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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.
*/
package org.apache.spark.sql
import org.apache.spark.sql.catalyst.InternalRow
import org.apache.spark.sql.catalyst.encoders.RowEncoder
import org.apache.spark.sql.catalyst.expressions.UnsafeProjection
import org.apache.spark.sql.types._
import org.apache.spark.util.Benchmark
/**
* Benchmark [[UnsafeProjection]] for fixed-length/primitive-type fields.
*/
object UnsafeProjectionBenchmark {
def generateRows(schema: StructType, numRows: Int): Array[InternalRow] = {
val generator = RandomDataGenerator.forType(schema, nullable = false).get
val encoder = RowEncoder(schema)
(1 to numRows).map(_ => encoder.toRow(generator().asInstanceOf[Row]).copy()).toArray
}
def main(args: Array[String]) {
val iters = 1024 * 16
val numRows = 1024 * 16
val benchmark = new Benchmark("unsafe projection", iters * numRows)
val schema1 = new StructType().add("l", LongType, false)
val attrs1 = schema1.toAttributes
val rows1 = generateRows(schema1, numRows)
val projection1 = UnsafeProjection.create(attrs1, attrs1)
benchmark.addCase("single long") { _ =>
for (_ <- 1 to iters) {
var sum = 0L
var i = 0
while (i < numRows) {
sum += projection1(rows1(i)).getLong(0)
i += 1
}
}
}
val schema2 = new StructType().add("l", LongType, true)
val attrs2 = schema2.toAttributes
val rows2 = generateRows(schema2, numRows)
val projection2 = UnsafeProjection.create(attrs2, attrs2)
benchmark.addCase("single nullable long") { _ =>
for (_ <- 1 to iters) {
var sum = 0L
var i = 0
while (i < numRows) {
sum += projection2(rows2(i)).getLong(0)
i += 1
}
}
}
val schema3 = new StructType()
.add("boolean", BooleanType, false)
.add("byte", ByteType, false)
.add("short", ShortType, false)
.add("int", IntegerType, false)
.add("long", LongType, false)
.add("float", FloatType, false)
.add("double", DoubleType, false)
val attrs3 = schema3.toAttributes
val rows3 = generateRows(schema3, numRows)
val projection3 = UnsafeProjection.create(attrs3, attrs3)
benchmark.addCase("7 primitive types") { _ =>
for (_ <- 1 to iters) {
var sum = 0L
var i = 0
while (i < numRows) {
sum += projection3(rows3(i)).getLong(0)
i += 1
}
}
}
val schema4 = new StructType()
.add("boolean", BooleanType, true)
.add("byte", ByteType, true)
.add("short", ShortType, true)
.add("int", IntegerType, true)
.add("long", LongType, true)
.add("float", FloatType, true)
.add("double", DoubleType, true)
val attrs4 = schema4.toAttributes
val rows4 = generateRows(schema4, numRows)
val projection4 = UnsafeProjection.create(attrs4, attrs4)
benchmark.addCase("7 nullable primitive types") { _ =>
for (_ <- 1 to iters) {
var sum = 0L
var i = 0
while (i < numRows) {
sum += projection4(rows4(i)).getLong(0)
i += 1
}
}
}
/*
Intel(R) Core(TM) i7-4960HQ CPU @ 2.60GHz
unsafe projection: Avg Time(ms) Avg Rate(M/s) Relative Rate
-------------------------------------------------------------------------------
single long 1533.34 175.07 1.00 X
single nullable long 2306.73 116.37 0.66 X
primitive types 8403.93 31.94 0.18 X
nullable primitive types 12448.39 21.56 0.12 X
*/
benchmark.run()
}
}
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