Github user rxin commented on a diff in the pull request:
https://github.com/apache/spark/pull/10589#discussion_r48929712
--- 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("%-24s %16s %16s %14s\n", name + ":", "Avg Time(ms)", "Avg
Rate(M/s)", "Relative Rate")
+
println("-------------------------------------------------------------------------")
+ results.zip(benchmarks).foreach { r =>
+ printf("%-24s %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
--- End diff --
I'd consider printing the detailed timing about each run too. Anyway for
the purpose of what @nongli is trying to accomplish, I don't think JIT is that
big of a deal here.
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