[MINOR] Issue: Change "slice" vs "partition" in exception messages (and code?)
## What changes were proposed in this pull request? Came across the term "slice" when running some spark scala code. Consequently, a Google search indicated that "slices" and "partitions" refer to the same things; indeed see: - [This issue](https://issues.apache.org/jira/browse/SPARK-1701) - [This pull request](https://github.com/apache/spark/pull/2305) - [This StackOverflow answer](http://stackoverflow.com/questions/23436640/what-is-the-difference-between-an-rdd-partition-and-a-slice) and [this one](http://stackoverflow.com/questions/24269495/what-are-the-differences-between-slices-and-partitions-of-rdds) Thus this pull request fixes the occurrence of slice I came accross. Nonetheless, [it would appear](https://github.com/apache/spark/search?utf8=%E2%9C%93&q=slice&type=) there are still many references to "slice/slices" - thus I thought I'd raise this Pull Request to address the issue (sorry if this is the wrong place, I'm not too familar with raising apache issues). ## How was this patch tested? (Not tested locally - only a minor exception message change.) Please review http://spark.apache.org/contributing.html before opening a pull request. Author: asmith26 <asmith26@users.noreply.github.com> Closes #17565 from asmith26/master.
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@ -116,7 +116,7 @@ private object ParallelCollectionRDD {
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*/
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def slice[T: ClassTag](seq: Seq[T], numSlices: Int): Seq[Seq[T]] = {
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if (numSlices < 1) {
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throw new IllegalArgumentException("Positive number of slices required")
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throw new IllegalArgumentException("Positive number of partitions required")
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}
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// Sequences need to be sliced at the same set of index positions for operations
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// like RDD.zip() to behave as expected
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@ -26,7 +26,7 @@ import java.util.List;
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/**
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* Computes an approximation to pi
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* Usage: JavaSparkPi [slices]
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* Usage: JavaSparkPi [partitions]
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*/
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public final class JavaSparkPi {
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@ -32,7 +32,7 @@ import org.apache.spark.sql.SparkSession;
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/**
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* Transitive closure on a graph, implemented in Java.
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* Usage: JavaTC [slices]
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* Usage: JavaTC [partitions]
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*/
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public final class JavaTC {
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@ -21,7 +21,7 @@ package org.apache.spark.examples
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import org.apache.spark.sql.SparkSession
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/**
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* Usage: BroadcastTest [slices] [numElem] [blockSize]
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* Usage: BroadcastTest [partitions] [numElem] [blockSize]
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*/
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object BroadcastTest {
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def main(args: Array[String]) {
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@ -23,7 +23,7 @@ import org.apache.spark.sql.SparkSession
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/**
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* Usage: MultiBroadcastTest [slices] [numElem]
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* Usage: MultiBroadcastTest [partitions] [numElem]
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*/
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object MultiBroadcastTest {
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def main(args: Array[String]) {
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@ -100,7 +100,7 @@ object SparkALS {
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ITERATIONS = iters.getOrElse("5").toInt
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slices = slices_.getOrElse("2").toInt
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case _ =>
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System.err.println("Usage: SparkALS [M] [U] [F] [iters] [slices]")
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System.err.println("Usage: SparkALS [M] [U] [F] [iters] [partitions]")
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System.exit(1)
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}
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@ -28,7 +28,7 @@ import org.apache.spark.sql.SparkSession
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/**
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* Logistic regression based classification.
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* Usage: SparkLR [slices]
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* Usage: SparkLR [partitions]
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*
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* This is an example implementation for learning how to use Spark. For more conventional use,
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* please refer to org.apache.spark.ml.classification.LogisticRegression.
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