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[SPARK-48735][SQL] Performance Improvement for BIN function #47119

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yaooqinn wants to merge 7 commits into from
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[SPARK-48735][SQL] Performance Improvement for BIN function #47119

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47c7a55
improvment
yaooqinn Jun 27, 2024
2544a84
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yaooqinn Jun 27, 2024
58d5870
fix
yaooqinn Jun 27, 2024
d43789f
add benchmark
yaooqinn Jun 27, 2024
364537d
add benchmark
yaooqinn Jun 27, 2024
d4d20f0
Revert "add benchmark"
yaooqinn Jun 27, 2024
21ace11
Revert "add benchmark"
yaooqinn Jun 27, 2024
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Revert "add benchmark" 
This reverts commit 364537d.
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@yaooqinn
yaooqinn committed Jun 27, 2024
commit d4d20f00fb9ebcfcdf6379ab69e8b107651925cd
4 changes: 2 additions & 2 deletions sql/core/benchmarks/MathFunctionBenchmark-results.txt
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Original file line number Diff line number Diff line change
Expand Up @@ -2,6 +2,6 @@ OpenJDK 64-Bit Server VM 17.0.10+0 on Mac OS X 14.5
Apple M2 Max
BIN: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------------------------------
BIN 6047 6056 13 16.5 60.5 1.0X
BIN OLD 12459 12526 96 8.0 124.6 0.5X
BIN 4935 4961 38 40.5 24.7 1.0X
BIN OLD 10170 10493 456 19.7 50.9 0.5X

6 changes: 3 additions & 3 deletions sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/MathFunctionBenchmark.scala
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Expand Up @@ -25,16 +25,16 @@ import org.apache.spark.sql.types.{DataType, LongType}
import org.apache.spark.unsafe.types.UTF8String

object MathFunctionBenchmark extends SqlBasedBenchmark {
private val N = 100L * 1000 * 1000
private val N = 200L * 1000 * 1000

override def runBenchmarkSuite(mainArgs: Array[String]): Unit = {
val benchmark = new Benchmark("BIN", N, output = output)
benchmark.addCase("BIN") { _ =>
spark.range(-N, N).select(Column(Bin(Column("id").expr))).noop()
spark.range(N).select(Column(Bin(Column("id").expr))).noop()
}

benchmark.addCase("BIN OLD") { _ =>
spark.range(-N, N).select(Column(BinOld(Column("id").expr))).noop()
spark.range(N).select(Column(BinOld(Column("id").expr))).noop()
}
benchmark.run()
}
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