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add benchmark ut for Spark TRowSet generation
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...-spark-sql-engine/src/test/scala/org/apache/kyuubi/engine/spark/schema/RowSetHelper.scala
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| /* | ||
| * 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. | ||
| */ | ||
|
|
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| package org.apache.kyuubi.engine.spark.schema | ||
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| import java.sql.{Date, Timestamp} | ||
| import java.time.{Instant, LocalDate} | ||
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| import org.apache.spark.sql.Row | ||
| import org.apache.spark.sql.catalyst.parser.CatalystSqlParser | ||
| import org.apache.spark.sql.types._ | ||
| import org.apache.spark.unsafe.types.CalendarInterval | ||
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| trait RowSetHelper { | ||
| protected def genRow(value: Int): Row = { | ||
| val boolVal = value % 3 match { | ||
| case 0 => true | ||
| case 1 => false | ||
| case _ => null | ||
| } | ||
| val byteVal = value.toByte | ||
| val shortVal = value.toShort | ||
| val longVal = value.toLong | ||
| val floatVal = java.lang.Float.valueOf(s"$value.$value") | ||
| val doubleVal = java.lang.Double.valueOf(s"$value.$value") | ||
| val stringVal = value.toString * value | ||
| val decimalVal = new java.math.BigDecimal(s"$value.$value") | ||
| val day = java.lang.String.format("%02d", java.lang.Integer.valueOf(value % 30 + 1)) | ||
| val dateVal = Date.valueOf(s"2018-11-$day") | ||
| val timestampVal = Timestamp.valueOf(s"2018-11-17 13:33:33.$value") | ||
| val binaryVal = Array.fill[Byte](value)(value.toByte) | ||
| val arrVal = Array.fill(value)(doubleVal).toSeq | ||
| val mapVal = Map(value -> doubleVal) | ||
| val interval = new CalendarInterval(value, value, value) | ||
| val localDate = LocalDate.of(2018, 11, 17) | ||
| val instant = Instant.now() | ||
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| Row( | ||
| boolVal, | ||
| byteVal, | ||
| shortVal, | ||
| value, | ||
| longVal, | ||
| floatVal, | ||
| doubleVal, | ||
| stringVal, | ||
| decimalVal, | ||
| dateVal, | ||
| timestampVal, | ||
| binaryVal, | ||
| arrVal, | ||
| mapVal, | ||
| interval, | ||
| localDate, | ||
| instant) | ||
| } | ||
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| protected val schemaStructFields: Seq[StructField] = Seq( | ||
| ("a", "boolean", "boolVal"), | ||
| ("b", "tinyint", "byteVal"), | ||
| ("c", "smallint", "shortVal"), | ||
| ("d", "int", "value"), | ||
| ("e", "bigint", "longVal"), | ||
| ("f", "float", "floatVal"), | ||
| ("g", "double", "doubleVal"), | ||
| ("h", "string", "stringVal"), | ||
| ("i", "decimal", "decimalVal"), | ||
| ("j", "date", "dateVal"), | ||
| ("k", "timestamp", "timestampVal"), | ||
| ("l", "binary", "binaryVal"), | ||
| ("m", "array<double>", "arrVal"), | ||
| ("n", "map<int, double>", "mapVal"), | ||
| ("o", "interval", "interval"), | ||
| ("p", "date", "localDate"), | ||
| ("q", "timestamp", "instant")) | ||
| .map { case (colName, typeName, comment) => | ||
| StructField(colName, CatalystSqlParser.parseDataType(typeName)).withComment(comment) | ||
| } | ||
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| protected val schema: StructType = StructType(schemaStructFields) | ||
| } |
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...rk-sql-engine/src/test/scala/org/apache/kyuubi/engine/spark/schema/TRowSetBenchmark.scala
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| Original file line number | Diff line number | Diff line change |
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| /* | ||
| * 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. | ||
| */ | ||
|
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| package org.apache.kyuubi.engine.spark.schema | ||
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| import scala.math.BigDecimal.RoundingMode | ||
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| import org.apache.commons.lang3.time.StopWatch | ||
| import org.apache.hive.service.rpc.thrift.TProtocolVersion | ||
| import org.apache.hive.service.rpc.thrift.TProtocolVersion._ | ||
| import org.apache.spark.sql.Row | ||
| import org.apache.spark.sql.types._ | ||
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| import org.apache.kyuubi.KyuubiFunSuite | ||
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| /** | ||
| * Benchmark to measure the performance of generate TRowSet. | ||
| * | ||
| * {{{ | ||
| * RUN_BENCHMARK=1 ./build/mvn clean test \ | ||
| * -pl externals/kyuubi-spark-sql-engine -am \ | ||
| * -Dtest=none -DwildcardSuites=org.apache.kyuubi.engine.spark.schema.TRowSetBenchmark | ||
| * }}} | ||
| */ | ||
| class TRowSetBenchmark extends KyuubiFunSuite with RowSetHelper { | ||
| private val runBenchmark = sys.env.contains("RUN_BENCHMARK") | ||
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| private val rowCount = 3000 | ||
| private lazy val allRows = (0 until rowCount).map(genRow) | ||
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| test("row-based toTRowSet benchmark") { | ||
| assume(runBenchmark) | ||
| tRowSetGenerationBenchmark(HIVE_CLI_SERVICE_PROTOCOL_V5) | ||
| } | ||
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| test("column-based toTRowSet benchmark") { | ||
| assume(runBenchmark) | ||
| tRowSetGenerationBenchmark(HIVE_CLI_SERVICE_PROTOCOL_V6) | ||
| } | ||
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| private def tRowSetGenerationBenchmark(protocolVersion: TProtocolVersion): Unit = { | ||
| val rowSetType = if (protocolVersion.getValue < HIVE_CLI_SERVICE_PROTOCOL_V6.getValue) { | ||
| "row-based" | ||
| } else { | ||
| "column-based" | ||
| } | ||
| // scalastyle:off | ||
| println( | ||
| s"Benchmark result for $rowSetType RowSet.toTRowSet on $protocolVersion with $rowCount rows.") | ||
| printf("%20s %20s %20s\n", "Type(s)", "Time Cost", "Rows/ms") | ||
| // scalastyle:on | ||
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| val totalMs = schemaStructFields.zipWithIndex.map { case (field, idx) => | ||
| // run benchmark with rows of single column with one data type | ||
| val rowsOfSingleType = allRows.map(row => Row(row.get(idx))) | ||
| val schemaOfSingleType = StructType(Seq(field)) | ||
| benchmarkToTRowSet( | ||
| field.getComment().getOrElse(field.dataType.typeName), | ||
| rowsOfSingleType, | ||
| schemaOfSingleType, | ||
| protocolVersion) | ||
| }.sum | ||
| val totalRowsPerMs: BigDecimal = (BigDecimal(rowCount) / totalMs) | ||
| .setScale(3, RoundingMode.HALF_UP) | ||
| // scalastyle:off | ||
| println() | ||
| printf("%20s %20s %20s\n", "sum(all types)", s"$totalMs ms", s"$totalRowsPerMs rows/ms") | ||
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| // run benchmark with rows of columns with all data types | ||
| benchmarkToTRowSet("with all types", allRows, schema, protocolVersion) | ||
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| println() | ||
| println() | ||
| // scalastyle:on | ||
| } | ||
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| private def benchmarkToTRowSet( | ||
| clue: String, | ||
| rows: Seq[Row], | ||
| schema: StructType, | ||
| protocolVersion: TProtocolVersion): BigDecimal = { | ||
| val sw = StopWatch.createStarted() | ||
| RowSet.toTRowSet(rows, schema, protocolVersion) | ||
| sw.stop() | ||
| val msTimeCost: BigDecimal = (BigDecimal(sw.getNanoTime) / BigDecimal(1000000)) | ||
| .setScale(3, RoundingMode.HALF_UP) | ||
| val rowsPerMilliSecond: BigDecimal = (BigDecimal(rows.size) / msTimeCost) | ||
| .setScale(3, RoundingMode.HALF_UP) | ||
| // scalastyle:off | ||
| printf( | ||
| "%20s %20s %20s\n", | ||
| clue, | ||
| s"$msTimeCost ms", | ||
| s"$rowsPerMilliSecond rows/ms") | ||
| // scalastyle:on | ||
| msTimeCost | ||
| } | ||
| } |