[SPARK-5939][MLLib] make FPGrowth example app take parameters

Add parameter parsing in FPGrowth example app in Scala and Java
And a sample data file is added in data/mllib folder

Author: Jacky Li <jacky.likun@huawei.com>

Closes #4714 from jackylk/parameter and squashes the following commits:

8c478b3 [Jacky Li] fix according to comments
3bb74f6 [Jacky Li] make FPGrowth exampl app take parameters
f0e4d10 [Jacky Li] make FPGrowth exampl app take parameters

1 files changed, 45 insertions, 14 deletions

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
index aaae275ec5..13f24a1e59 100644
--- a/examples/src/main/scala/org/apache/spark/examples/mllib/FPGrowthExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/mllib/FPGrowthExample.scala
@@ -17,30 +17,61 @@
 
 package org.apache.spark.examples.mllib
 
+import scopt.OptionParser
+
 import org.apache.spark.mllib.fpm.FPGrowth
-import org.apache.spark.{SparkContext, SparkConf}
+import org.apache.spark.{SparkConf, SparkContext}
 
 /**
  * Example for mining frequent itemsets using FP-growth.
+ * Example usage: ./bin/run-example mllib.FPGrowthExample \
+ *   --minSupport 0.8 --numPartition 2 ./data/mllib/sample_fpgrowth.txt
  */
 object FPGrowthExample {
 
+  case class Params(
+    input: String = null,
+    minSupport: Double = 0.3,
+    numPartition: Int = -1) extends AbstractParams[Params]
+
   def main(args: Array[String]) {
-    val conf = new SparkConf().setAppName("FPGrowthExample")
+    val defaultParams = Params()
+
+    val parser = new OptionParser[Params]("FPGrowthExample") {
+      head("FPGrowth: an example FP-growth app.")
+      opt[Double]("minSupport")
+        .text(s"minimal support level, default: ${defaultParams.minSupport}")
+        .action((x, c) => c.copy(minSupport = x))
+      opt[Int]("numPartition")
+        .text(s"number of partition, default: ${defaultParams.numPartition}")
+        .action((x, c) => c.copy(numPartition = x))
+      arg[String]("<input>")
+        .text("input paths to input data set, whose file format is that each line " +
+          "contains a transaction with each item in String and separated by a space")
+        .required()
+        .action((x, c) => c.copy(input = x))
+    }
+
+    parser.parse(args, defaultParams).map { params =>
+      run(params)
+    }.getOrElse {
+      sys.exit(1)
+    }
+  }
+
+  def run(params: Params) {
+    val conf = new SparkConf().setAppName(s"FPGrowthExample with $params")
     val sc = new SparkContext(conf)
+    val transactions = sc.textFile(params.input).map(_.split(" ")).cache()
+
+    println(s"Number of transactions: ${transactions.count()}")
+
+    val model = new FPGrowth()
+      .setMinSupport(params.minSupport)
+      .setNumPartitions(params.numPartition)
+      .run(transactions)
 
-    // 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)
+    println(s"Number of frequent itemsets: ${model.freqItemsets.count()}")
 
     model.freqItemsets.collect().foreach { itemset =>
       println(itemset.items.mkString("[", ",", "]") + ", " + itemset.freq)