Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/4714#discussion_r25124134
--- Diff:
examples/src/main/scala/org/apache/spark/examples/mllib/FPGrowthExample.scala
---
@@ -18,29 +18,58 @@
package org.apache.spark.examples.mllib
import org.apache.spark.mllib.fpm.FPGrowth
-import org.apache.spark.{SparkContext, SparkConf}
+import org.apache.spark.{SparkConf, SparkContext}
+import scopt.OptionParser
/**
* Example for mining frequent itemsets using FP-growth.
+ * Example usage: ./bin/run-example
org.apache.spark.examples.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]("FPGrowth") {
+ 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")
+ .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}")
--- End diff --
`count` -> `count()`. We use `()` if it is an action.
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