yhuang-db commented on code in PR #49447: URL: https://github.com/apache/spark/pull/49447#discussion_r1912371900
########## sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/LargeRowBenchmark.scala: ########## @@ -0,0 +1,73 @@ +/* + * 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.execution.benchmark + +import org.apache.spark.benchmark.Benchmark + +/** + * Benchmark to measure performance for wide table. + * {{{ + * To run this benchmark: + * 1. without sbt: bin/spark-submit --class <this class> + * --jars <spark core test jar>,<spark catalyst test jar> <spark sql test jar> + * 2. build/sbt "sql/Test/runMain <this class>" + * 3. generate result: SPARK_GENERATE_BENCHMARK_FILES=1 build/sbt "sql/Test/runMain <this class>" + * Results will be written to "benchmarks/WideTableBenchmark-results.txt". + * }}} + */ +object LargeRowBenchmark extends SqlBasedBenchmark { + + def runLargeRowBenchmark(rowsNum: Int, numCols: Int, cellSize_mb: Int): Unit = { + withTempPath { path => + val benchmark = new Benchmark( + s"#rows: $rowsNum, #cols: $numCols, cell: $cellSize_mb MB", rowsNum, output = output) + writeLargeRow(path.getAbsolutePath, rowsNum, numCols, cellSize_mb) + val df = spark.read.parquet(path.getAbsolutePath) + df.createOrReplaceTempView("T") + benchmark.addCase("built-in UPPER") { _ => + val sql_select = df.columns.map(c => s"UPPER($c) as $c").mkString(", ") + spark.sql(s"SELECT $sql_select FROM T").noop() + } + benchmark.addCase("udf UPPER") { _ => + val sql_select = df.columns.map(c => s"udf_upper($c) as $c").mkString(", ") + spark.sql(s"SELECT $sql_select FROM T").noop() + } + benchmark.run() + } + } + + override def runBenchmarkSuite(mainArgs: Array[String]): Unit = { + runBenchmark("Large Row Benchmark") { + val udf_upper = (s: String) => s.toUpperCase() + spark.udf.register("udf_upper", udf_upper(_: String): String) + + val benchmarks = Array( + Map("rows" -> 100, "cols" -> 10, "cellSize_mb" -> 1), // OutOfMemory @ 100, 10, 2 Review Comment: We can. If we wanna be more accurate after the decimal, the number would be 1.3mb here. It goes `OutOfMemory` at 1.4mb. -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org --------------------------------------------------------------------- To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
