaSparkContext sc = new JavaSparkContext(conf);
|
||||
Logger.getLogger("org")
|
||||
.setLevel(Level.OFF);
|
||||
Logger.getLogger("akka")
|
||||
.setLevel(Level.OFF);
|
||||
|
||||
// 2. Loading the Data-set
|
||||
String dataFile = "data\\iris.data";
|
||||
JavaRDD<String> data = sc.textFile(dataFile);
|
||||
|
||||
// 3. Exploratory Data Analysis
|
||||
// 3.1. Creating Vector of Input Data
|
||||
JavaRDD<Vector> inputData = data.map(line -> {
|
||||
String[] parts = line.split(",");
|
||||
double[] v = new double[parts.length - 1];
|
||||
for (int i = 0; i < parts.length - 1; i++) {
|
||||
v[i] = Double.parseDouble(parts[i]);
|
||||
}
|
||||
return Vectors.dense(v);
|
||||
});
|
||||
// 3.2. Performing Statistical Analysis
|
||||
MultivariateStatisticalSummary summary = Statistics.colStats(inputData.rdd());
|
||||
System.out.println("Summary Mean:");
|
||||
System.out.println(summary.mean());
|
||||
System.out.println("Summary Variance:");
|
||||
System.out.println(summary.variance());
|
||||
System.out.println("Summary Non-zero:");
|
||||
System.out.println(summary.numNonzeros());
|
||||
// 3.3. Performing Correlation Analysis
|
||||
Matrix correlMatrix = Statistics.corr(inputData.rdd(), "pearson");
|
||||
System.out.println("Correlation Matrix:");
|
||||
System.out.println(correlMatrix.toString());
|
||||
|
||||
// 4. Data Preparation
|
||||
// 4.1. Creating Map for Textual Output Labels
|
||||
Map<String, Integer> map = new HashMap<String, Integer>();
|
||||
map.put("Iris-setosa", 0);
|
||||
map.put("Iris-versicolor", 1);
|
||||
map.put("Iris-virginica", 2);
|
||||
// 4.2. Creating LabeledPoint of Input and Output Data
|
||||
JavaRDD<LabeledPoint> parsedData = data.map(line -> {
|
||||
String[] parts = line.split(",");
|
||||
double[] v = new double[parts.length - 1];
|
||||
for (int i = 0; i < parts.length - 1; i++) {
|
||||
v[i] = Double.parseDouble(parts[i]);
|
||||
}
|
||||
return new LabeledPoint(map.get(parts[parts.length - 1]), Vectors.dense(v));
|
||||
});
|
||||
|
||||
// 5. Data Splitting into 80% Training and 20% Test Sets
|
||||
JavaRDD<LabeledPoint>[] splits = parsedData.randomSplit(new double[] { 0.8, 0.2 }, 11L);
|
||||
JavaRDD<LabeledPoint> trainingData = splits[0].cache();
|
||||
JavaRDD<LabeledPoint> testData = splits[1];
|
||||
|
||||
// 6. Modeling
|
||||
// 6.1. Model Training
|
||||
LogisticRegressionModel model = new LogisticRegressionWithLBFGS().setNumClasses(3)
|
||||
.run(trainingData.rdd());
|
||||
// 6.2. Model Evaluation
|
||||
JavaPairRDD<Object, Object> predictionAndLabels = testData.mapToPair(p -> new Tuple2<>(model.predict(p.features()), p.label()));
|
||||
MulticlassMetrics metrics = new MulticlassMetrics(predictionAndLabels.rdd());
|
||||
double accuracy = metrics.accuracy();
|
||||
System.out.println("Model Accuracy on Test Data: " + accuracy);
|
||||
|
||||
// 7. Model Saving and Loading
|
||||
// 7.1. Model Saving
|
||||
model.save(sc.sc(), "model\\logistic-regression");
|
||||
// 7.2. Model Loading
|
||||
LogisticRegressionModel sameModel = LogisticRegressionModel.load(sc.sc(), "model\\logistic-regression");
|
||||
// 7.3. Prediction on New Data
|
||||
Vector newData = Vectors.dense(new double[] { 1, 1, 1, 1 });
|
||||
double prediction = sameModel.predict(newData);
|
||||
System.out.println("Model Prediction on New Data = " + prediction);
|
||||
|
||||
// 8. Clean-up
|
||||
sc.close();
|
||||
}
|
||||
|
||||
}
|
||||
Loading…
Reference in New Issue