From 04fa1223ee69760f0d23b40e56f4b036aa301879 Mon Sep 17 00:00:00 2001
From: Sean Owen <sowen@cloudera.com>
Date: Mon, 30 Jun 2014 16:03:38 -0700
Subject: [PATCH] SPARK-2293. Replace RDD.zip usage by map with predict inside.
This is the only occurrence of this pattern in the examples that needs to be replaced. It only addresses the example change.
Author: Sean Owen <sowen@cloudera.com>
Closes #1250 from srowen/SPARK-2293 and squashes the following commits:
6b1b28c [Sean Owen] Compute prediction-and-label RDD directly rather than by zipping, for efficiency
---
docs/mllib-naive-bayes.md | 18 ++++++------------
1 file changed, 6 insertions(+), 12 deletions(-)
diff --git a/docs/mllib-naive-bayes.md b/docs/mllib-naive-bayes.md
index 4b3a7cab32..1d1d7dcf6f 100644
--- a/docs/mllib-naive-bayes.md
+++ b/docs/mllib-naive-bayes.md
@@ -51,9 +51,8 @@ val training = splits(0)
val test = splits(1)
val model = NaiveBayes.train(training, lambda = 1.0)
-val prediction = model.predict(test.map(_.features))
-val predictionAndLabel = prediction.zip(test.map(_.label))
+val predictionAndLabel = test.map(p => (model.predict(p.features), p.label))
val accuracy = 1.0 * predictionAndLabel.filter(x => x._1 == x._2).count() / test.count()
{% endhighlight %}
</div>
@@ -71,6 +70,7 @@ can be used for evaluation and prediction.
import org.apache.spark.api.java.JavaPairRDD;
import org.apache.spark.api.java.JavaRDD;
import org.apache.spark.api.java.function.Function;
+import org.apache.spark.api.java.function.PairFunction;
import org.apache.spark.mllib.classification.NaiveBayes;
import org.apache.spark.mllib.classification.NaiveBayesModel;
import org.apache.spark.mllib.regression.LabeledPoint;
@@ -81,18 +81,12 @@ JavaRDD<LabeledPoint> test = ... // test set
final NaiveBayesModel model = NaiveBayes.train(training.rdd(), 1.0);
-JavaRDD<Double> prediction =
- test.map(new Function<LabeledPoint, Double>() {
- @Override public Double call(LabeledPoint p) {
- return model.predict(p.features());
- }
- });
JavaPairRDD<Double, Double> predictionAndLabel =
- prediction.zip(test.map(new Function<LabeledPoint, Double>() {
- @Override public Double call(LabeledPoint p) {
- return p.label();
+ test.mapToPair(new PairFunction<LabeledPoint, Double, Double>() {
+ @Override public Tuple2<Double, Double> call(LabeledPoint p) {
+ return new Tuple2<Double, Double>(model.predict(p.features()), p.label());
}
- }));
+ });
double accuracy = 1.0 * predictionAndLabel.filter(new Function<Tuple2<Double, Double>, Boolean>() {
@Override public Boolean call(Tuple2<Double, Double> pl) {
return pl._1() == pl._2();
--
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