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import org.apache.spark.SparkConf | |
import org.apache.spark.serializer.{JavaSerializer, KryoSerializer} | |
import org.apache.spark.sql.catalyst.encoders.ExpressionEncoder | |
import org.apache.spark.sql.catalyst.expressions.UnsafeRow | |
case class Test(i1: Int, i2: Int, i3: Int, i4: Int, i5: Int, i6: Int, i7: Int, i8: Int) | |
object EncoderBenchmark { | |
val runCount = 10000000 | |
def benchmark(a: => Unit) { | |
val results = (1 to 5).map { _ => | |
val startTime = System.nanoTime() | |
var i = 0 | |
while (i < runCount) { | |
i += 1 | |
a | |
} | |
val endTime = System.nanoTime() | |
val runtime = (endTime - startTime).toDouble / 1000000 / 1000 | |
println(s"Runtime: $runtime") | |
runtime | |
} | |
val average = results.sum / results.size | |
println(s"average: $average") | |
println(s"rec/sec: ${runCount/average}") | |
} | |
def main(args: Array[String]): Unit = { | |
val kryo = new org.apache.spark.serializer.KryoSerializer(new org.apache.spark.SparkConf()).newInstance() | |
val instance = Test(1,2,3,4,5,6,7,8) | |
benchmark(kryo.deserialize[Test](kryo.serialize(instance))) | |
println(s"size: ${kryo.serialize(instance).array().length}") | |
val java = new JavaSerializer(new SparkConf()).newInstance() | |
benchmark(java.deserialize[Test](java.serialize(instance))) | |
println(s"size: ${java.serialize(instance).array().length}") | |
val encoder = ExpressionEncoder[Test]().defaultBinding | |
benchmark(encoder.fromRow(encoder.toRow(instance))) | |
println(s"size: ${encoder.toRow(instance).asInstanceOf[UnsafeRow].getSizeInBytes}") | |
} | |
} |
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