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[SPARK-10019][MLlib]: ML model broadcasts should be stored in private vars: mllib IDFModel #8248

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sabhyankar wants to merge 2 commits into from
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[SPARK-10019][MLlib]: ML model broadcasts should be stored in private vars: mllib IDFModel #8248

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6bf0bec
Add private var to store broadcast variable
Aug 17, 2015
98fa159
Create a local ref to model object to avoid sending the entire object…
Aug 18, 2015
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11 changes: 9 additions & 2 deletions mllib/src/main/scala/org/apache/spark/mllib/feature/IDF.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -21,6 +21,7 @@ import breeze.linalg.{DenseVector => BDV}

import org.apache.spark.annotation.Experimental
import org.apache.spark.api.java.JavaRDD
import org.apache.spark.broadcast.Broadcast
import org.apache.spark.mllib.linalg.{DenseVector, SparseVector, Vector, Vectors}
import org.apache.spark.rdd.RDD

Expand Down Expand Up @@ -161,6 +162,8 @@ private object IDF {
@Experimental
class IDFModel private[spark] (val idf: Vector) extends Serializable {

private var bcIdf: Option[Broadcast[Vector]] = None

/**
* Transforms term frequency (TF) vectors to TF-IDF vectors.
*
Expand All @@ -172,8 +175,12 @@ class IDFModel private[spark] (val idf: Vector) extends Serializable {
* @return an RDD of TF-IDF vectors
*/
def transform(dataset: RDD[Vector]): RDD[Vector] = {
val bcIdf = dataset.context.broadcast(idf)
dataset.mapPartitions(iter => iter.map(v => IDFModel.transform(bcIdf.value, v)))
bcIdf match {
case None => bcIdf = Some(dataset.context.broadcast(idf))
case _ =>
}
val lclBcIdf = bcIdf
dataset.mapPartitions(iter => iter.map(v => IDFModel.transform(lclBcIdf.get.value, v)))
}

/**
Expand Down