wangyum edited a comment on pull request #31691:
URL: https://github.com/apache/spark/pull/31691#issuecomment-792288495
Benchmark there is a window function with a different orderSpec:
```scala
import org.apache.spark.benchmark.Benchmark
val numRows = 50000000L
val benchmark = new Benchmark("Benchmark bloom filter write", numRows,
minNumIters = 3)
spark.sql(s"CREATE TABLE T1 USING PARQUET AS SELECT ID AS A, ID AS B, ID AS
C FROM range(${numRows})")
Seq("org.apache.spark.sql.catalyst.optimizer.LimitPushDown", "").foreach {
rule =>
benchmark.addCase(s"Benchmark excludedRules: ${rule}") { _ =>
withSQLConf("spark.sql.optimizer.excludedRules" -> rule) {
spark.sql("SELECT *, ROW_NUMBER() OVER(ORDER BY a) AS rn, RANK()
OVER(ORDER BY b DESC) AS rk FROM t1 LIMIT 5").show()
}
}
}
benchmark.run()
```
Benchmark results:
```
Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.15.7
Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
Benchmark bloom filter write:
Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns)
Relative
--------------------------------------------------------------------------------------------------------------------------------------------------------------
Benchmark excludedRules:
org.apache.spark.sql.catalyst.optimizer.LimitPushDown 98110
107339 1965 0.5 1962.2 1.0X
Benchmark excludedRules:
53945 65014 1566 0.9 1078.9
1.8X
```
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