yaooqinn commented on code in PR #44849:
URL: https://github.com/apache/spark/pull/44849#discussion_r1464211489
##########
connector/avro/src/test/scala/org/apache/spark/sql/execution/benchmark/AvroWriteBenchmark.scala:
##########
@@ -52,12 +54,48 @@ object AvroWriteBenchmark extends DataSourceWriteBenchmark {
// cache the data to ensure we are not benchmarking range or
repartition
df.noop()
df.createOrReplaceTempView("t1")
- val benchmark = new Benchmark(s"Write wide rows into $files files",
values, output = output)
- benchmark.addCase("Write wide rows") { _ =>
- spark.sql("SELECT * FROM t1").
-
write.format("avro").save(s"${dir.getCanonicalPath}/${Random.nextLong().abs}")
+
+ def addBenchmark(
+ benchmark: Benchmark,
+ codec: String,
+ conf: Map[String, String] = Map.empty): Unit = {
+ val name = conf.map(kv => kv._1.stripPrefix("spark.sql.avro.") + "="
+ kv._2)
+ .mkString(codec + ": ", ", ", "")
+ benchmark.addCase(name) { _ =>
+ withSQLConf(conf.toSeq: _*) {
+ spark
+ .table("t1")
+ .write
+ .option("compression", codec)
+ .format("avro")
+ .save(s"${dir.getCanonicalPath}/${Random.nextLong().abs}")
+ }
+ }
+ }
+
+ val bm = new Benchmark(s"Avro compression with different codec",
values, output = output)
+ AvroCompressionCodec.values().sortBy(_.getCodecName).foreach { codec =>
+ addBenchmark(bm, codec.name)
+ }
+ bm.run()
+
+
AvroCompressionCodec.values().filter(_.getSupportCompressionLevel).foreach {
codec =>
+ val bm = new Benchmark(
+ s"Avro ${codec.getCodecName} with different levels", values,
output = output)
+ Seq(1, 3, 5, 7, 9).foreach { level =>
+ val conf = Map(s"spark.sql.avro.${codec.getCodecName}.level" ->
level.toString)
+ addBenchmark(bm, codec.name, conf)
+ if (codec == AvroCompressionCodec.ZSTANDARD) {
+ val nondft =
Review Comment:
Yes, I hope the name doesn't bother you too much.：）
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