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minor: Refactor expression microbenchmarks to remove duplicate code #2956

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Merged
andygrove merged 5 commits into from
Dec 22, 2025
Merged

minor: Refactor expression microbenchmarks to remove duplicate code #2956

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91c1e4a
refactor
andygrove Dec 22, 2025
2d52bb8
Merge remote-tracking branch 'apache/main' into refactor-expression-b…
andygrove Dec 22, 2025
f1c6be8
refactor Cast benchmark
andygrove Dec 22, 2025
3a8d49a
format
andygrove Dec 22, 2025
7034e27
format
andygrove Dec 22, 2025
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53 changes: 6 additions & 47 deletions spark/src/test/scala/org/apache/spark/sql/benchmark/CometArithmeticBenchmark.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -19,11 +19,8 @@

package org.apache.spark.sql.benchmark

import org.apache.spark.benchmark.Benchmark
import org.apache.spark.sql.types._

import org.apache.comet.CometConf

/**
* Benchmark to measure Comet expression evaluation performance. To run this benchmark:
* `SPARK_GENERATE_BENCHMARK_FILES=1 make
Expand All @@ -35,10 +32,6 @@ object CometArithmeticBenchmark extends CometBenchmarkBase {

def integerArithmeticBenchmark(values: Int, op: BinaryOp, useDictionary: Boolean): Unit = {
val dataType = IntegerType
val benchmark = new Benchmark(
s"Binary op ${dataType.sql}, dictionary = $useDictionary",
values,
output = output)

withTempPath { dir =>
withTempTable(table) {
Expand All @@ -48,25 +41,10 @@ object CometArithmeticBenchmark extends CometBenchmarkBase {
s"SELECT CAST(value AS ${dataType.sql}) AS c1, " +
s"CAST(value AS ${dataType.sql}) c2 FROM $tbl"))

benchmark.addCase(s"$op ($dataType) - Spark") { _ =>
spark.sql(s"SELECT c1 ${op.sig} c2 FROM $table").noop()
}

benchmark.addCase(s"$op ($dataType) - Comet (Scan)") { _ =>
withSQLConf(CometConf.COMET_ENABLED.key -> "true") {
spark.sql(s"SELECT c1 ${op.sig} c2 FROM $table").noop()
}
}

benchmark.addCase(s"$op ($dataType) - Comet (Scan, Exec)") { _ =>
withSQLConf(
CometConf.COMET_ENABLED.key -> "true",
CometConf.COMET_EXEC_ENABLED.key -> "true") {
spark.sql(s"SELECT c1 ${op.sig} c2 FROM $table").noop()
}
}
val name = s"Binary op ${dataType.sql}, dictionary = $useDictionary"
val query = s"SELECT c1 ${op.sig} c2 FROM $table"

benchmark.run()
runExpressionBenchmark(name, values, query)
}
}
}
Expand All @@ -76,36 +54,17 @@ object CometArithmeticBenchmark extends CometBenchmarkBase {
dataType: DecimalType,
op: BinaryOp,
useDictionary: Boolean): Unit = {
val benchmark = new Benchmark(
s"Binary op ${dataType.sql}, dictionary = $useDictionary",
values,
output = output)
val df = makeDecimalDataFrame(values, dataType, useDictionary)

withTempPath { dir =>
withTempTable(table) {
df.createOrReplaceTempView(tbl)
prepareTable(dir, spark.sql(s"SELECT dec AS c1, dec AS c2 FROM $tbl"))

benchmark.addCase(s"$op ($dataType) - Spark") { _ =>
spark.sql(s"SELECT c1 ${op.sig} c2 FROM $table").noop()
}

benchmark.addCase(s"$op ($dataType) - Comet (Scan)") { _ =>
withSQLConf(CometConf.COMET_ENABLED.key -> "true") {
spark.sql(s"SELECT c1 ${op.sig} c2 FROM $table").noop()
}
}

benchmark.addCase(s"$op ($dataType) - Comet (Scan, Exec)") { _ =>
withSQLConf(
CometConf.COMET_ENABLED.key -> "true",
CometConf.COMET_EXEC_ENABLED.key -> "true") {
spark.sql(s"SELECT c1 ${op.sig} c2 FROM $table").noop()
}
}
val name = s"Binary op ${dataType.sql}, dictionary = $useDictionary"
val query = s"SELECT c1 ${op.sig} c2 FROM $table"

benchmark.run()
runExpressionBenchmark(name, values, query)
}
}
}
Expand Down
48 changes: 48 additions & 0 deletions spark/src/test/scala/org/apache/spark/sql/benchmark/CometBenchmarkBase.scala
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Expand Up @@ -110,6 +110,54 @@ trait CometBenchmarkBase extends SqlBasedBenchmark {
benchmark.run()
}

/**
* Runs an expression benchmark with standard cases: Spark, Comet (Scan), Comet (Scan + Exec).
* This provides a consistent benchmark structure for expression evaluation.
*
* @param name
* Benchmark name
* @param cardinality
* Number of rows being processed
* @param query
* SQL query to benchmark
* @param extraCometConfigs
* Additional configurations to apply for Comet cases (optional)
*/
final def runExpressionBenchmark(
name: String,
cardinality: Long,
query: String,
extraCometConfigs: Map[String, String] = Map.empty): Unit = {
val benchmark = new Benchmark(name, cardinality, output = output)

benchmark.addCase("Spark") { _ =>
withSQLConf(CometConf.COMET_ENABLED.key -> "false") {
spark.sql(query).noop()
}
}

benchmark.addCase("Comet (Scan)") { _ =>
withSQLConf(
CometConf.COMET_ENABLED.key -> "true",
CometConf.COMET_EXEC_ENABLED.key -> "false") {
spark.sql(query).noop()
}
}
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@coderfender coderfender Dec 22, 2025

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Minor : Would we be needing exec and scan exec for all types of benchmarks @andygrove ?

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@andygrove andygrove Dec 22, 2025

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Yes, I only updated expression benchmarks in this PR but will follow up for the other ones (shuffle, exec, aggregate) in separate PRs in the future but those ones are a little more involved. My short term goal is to add benchmarks for all expressions, so wanted to refactor the expression benchmarks before doing that.


val cometExecConfigs = Map(
CometConf.COMET_ENABLED.key -> "true",
CometConf.COMET_EXEC_ENABLED.key -> "true",
"spark.sql.optimizer.constantFolding.enabled" -> "false") ++ extraCometConfigs

benchmark.addCase("Comet (Scan + Exec)") { _ =>
withSQLConf(cometExecConfigs.toSeq: _*) {
spark.sql(query).noop()
}
}

benchmark.run()
}

protected def prepareTable(dir: File, df: DataFrame, partition: Option[String] = None): Unit = {
val testDf = if (partition.isDefined) {
df.write.partitionBy(partition.get)
Expand Down
42 changes: 5 additions & 37 deletions spark/src/test/scala/org/apache/spark/sql/benchmark/CometCastBenchmark.scala
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Expand Up @@ -19,14 +19,10 @@

package org.apache.spark.sql.benchmark

import scala.util.Try

import org.apache.spark.benchmark.Benchmark
import org.apache.spark.sql.SparkSession
import org.apache.spark.sql.internal.SQLConf
import org.apache.spark.sql.types.{DataType, LongType}

import org.apache.comet.CometConf
import org.apache.comet.expressions.{CometCast, CometEvalMode}
import org.apache.comet.serde.{Compatible, Incompatible, Unsupported}

Expand Down Expand Up @@ -81,48 +77,20 @@ object CometCastBenchmark extends CometBenchmarkBase {
toDataType: DataType,
isAnsiMode: Boolean): Unit = {

val benchmark =
new Benchmark(
s"Cast function to : ${toDataType} , ansi mode enabled : ${isAnsiMode}",
values,
output = output)

withTempPath { dir =>
withTempTable("parquetV1Table") {
prepareTable(dir, spark.sql(s"SELECT value FROM $tbl"))

val functionSQL = castExprSQL(toDataType, "value")
val query = s"SELECT $functionSQL FROM parquetV1Table"
val name =
s"Cast function to : ${toDataType} , ansi mode enabled : ${isAnsiMode}"

benchmark.addCase(
s"SQL Parquet - Spark Cast expr from ${fromDataType.sql} to : ${toDataType.sql} , " +
s"ansi mode enabled : ${isAnsiMode}") { _ =>
withSQLConf(SQLConf.ANSI_ENABLED.key -> isAnsiMode.toString) {
if (isAnsiMode) {
Try { spark.sql(query).noop() }
} else {
spark.sql(query).noop()
}
}
}
val extraConfigs = Map(SQLConf.ANSI_ENABLED.key -> isAnsiMode.toString)

benchmark.addCase(
s"SQL Parquet - Comet Cast expr from ${fromDataType.sql} to : ${toDataType.sql} , " +
s"ansi mode enabled : ${isAnsiMode}") { _ =>
withSQLConf(
CometConf.COMET_ENABLED.key -> "true",
CometConf.COMET_EXEC_ENABLED.key -> "true",
SQLConf.ANSI_ENABLED.key -> isAnsiMode.toString) {
if (isAnsiMode) {
Try { spark.sql(query).noop() }
} else {
spark.sql(query).noop()
}
}
}
benchmark.run()
runExpressionBenchmark(name, values, query, extraConfigs)
}
}

}

}
49 changes: 3 additions & 46 deletions ...k/src/test/scala/org/apache/spark/sql/benchmark/CometConditionalExpressionBenchmark.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -19,10 +19,6 @@

package org.apache.spark.sql.benchmark

import org.apache.spark.benchmark.Benchmark

import org.apache.comet.CometConf

/**
* Benchmark to measure Comet execution performance. To run this benchmark:
* `SPARK_GENERATE_BENCHMARK_FILES=1 make
Expand All @@ -32,65 +28,26 @@ import org.apache.comet.CometConf
object CometConditionalExpressionBenchmark extends CometBenchmarkBase {

def caseWhenExprBenchmark(values: Int): Unit = {
val benchmark = new Benchmark("Case When Expr", values, output = output)

withTempPath { dir =>
withTempTable("parquetV1Table") {
prepareTable(dir, spark.sql(s"SELECT value AS c1 FROM $tbl"))

val query =
"select CASE WHEN c1 < 0 THEN '<0' WHEN c1 = 0 THEN '=0' ELSE '>0' END from parquetV1Table"

benchmark.addCase("SQL Parquet - Spark") { _ =>
spark.sql(query).noop()
}

benchmark.addCase("SQL Parquet - Comet (Scan)") { _ =>
withSQLConf(CometConf.COMET_ENABLED.key -> "true") {
spark.sql(query).noop()
}
}

benchmark.addCase("SQL Parquet - Comet (Scan, Exec)") { _ =>
withSQLConf(
CometConf.COMET_ENABLED.key -> "true",
CometConf.COMET_EXEC_ENABLED.key -> "true") {
spark.sql(query).noop()
}
}

benchmark.run()
runExpressionBenchmark("Case When Expr", values, query)
}
}
}

def ifExprBenchmark(values: Int): Unit = {
val benchmark = new Benchmark("If Expr", values, output = output)

withTempPath { dir =>
withTempTable("parquetV1Table") {
prepareTable(dir, spark.sql(s"SELECT value AS c1 FROM $tbl"))
val query = "select IF (c1 < 0, '<0', '>=0') from parquetV1Table"

benchmark.addCase("SQL Parquet - Spark") { _ =>
spark.sql(query).noop()
}

benchmark.addCase("SQL Parquet - Comet (Scan)") { _ =>
withSQLConf(CometConf.COMET_ENABLED.key -> "true") {
spark.sql(query).noop()
}
}

benchmark.addCase("SQL Parquet - Comet (Scan, Exec)") { _ =>
withSQLConf(
CometConf.COMET_ENABLED.key -> "true",
CometConf.COMET_EXEC_ENABLED.key -> "true") {
spark.sql(query).noop()
}
}
val query = "select IF (c1 < 0, '<0', '>=0') from parquetV1Table"

benchmark.run()
runExpressionBenchmark("If Expr", values, query)
}
}
}
Expand Down
12 changes: 6 additions & 6 deletions spark/src/test/scala/org/apache/spark/sql/benchmark/CometDatetimeExpressionBenchmark.scala
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Expand Up @@ -39,9 +39,9 @@ object CometDatetimeExpressionBenchmark extends CometBenchmarkBase {
s"select cast(timestamp_micros(cast(value/100000 as integer)) as date) as dt FROM $tbl"))
Seq("YEAR", "YYYY", "YY", "MON", "MONTH", "MM").foreach { level =>
val isDictionary = if (useDictionary) "(Dictionary)" else ""
runWithComet(s"Date Truncate $isDictionary - $level", values) {
spark.sql(s"select trunc(dt, '$level') from parquetV1Table").noop()
}
val name = s"Date Truncate $isDictionary - $level"
val query = s"select trunc(dt, '$level') from parquetV1Table"
runExpressionBenchmark(name, values, query)
}
}
}
Expand All @@ -68,9 +68,9 @@ object CometDatetimeExpressionBenchmark extends CometBenchmarkBase {
"WEEK",
"QUARTER").foreach { level =>
val isDictionary = if (useDictionary) "(Dictionary)" else ""
runWithComet(s"Timestamp Truncate $isDictionary - $level", values) {
spark.sql(s"select date_trunc('$level', ts) from parquetV1Table").noop()
}
val name = s"Timestamp Truncate $isDictionary - $level"
val query = s"select date_trunc('$level', ts) from parquetV1Table"
runExpressionBenchmark(name, values, query)
}
}
}
Expand Down
31 changes: 4 additions & 27 deletions spark/src/test/scala/org/apache/spark/sql/benchmark/CometJsonExpressionBenchmark.scala
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Expand Up @@ -19,7 +19,6 @@

package org.apache.spark.sql.benchmark

import org.apache.spark.benchmark.Benchmark
import org.apache.spark.sql.catalyst.expressions.JsonToStructs

import org.apache.comet.CometConf
Expand Down Expand Up @@ -54,8 +53,6 @@ object CometJsonExpressionBenchmark extends CometBenchmarkBase {
* Generic method to run a JSON expression benchmark with the given configuration.
*/
def runJsonExprBenchmark(config: JsonExprConfig, values: Int): Unit = {
val benchmark = new Benchmark(config.name, values, output = output)

withTempPath { dir =>
withTempTable("parquetV1Table") {
// Generate data with specified JSON patterns
Expand Down Expand Up @@ -119,31 +116,11 @@ object CometJsonExpressionBenchmark extends CometBenchmarkBase {

prepareTable(dir, jsonData)

benchmark.addCase("SQL Parquet - Spark") { _ =>
spark.sql(config.query).noop()
}

benchmark.addCase("SQL Parquet - Comet (Scan)") { _ =>
withSQLConf(CometConf.COMET_ENABLED.key -> "true") {
spark.sql(config.query).noop()
}
}

benchmark.addCase("SQL Parquet - Comet (Scan, Exec)") { _ =>
val baseConfigs =
Map(
CometConf.COMET_ENABLED.key -> "true",
CometConf.COMET_EXEC_ENABLED.key -> "true",
CometConf.getExprAllowIncompatConfigKey(classOf[JsonToStructs]) -> "true",
"spark.sql.optimizer.constantFolding.enabled" -> "false")
val allConfigs = baseConfigs ++ config.extraCometConfigs

withSQLConf(allConfigs.toSeq: _*) {
spark.sql(config.query).noop()
}
}
val extraConfigs = Map(
CometConf.getExprAllowIncompatConfigKey(
classOf[JsonToStructs]) -> "true") ++ config.extraCometConfigs

benchmark.run()
runExpressionBenchmark(config.name, values, config.query, extraConfigs)
}
}
}
Expand Down
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