MaxGekk commented on code in PR #45453: URL: https://github.com/apache/spark/pull/45453#discussion_r1538045707
########## sql/core/benchmarks/CollationBenchmark-results.txt: ########## @@ -0,0 +1,26 @@ +OpenJDK 64-Bit Server VM 17.0.10+7-LTS on Linux 6.5.0-1016-azure +AMD EPYC 7763 64-Core Processor +filter df column with collation: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative +----------------------------------------------------------------------------------------------------------------------------------- +filter df column with collation - UNICODE_CI 403 463 39 0.0 20147470.0 1.0X +filter df column with collation - UNICODE 187 223 37 0.0 9339586.0 2.2X +filter df column with collation - UTF8_BINARY_LCASE 426 434 7 0.0 21300903.4 0.9X +filter df column with collation - UTF8_BINARY 188 199 5 0.0 9403169.1 2.1X + +OpenJDK 64-Bit Server VM 17.0.10+7-LTS on Linux 6.5.0-1016-azure +AMD EPYC 7763 64-Core Processor +collation unit benchmarks: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative +------------------------------------------------------------------------------------------------------------------------ +equalsFunction - UTF8_BINARY 0 0 0 10.4 96.6 1.0X Review Comment: Could you increase the number of iterations to have execution time at least > 0. ########## sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/CollationBenchmark.scala: ########## @@ -0,0 +1,117 @@ +/* + * 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 +import org.apache.spark.sql.DataFrame +import org.apache.spark.sql.catalyst.util.CollationFactory +import org.apache.spark.sql.functions._ +import org.apache.spark.unsafe.types.UTF8String + +/** + * Benchmark to measure performance for comparisons between collated strings. 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 org.apache.spark.sql.execution.benchmark.CollationBenchmark" + * 3. generate result: + * SPARK_GENERATE_BENCHMARK_FILES=1 build/sbt "sql/Test/runMain <this class>" + * Results will be written to "benchmarks/CollationBenchmark-results.txt". + * }}} + */ + +object CollationBenchmark extends SqlBasedBenchmark { + private val collationTypes = Seq("UTF8_BINARY_LCASE", "UNICODE", "UTF8_BINARY", "UNICODE_CI") + + def generateSeqInput(n: Long): Seq[UTF8String] = { + val input = Seq("ABC", "ABC", "aBC", "aBC", "abc", "abc", "DEF", "DEF", "def", + "def", "GHI", "ghi", + "JKL", "jkl", "MNO", "mno", "PQR", "pqr", "STU", "stu", "VWX", "vwx", "YZ", + "ABC", "ABC", "aBC", "aBC", "abc", "abc", "DEF", "DEF", "def", "def", "GHI", "ghi", + "JKL", "jkl", "MNO", "mno", "PQR", "pqr", "STU", "stu", "VWX", "vwx", "YZ") + .map(UTF8String.fromString) + val inputLong: Seq[UTF8String] = (0L until n).map(i => input(i.toInt % input.size)) + inputLong + } + + private def getDataFrame(strings: Seq[String]): DataFrame = { + val asPairs = strings.sliding(2, 1).toSeq.map { + case Seq(s1, s2) => (s1, s2) + } + val d = spark.createDataFrame(asPairs).toDF("s1", "s2") + d + } + + private def generateDataframeInput(l: Long): DataFrame = { + getDataFrame(generateSeqInput(l).map(_.toString)) + } + + def benchmarkUTFString(collationTypes: Seq[String], utf8Strings: Seq[UTF8String]): Unit = { + val sublistStrings = utf8Strings + + val benchmark = new Benchmark("collation unit benchmarks", utf8Strings.size, output = output) + collationTypes.foreach(collationType => { + val collation = CollationFactory.fetchCollation(collationType) + benchmark.addCase(s"equalsFunction - $collationType") { _ => + sublistStrings.foreach(s1 => + utf8Strings.foreach(s => + collation.equalsFunction(s, s1).booleanValue() + ) + ) + } + benchmark.addCase(s"collator.compare - $collationType") { _ => + sublistStrings.foreach(s1 => + utf8Strings.foreach(s => + collation.comparator.compare(s, s1) + ) + ) + } + benchmark.addCase(s"hashFunction - $collationType") { _ => + sublistStrings.foreach(_ => + utf8Strings.foreach(s => + collation.hashFunction.applyAsLong(s) + ) + ) + } + } + ) + benchmark.run() + } + + def benchmarkFilterEqual(collationTypes: Seq[String], + dfUncollated: DataFrame): Unit = { + val benchmark = + new Benchmark("filter df column with collation", dfUncollated.count(), output = output) + collationTypes.foreach(collationType => { + val dfCollated = dfUncollated.selectExpr( + s"collate(s2, '$collationType') as k2_$collationType", + s"collate(s1, '$collationType') as k1_$collationType") + benchmark.addCase(s"filter df column with collation - $collationType") { _ => + dfCollated.where(col(s"k1_$collationType") === col(s"k2_$collationType")) + .queryExecution.executedPlan.executeCollect() Review Comment: Could you elaborate a little but why do you use the `executeCollect()` action instead of writing to `noop`? ########## sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/CollationBenchmark.scala: ########## @@ -0,0 +1,117 @@ +/* + * 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 +import org.apache.spark.sql.DataFrame +import org.apache.spark.sql.catalyst.util.CollationFactory +import org.apache.spark.sql.functions._ +import org.apache.spark.unsafe.types.UTF8String + +/** + * Benchmark to measure performance for comparisons between collated strings. 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 org.apache.spark.sql.execution.benchmark.CollationBenchmark" + * 3. generate result: + * SPARK_GENERATE_BENCHMARK_FILES=1 build/sbt "sql/Test/runMain <this class>" + * Results will be written to "benchmarks/CollationBenchmark-results.txt". + * }}} + */ + +object CollationBenchmark extends SqlBasedBenchmark { + private val collationTypes = Seq("UTF8_BINARY_LCASE", "UNICODE", "UTF8_BINARY", "UNICODE_CI") + + def generateSeqInput(n: Long): Seq[UTF8String] = { + val input = Seq("ABC", "ABC", "aBC", "aBC", "abc", "abc", "DEF", "DEF", "def", + "def", "GHI", "ghi", + "JKL", "jkl", "MNO", "mno", "PQR", "pqr", "STU", "stu", "VWX", "vwx", "YZ", + "ABC", "ABC", "aBC", "aBC", "abc", "abc", "DEF", "DEF", "def", "def", "GHI", "ghi", + "JKL", "jkl", "MNO", "mno", "PQR", "pqr", "STU", "stu", "VWX", "vwx", "YZ") + .map(UTF8String.fromString) + val inputLong: Seq[UTF8String] = (0L until n).map(i => input(i.toInt % input.size)) + inputLong + } + + private def getDataFrame(strings: Seq[String]): DataFrame = { + val asPairs = strings.sliding(2, 1).toSeq.map { + case Seq(s1, s2) => (s1, s2) + } + val d = spark.createDataFrame(asPairs).toDF("s1", "s2") + d + } + + private def generateDataframeInput(l: Long): DataFrame = { + getDataFrame(generateSeqInput(l).map(_.toString)) + } + + def benchmarkUTFString(collationTypes: Seq[String], utf8Strings: Seq[UTF8String]): Unit = { + val sublistStrings = utf8Strings + + val benchmark = new Benchmark("collation unit benchmarks", utf8Strings.size, output = output) + collationTypes.foreach(collationType => { + val collation = CollationFactory.fetchCollation(collationType) + benchmark.addCase(s"equalsFunction - $collationType") { _ => + sublistStrings.foreach(s1 => + utf8Strings.foreach(s => + collation.equalsFunction(s, s1).booleanValue() + ) + ) + } + benchmark.addCase(s"collator.compare - $collationType") { _ => + sublistStrings.foreach(s1 => + utf8Strings.foreach(s => + collation.comparator.compare(s, s1) + ) + ) + } + benchmark.addCase(s"hashFunction - $collationType") { _ => + sublistStrings.foreach(_ => + utf8Strings.foreach(s => + collation.hashFunction.applyAsLong(s) + ) + ) + } + } + ) + benchmark.run() + } + + def benchmarkFilterEqual(collationTypes: Seq[String], + dfUncollated: DataFrame): Unit = { Review Comment: fix indentation, see https://github.com/databricks/scala-style-guide?tab=readme-ov-file#indent -- This is an automated message from the Apache Git Service. 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