Github user nongli commented on a diff in the pull request: https://github.com/apache/spark/pull/10593#discussion_r49035976 --- Diff: core/src/test/scala/org/apache/spark/Benchmark.scala --- @@ -0,0 +1,102 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark + +import scala.collection.mutable + +import org.apache.commons.lang3.SystemUtils +import org.apache.spark.util.Utils + +/** + * Utility class to benchmark components. An example of how to use this is: + * val benchmark = new Benchmark("My Benchmark", valuesPerIteration) + * benchmark.addCase("V1", <function>") + * benchmark.addCase("V2", <function>") + * benchmark.run + * This will output the average time to run each function and the rate of each function. + * + * The benchmark function takes one argument that is the iteration that's being run + */ +class Benchmark(name: String, valuesPerIteration: Long, iters: Int = 5) { + val benchmarks = mutable.ArrayBuffer.empty[Benchmark.Case] + + def addCase(name: String, f: Int => Unit): Unit = { + benchmarks += Benchmark.Case(name, f) + } + + /** + * Runs the benchmark and outputs the results to stdout. This should be copied and added as + * a comment with the benchmark. Although the results vary from machine to machine, it should + * provide some baseline. + */ + def run(): Unit = { + require(benchmarks.nonEmpty) + val results = benchmarks.map { c => + Benchmark.measure(valuesPerIteration, c.fn, iters) + } + val firstRate = results.head.avgRate + // scalastyle:off + // The results are going to be processor specific so it is useful to include that. + println(Benchmark.getProcessorName()) + printf("%-30s %16s %16s %14s\n", name + ":", "Avg Time(ms)", "Avg Rate(M/s)", "Relative Rate") + println("-------------------------------------------------------------------------------") + results.zip(benchmarks).foreach { r => + printf("%-30s %16s %16s %14s\n", r._2.name, r._1.avgMs.toString, "%10.2f" format r._1.avgRate, + "%6.2f X" format (r._1.avgRate / firstRate)) + } + println + // scalastyle:on + } +} + +object Benchmark { + case class Case(name: String, fn: Int => Unit) + case class Result(avgMs: Double, avgRate: Double) + + /** + * This should return a user helpful processor information. Getting at this depends on the OS. + * This should return something like "Intel(R) Core(TM) i7-4870HQ CPU @ 2.50GHz" + */ + def getProcessorName(): String = { + if (SystemUtils.IS_OS_MAC_OSX) { + Utils.executeAndGetOutput(Seq("/usr/sbin/sysctl", "-n", "machdep.cpu.brand_string")) + } else if (SystemUtils.IS_OS_LINUX) { + Utils.executeAndGetOutput(Seq("/usr/bin/grep", "-m", "1", "\"model name\"", "/proc/cpuinfo")) + } else { + System.getenv("PROCESSOR_IDENTIFIER") + } + } + + /** + * Runs a single function `f` for iters, returning the average time the function took and + * the rate of the function. + */ + def measure(num: Long, f: Int => Unit, iters: Int): Result = { + var totalTime = 0L + for (i <- 0 until iters + 1) { + val start = System.currentTimeMillis() --- End diff -- JMH looks great and it would be good to add. The utility I added is super simple and gets us going and I don't think it's worth blocking other work items. It would be great if someone added JMH to spark and deleted this benchmarking harness.
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