org.apache.spark.examples.mllib.JavaSimpleFPGrowth Maven / Gradle / Ivy
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* 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,
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package org.apache.spark.examples.mllib;
// $example on$
import java.util.Arrays;
import java.util.List;
import org.apache.spark.api.java.JavaRDD;
import org.apache.spark.api.java.JavaSparkContext;
import org.apache.spark.mllib.fpm.AssociationRules;
import org.apache.spark.mllib.fpm.FPGrowth;
import org.apache.spark.mllib.fpm.FPGrowthModel;
// $example off$
import org.apache.spark.SparkConf;
public class JavaSimpleFPGrowth {
public static void main(String[] args) {
SparkConf conf = new SparkConf().setAppName("FP-growth Example");
JavaSparkContext sc = new JavaSparkContext(conf);
// $example on$
JavaRDD data = sc.textFile("data/mllib/sample_fpgrowth.txt");
JavaRDD> transactions = data.map(line -> Arrays.asList(line.split(" ")));
FPGrowth fpg = new FPGrowth()
.setMinSupport(0.2)
.setNumPartitions(10);
FPGrowthModel model = fpg.run(transactions);
for (FPGrowth.FreqItemset itemset: model.freqItemsets().toJavaRDD().collect()) {
System.out.println("[" + itemset.javaItems() + "], " + itemset.freq());
}
double minConfidence = 0.8;
for (AssociationRules.Rule rule
: model.generateAssociationRules(minConfidence).toJavaRDD().collect()) {
System.out.println(
rule.javaAntecedent() + " => " + rule.javaConsequent() + ", " + rule.confidence());
}
// $example off$
sc.stop();
}
}
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