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authorXiangrui Meng <meng@databricks.com>2015-02-18 10:09:56 -0800
committerXiangrui Meng <meng@databricks.com>2015-02-18 10:09:56 -0800
commit85e9d091d5d785d412e91038c2490131e64f5634 (patch)
tree79d956ee9eb4859e32e0dfc46531a346389cb581 /examples
parent5aecdcf1f23a826f6236096001de1dd811dbc443 (diff)
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[SPARK-5519][MLLIB] add user guide with example code for fp-growth
The API is still not very Java-friendly because `Array[Item]` in `freqItemsets` is recognized as `Object` in Java. We might want to define a case class to wrap the return pair to make it Java friendly. Author: Xiangrui Meng <meng@databricks.com> Closes #4661 from mengxr/SPARK-5519 and squashes the following commits: 58ccc25 [Xiangrui Meng] add user guide with example code for fp-growth
Diffstat (limited to 'examples')
-rw-r--r--examples/src/main/java/org/apache/spark/examples/mllib/JavaFPGrowthExample.java63
-rw-r--r--examples/src/main/scala/org/apache/spark/examples/mllib/FPGrowthExample.scala51
2 files changed, 114 insertions, 0 deletions
diff --git a/examples/src/main/java/org/apache/spark/examples/mllib/JavaFPGrowthExample.java b/examples/src/main/java/org/apache/spark/examples/mllib/JavaFPGrowthExample.java
new file mode 100644
index 0000000000..0db572d760
--- /dev/null
+++ b/examples/src/main/java/org/apache/spark/examples/mllib/JavaFPGrowthExample.java
@@ -0,0 +1,63 @@
+/*
+ * 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.
+ */
+
+package org.apache.spark.examples.mllib;
+
+import java.util.ArrayList;
+import java.util.Arrays;
+
+import scala.Tuple2;
+
+import com.google.common.collect.Lists;
+
+import org.apache.spark.SparkConf;
+import org.apache.spark.api.java.JavaRDD;
+import org.apache.spark.api.java.JavaSparkContext;
+import org.apache.spark.mllib.fpm.FPGrowth;
+import org.apache.spark.mllib.fpm.FPGrowthModel;
+
+/**
+ * Java example for mining frequent itemsets using FP-growth.
+ */
+public class JavaFPGrowthExample {
+
+ public static void main(String[] args) {
+ SparkConf sparkConf = new SparkConf().setAppName("JavaFPGrowthExample");
+ JavaSparkContext sc = new JavaSparkContext(sparkConf);
+
+
+ // TODO: Read a user-specified input file.
+ @SuppressWarnings("unchecked")
+ JavaRDD<ArrayList<String>> transactions = sc.parallelize(Lists.newArrayList(
+ Lists.newArrayList("r z h k p".split(" ")),
+ Lists.newArrayList("z y x w v u t s".split(" ")),
+ Lists.newArrayList("s x o n r".split(" ")),
+ Lists.newArrayList("x z y m t s q e".split(" ")),
+ Lists.newArrayList("z".split(" ")),
+ Lists.newArrayList("x z y r q t p".split(" "))), 2);
+
+ FPGrowth fpg = new FPGrowth()
+ .setMinSupport(0.3);
+ FPGrowthModel<String> model = fpg.run(transactions);
+
+ for (Tuple2<Object, Long> s: model.javaFreqItemsets().collect()) {
+ System.out.println(Arrays.toString((Object[]) s._1()) + ", " + s._2());
+ }
+
+ sc.stop();
+ }
+}
diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/FPGrowthExample.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/FPGrowthExample.scala
new file mode 100644
index 0000000000..ae66107d70
--- /dev/null
+++ b/examples/src/main/scala/org/apache/spark/examples/mllib/FPGrowthExample.scala
@@ -0,0 +1,51 @@
+/*
+ * 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.
+ */
+
+package org.apache.spark.examples.mllib
+
+import org.apache.spark.mllib.fpm.FPGrowth
+import org.apache.spark.{SparkContext, SparkConf}
+
+/**
+ * Example for mining frequent itemsets using FP-growth.
+ */
+object FPGrowthExample {
+
+ def main(args: Array[String]) {
+ val conf = new SparkConf().setAppName("FPGrowthExample")
+ val sc = new SparkContext(conf)
+
+ // TODO: Read a user-specified input file.
+ val transactions = sc.parallelize(Seq(
+ "r z h k p",
+ "z y x w v u t s",
+ "s x o n r",
+ "x z y m t s q e",
+ "z",
+ "x z y r q t p").map(_.split(" ")), numSlices = 2)
+
+ val fpg = new FPGrowth()
+ .setMinSupport(0.3)
+ val model = fpg.run(transactions)
+
+ model.freqItemsets.collect().foreach { case (itemset, freq) =>
+ println(itemset.mkString("[", ",", "]") + ", " + freq)
+ }
+
+ sc.stop()
+ }
+}