From 66924ffa6bdb8e0df1b90b789cb7ad443377e729 Mon Sep 17 00:00:00 2001 From: Xiangrui Meng Date: Sun, 2 Aug 2015 11:50:17 -0700 Subject: [SPARK-9527] [MLLIB] add PrefixSpanModel and make PrefixSpan Java friendly 1. Use `PrefixSpanModel` to wrap the frequent sequences. 2. Define `FreqSequence` to wrap each frequent sequence, which contains a Java-friendly method `javaSequence` 3. Overload `run` for Java users. 4. Added a unit test in Java to check Java compatibility. zhangjiajin feynmanliang Author: Xiangrui Meng Closes #7869 from mengxr/SPARK-9527 and squashes the following commits: 4345594 [Xiangrui Meng] add PrefixSpanModel and make PrefixSpan Java friendly --- .../org/apache/spark/mllib/fpm/PrefixSpan.scala | 52 +++++++++++++++++++--- 1 file changed, 47 insertions(+), 5 deletions(-) (limited to 'mllib/src/main') diff --git a/mllib/src/main/scala/org/apache/spark/mllib/fpm/PrefixSpan.scala b/mllib/src/main/scala/org/apache/spark/mllib/fpm/PrefixSpan.scala index c1761c3642..9eaf733fad 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/fpm/PrefixSpan.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/fpm/PrefixSpan.scala @@ -17,11 +17,16 @@ package org.apache.spark.mllib.fpm +import java.{lang => jl, util => ju} + +import scala.collection.JavaConverters._ import scala.collection.mutable.ArrayBuilder import scala.reflect.ClassTag import org.apache.spark.Logging import org.apache.spark.annotation.Experimental +import org.apache.spark.api.java.JavaRDD +import org.apache.spark.api.java.JavaSparkContext.fakeClassTag import org.apache.spark.rdd.RDD import org.apache.spark.storage.StorageLevel @@ -93,9 +98,9 @@ class PrefixSpan private ( /** * Find the complete set of sequential patterns in the input sequences of itemsets. * @param data ordered sequences of itemsets. - * @return (sequential itemset pattern, count) tuples + * @return a [[PrefixSpanModel]] that contains the frequent sequences */ - def run[Item: ClassTag](data: RDD[Array[Array[Item]]]): RDD[(Array[Array[Item]], Long)] = { + def run[Item: ClassTag](data: RDD[Array[Array[Item]]]): PrefixSpanModel[Item] = { val itemToInt = data.aggregate(Set[Item]())( seqOp = { (uniqItems, item) => uniqItems ++ item.flatten.toSet }, combOp = { _ ++ _ } @@ -113,9 +118,25 @@ class PrefixSpan private ( case (x, xs) => List(x.map(intToItem).toArray) } } - results.map { case (seq: Array[Int], count: Long) => - (toPublicRepr(seq).toArray, count) + val freqSequences = results.map { case (seq: Array[Int], count: Long) => + new FreqSequence[Item](toPublicRepr(seq).toArray, count) } + new PrefixSpanModel[Item](freqSequences) + } + + /** + * A Java-friendly version of [[run()]] that reads sequences from a [[JavaRDD]] and returns + * frequent sequences in a [[PrefixSpanModel]]. + * @param data ordered sequences of itemsets stored as Java Iterable of Iterables + * @tparam Item item type + * @tparam Itemset itemset type, which is an Iterable of Items + * @tparam Sequence sequence type, which is an Iterable of Itemsets + * @return a [[PrefixSpanModel]] that contains the frequent sequences + */ + def run[Item, Itemset <: jl.Iterable[Item], Sequence <: jl.Iterable[Itemset]]( + data: JavaRDD[Sequence]): PrefixSpanModel[Item] = { + implicit val tag = fakeClassTag[Item] + run(data.rdd.map(_.asScala.map(_.asScala.toArray).toArray)) } /** @@ -287,7 +308,7 @@ class PrefixSpan private ( } -private[fpm] object PrefixSpan { +object PrefixSpan { private[fpm] val DELIMITER = -1 /** Splits an array of itemsets delimited by [[DELIMITER]]. */ @@ -313,4 +334,25 @@ private[fpm] object PrefixSpan { // TODO: improve complexity by using partial prefixes, considering one item at a time itemSet.subsets.filter(_ != Set.empty[Int]) } + + /** + * Represents a frequence sequence. + * @param sequence a sequence of itemsets stored as an Array of Arrays + * @param freq frequency + * @tparam Item item type + */ + class FreqSequence[Item](val sequence: Array[Array[Item]], val freq: Long) extends Serializable { + /** + * Returns sequence as a Java List of lists for Java users. + */ + def javaSequence: ju.List[ju.List[Item]] = sequence.map(_.toList.asJava).toList.asJava + } } + +/** + * Model fitted by [[PrefixSpan]] + * @param freqSequences frequent sequences + * @tparam Item item type + */ +class PrefixSpanModel[Item](val freqSequences: RDD[PrefixSpan.FreqSequence[Item]]) + extends Serializable -- cgit v1.2.3