wangyum edited a comment on issue #24872: [SPARK-28023][SQL] Trim the string when cast string type to Boolean/Numeric types URL: https://github.com/apache/spark/pull/24872#issuecomment-503827016 Benchmark and benchmark result. ```scala /* * 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 trim the string when casting string type to Boolean/Numeric types. * To run this benchmark: * {{{ * 1. without sbt: * bin/spark-submit --class <this class> --jars <spark core 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/CastBenchmark-results.txt". * }}} */ object CastBenchmark extends SqlBasedBenchmark { override def runBenchmarkSuite(mainArgs: Array[String]): Unit = { val title = "Benchmark trim the string" runBenchmark(title) { withTempPath { dir => val N = 500L << 13 val df = spark.range(N) val withoutWhitespace = "withoutWhitespace" val withWhitespace = "withWhitespace" val types = Seq("int", "long", "float", "double", "decimal", "boolean") df.selectExpr("cast(id as string) as str") .write.mode("overwrite").parquet(dir + withoutWhitespace) df.selectExpr(s"concat('${" " * 5}', id, '${" " * 5}') as str") .write.mode("overwrite").parquet(dir + withWhitespace) val benchmark = new Benchmark(title, N, minNumIters = 5, output = output) Seq(withoutWhitespace, withWhitespace).foreach { data => Seq(false, true).foreach { isTrimStr => val expr = types.map(t => s"cast(${if (isTrimStr) "trim(str)" else "str"} as $t) as c_$t") val name = s"$data ${if (isTrimStr) "with" else "without"} trim" benchmark.addCase(name) { _ => spark.read.parquet(dir + data).selectExpr(expr: _*).collect() } } } benchmark.run() } } } } ``` Before this pr(after SPARK-28066): ``` [info] Java HotSpot(TM) 64-Bit Server VM 1.8.0_191-b12 on Mac OS X 10.12.6 [info] Intel(R) Core(TM) i7-7820HQ CPU @ 2.90GHz [info] Benchmark trim the string: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative [info] ------------------------------------------------------------------------------------------------------------------------ [info] withoutWhitespace without trim 7452 7945 529 0.5 1819.2 1.0X [info] withoutWhitespace with trim 8013 8289 277 0.5 1956.3 0.9X [info] withWhitespace without trim 12502 13474 1062 0.3 3052.3 0.6X [info] withWhitespace with trim 7652 8544 688 0.5 1868.1 1.0X ``` After this pr(after SPARK-28066): ``` [info] Java HotSpot(TM) 64-Bit Server VM 1.8.0_191-b12 on Mac OS X 10.12.6 [info] Intel(R) Core(TM) i7-7820HQ CPU @ 2.90GHz [info] Benchmark trim the string: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative [info] ------------------------------------------------------------------------------------------------------------------------ [info] withoutWhitespace without trim 7467 7849 336 0.5 1823.0 1.0X [info] withoutWhitespace with trim 7445 8006 702 0.6 1817.6 1.0X [info] withWhitespace without trim 5665 6889 1295 0.7 1383.0 1.3X [info] withWhitespace with trim 5627 6201 630 0.7 1373.8 1.3X ```
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