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Diffstat (limited to 'examples')
3 files changed, 129 insertions, 0 deletions
diff --git a/examples/src/main/scala/spark/examples/GroupByTest.scala b/examples/src/main/scala/spark/examples/GroupByTest.scala new file mode 100644 index 0000000000..48c02a52c6 --- /dev/null +++ b/examples/src/main/scala/spark/examples/GroupByTest.scala @@ -0,0 +1,37 @@ +package spark.examples + +import spark.SparkContext +import spark.SparkContext._ +import java.util.Random + +object GroupByTest { + def main(args: Array[String]) { + if (args.length == 0) { + System.err.println("Usage: GroupByTest <host> [numMappers] [numKVPairs] [KeySize] [numReducers]") + System.exit(1) + } + + var numMappers = if (args.length > 1) args(1).toInt else 2 + var numKVPairs = if (args.length > 2) args(2).toInt else 1000 + var valSize = if (args.length > 3) args(3).toInt else 1000 + var numReducers = if (args.length > 4) args(4).toInt else numMappers + + val sc = new SparkContext(args(0), "GroupBy Test") + + val pairs1 = sc.parallelize(0 until numMappers, numMappers).flatMap { p => + val ranGen = new Random + var arr1 = new Array[(Int, Array[Byte])](numKVPairs) + for (i <- 0 until numKVPairs) { + val byteArr = new Array[Byte](valSize) + ranGen.nextBytes(byteArr) + arr1(i) = (ranGen.nextInt(Int.MaxValue), byteArr) + } + arr1 + }.cache + // Enforce that everything has been calculated and in cache + pairs1.count + + println(pairs1.groupByKey(numReducers).count) + } +} + diff --git a/examples/src/main/scala/spark/examples/SimpleSkewedGroupByTest.scala b/examples/src/main/scala/spark/examples/SimpleSkewedGroupByTest.scala new file mode 100644 index 0000000000..c8edb7d8b4 --- /dev/null +++ b/examples/src/main/scala/spark/examples/SimpleSkewedGroupByTest.scala @@ -0,0 +1,51 @@ +package spark.examples + +import spark.SparkContext +import spark.SparkContext._ +import java.util.Random + +object SimpleSkewedGroupByTest { + def main(args: Array[String]) { + if (args.length == 0) { + System.err.println("Usage: SimpleSkewedGroupByTest <host> " + + "[numMappers] [numKVPairs] [valSize] [numReducers] [ratio]") + System.exit(1) + } + + var numMappers = if (args.length > 1) args(1).toInt else 2 + var numKVPairs = if (args.length > 2) args(2).toInt else 1000 + var valSize = if (args.length > 3) args(3).toInt else 1000 + var numReducers = if (args.length > 4) args(4).toInt else numMappers + var ratio = if (args.length > 5) args(5).toInt else 5.0 + + val sc = new SparkContext(args(0), "GroupBy Test") + + val pairs1 = sc.parallelize(0 until numMappers, numMappers).flatMap { p => + val ranGen = new Random + var result = new Array[(Int, Array[Byte])](numKVPairs) + for (i <- 0 until numKVPairs) { + val byteArr = new Array[Byte](valSize) + ranGen.nextBytes(byteArr) + val offset = ranGen.nextInt(1000) * numReducers + if (ranGen.nextDouble < ratio / (numReducers + ratio - 1)) { + // give ratio times higher chance of generating key 0 (for reducer 0) + result(i) = (offset, byteArr) + } else { + // generate a key for one of the other reducers + val key = 1 + ranGen.nextInt(numReducers-1) + offset + result(i) = (key, byteArr) + } + } + result + }.cache + // Enforce that everything has been calculated and in cache + pairs1.count + + println("RESULT: " + pairs1.groupByKey(numReducers).count) + // Print how many keys each reducer got (for debugging) + //println("RESULT: " + pairs1.groupByKey(numReducers) + // .map{case (k,v) => (k, v.size)} + // .collectAsMap) + } +} + diff --git a/examples/src/main/scala/spark/examples/SkewedGroupByTest.scala b/examples/src/main/scala/spark/examples/SkewedGroupByTest.scala new file mode 100644 index 0000000000..e6dec44bed --- /dev/null +++ b/examples/src/main/scala/spark/examples/SkewedGroupByTest.scala @@ -0,0 +1,41 @@ +package spark.examples + +import spark.SparkContext +import spark.SparkContext._ +import java.util.Random + +object SkewedGroupByTest { + def main(args: Array[String]) { + if (args.length == 0) { + System.err.println("Usage: GroupByTest <host> [numMappers] [numKVPairs] [KeySize] [numReducers]") + System.exit(1) + } + + var numMappers = if (args.length > 1) args(1).toInt else 2 + var numKVPairs = if (args.length > 2) args(2).toInt else 1000 + var valSize = if (args.length > 3) args(3).toInt else 1000 + var numReducers = if (args.length > 4) args(4).toInt else numMappers + + val sc = new SparkContext(args(0), "GroupBy Test") + + val pairs1 = sc.parallelize(0 until numMappers, numMappers).flatMap { p => + val ranGen = new Random + + // map output sizes lineraly increase from the 1st to the last + numKVPairs = (1. * (p + 1) / numMappers * numKVPairs).toInt + + var arr1 = new Array[(Int, Array[Byte])](numKVPairs) + for (i <- 0 until numKVPairs) { + val byteArr = new Array[Byte](valSize) + ranGen.nextBytes(byteArr) + arr1(i) = (ranGen.nextInt(Int.MaxValue), byteArr) + } + arr1 + }.cache + // Enforce that everything has been calculated and in cache + pairs1.count + + println(pairs1.groupByKey(numReducers).count) + } +} + |