viirya commented on code in PR #55420:
URL: https://github.com/apache/spark/pull/55420#discussion_r3278041941


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connector/kafka-0-10-sql/src/test/scala/org/apache/spark/sql/kafka010/benchmark/RTMKafkaKafkaBenchmark.scala:
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@@ -0,0 +1,433 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.kafka010.benchmark
+
+import java.io.File
+import java.util.{Properties, Timer, TimerTask}
+import java.util.concurrent.{CountDownLatch, TimeUnit}
+import java.util.concurrent.atomic.{AtomicInteger, AtomicLong}
+
+import scala.concurrent.duration._
+
+import org.apache.kafka.clients.producer.{Callback, KafkaProducer, Producer, 
ProducerRecord, RecordMetadata}
+
+import org.apache.spark.benchmark.{Benchmark, BenchmarkBase}
+import org.apache.spark.internal.Logging
+import org.apache.spark.sql.{Column, SparkSession}
+import org.apache.spark.sql.execution.streaming.RealTimeTrigger
+import org.apache.spark.sql.functions._
+import org.apache.spark.sql.internal.SQLConf
+import org.apache.spark.sql.kafka010.KafkaTestUtils
+import org.apache.spark.sql.streaming.StreamingQueryListener
+import org.apache.spark.util.Utils
+
+/**
+ * Stateless Kafka-to-Kafka RTM benchmark. Reads from an input Kafka topic, 
applies a
+ * stateless transformation, and writes results to an output Kafka topic using
+ * [[RealTimeTrigger]]. After the run it reports e2e latency percentiles.
+ *
+ * The benchmark spins up a real local-cluster Spark context and a live 
embedded Kafka
+ * broker, so a single run takes several minutes.
+ *
+ * Unlike most Spark benchmarks, this one does not use `Benchmark.run()` / 
`addCase`: the
+ * metric of interest is end-to-end latency percentiles across a streaming 
pipeline, which
+ * does not fit the Best/Avg/Stdev table format. The JVM/OS/processor header 
that
+ * `Benchmark.run()` would normally emit is therefore written manually in
+ * `printLatenciesTable` for consistency with other benchmark result files.
+ *
+ * To run this benchmark:
+ * {{{
+ *   1. without sbt:
+ *      bin/spark-submit --class <this class>
+ *        --jars <spark core test jar>,<spark sql test jar> <spark sql kafka 
0-10 test jar>
+ *   2. build/sbt "sql-kafka-0-10/Test/runMain <this class>"
+ *   3. generate result:
+ *      SPARK_GENERATE_BENCHMARK_FILES=1 build/sbt 
"sql-kafka-0-10/Test/runMain <this class>"
+ *      Results will be written to:
+ *      
"connector/kafka-0-10-sql/benchmarks/RTMKafkaKafkaBenchmark-results.txt".
+ * }}}
+ *
+ * See `benchmarks/RTMKafkaKafkaBenchmark-results.txt` for a recorded run.
+ */
+object RTMKafkaKafkaBenchmark extends BenchmarkBase with Logging {
+
+  // ----- Benchmark dimensions -----
+
+  // Checkpoint interval for the streaming query. 5-minute is recommended.
+  // Lowering it may cause more frequent checkpointing but can increase 
latency.
+  private val checkpointInterval = 5.minutes

Review Comment:
   I think I see what you mean: in RTM, batches run for a fixed amount of time, 
and the batch boundary is also where progress/checkpoint-like work is 
committed, so this duration effectively influences the checkpoint/progress 
cadence.
   
   That said, since this value is passed directly to RealTimeTrigger(...), 
whose API names it batchDurationMs, I think calling the benchmark variable 
checkpointInterval is still a bit misleading. A reader may assume it is a 
checkpoint-specific configuration rather than the RTM batch duration.
   
   Could we name it realTimeBatchDuration or batchDuration, and keep your point 
in the comment? For example:
   
   ```
   // Duration of each RTM batch. Since RTM commits progress/checkpoints at 
batch
   // boundaries, this also controls the effective checkpoint/progress cadence.
   private val realTimeBatchDuration = 5.minutes
   ```
   
   This keeps the variable aligned with the public API while still explaining 
the RTM checkpoint/progress behavior.
   
   
   
   
   
   



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