Github user rxin commented on a diff in the pull request: https://github.com/apache/spark/pull/12087#discussion_r58643458 --- Diff: sql/core/src/test/scala/org/apache/spark/sql/DatasetBenchmark.scala --- @@ -0,0 +1,85 @@ +/* + * 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.sql + +import org.apache.spark.SparkContext +import org.apache.spark.sql.types.StringType +import org.apache.spark.util.Benchmark + +/** + * Benchmark for Dataset typed operations comparing with DataFrame and RDD versions. + */ +object DatasetBenchmark { + + case class Data(l: Long, s: String) + + def main(args: Array[String]): Unit = { + val sparkContext = new SparkContext("local[*]", "Dataset benchmark") + val sqlContext = new SQLContext(sparkContext) + + import sqlContext.implicits._ + + val numRows = 10000000 + val df = sqlContext.range(1, numRows).select($"id".as("l"), $"id".cast(StringType).as("s")) + + val benchmark = new Benchmark("back-to-back map", numRows) + + val scalaFunc = (d: Data) => Data(d.l + 1, d.s) + benchmark.addCase("Dataset") { iter => + var res = df.as[Data] + var i = 0 + while (i < 10) { + res = res.map(scalaFunc) + i += 1 + } + res.queryExecution.toRdd.foreach(_ => Unit) + } + + benchmark.addCase("DataFrame") { iter => + var res = df + var i = 0 + while (i < 10) { + res = res.select($"l" + 1 as "l") + i += 1 + } + res.queryExecution.toRdd.foreach(_ => Unit) + } + + val rdd = sparkContext.range(1, numRows).map(l => Data(l, l.toString)) + benchmark.addCase("RDD") { iter => + var res = rdd + var i = 0 + while (i < 10) { + res = rdd.map(scalaFunc) + i += 1 + } + res.foreach(_ => Unit) + } + + /* + Java HotSpot(TM) 64-Bit Server VM 1.8.0_60-b27 on Mac OS X 10.11.4 + Intel(R) Core(TM) i7-4960HQ CPU @ 2.60GHz + back-to-back map: Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative + ------------------------------------------------------------------------------------------- + Dataset 902 / 995 11.1 90.2 1.0X + DataFrame 132 / 167 75.5 13.2 6.8X + RDD 216 / 237 46.3 21.6 4.2X --- End diff -- cc @marmbrus not part of this pr, but can we reuse the same object in dataset?
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