HeartSaVioR commented on code in PR #38517:
URL: https://github.com/apache/spark/pull/38517#discussion_r1049119941
##########
connector/kafka-0-10-sql/src/test/scala/org/apache/spark/sql/kafka010/KafkaMicroBatchSourceSuite.scala:
##########
@@ -195,6 +200,102 @@ abstract class KafkaMicroBatchSourceSuiteBase extends
KafkaSourceSuiteBase {
true
}
+ /**
+ * Test async progress tracking capability with Kafka source and sink
+ */
+ test("async progress tracking") {
+ val inputTopic = newTopic()
+ testUtils.createTopic(inputTopic, partitions = 5)
+
+ val dataSent = new ListBuffer[String]()
+ testUtils.sendMessages(inputTopic, (0 until 15).map { case x =>
+ val m = s"foo-$x"
+ dataSent += m
+ m
+ }.toArray, Some(0))
+
+ val outputTopic = newTopic()
+ testUtils.createTopic(outputTopic, partitions = 5)
+
+ withTempDir { dir =>
+ val reader = spark
+ .readStream
+ .format("kafka")
+ .option("kafka.bootstrap.servers", testUtils.brokerAddress)
+ .option("kafka.metadata.max.age.ms", "1")
+ .option("maxOffsetsPerTrigger", 5)
+ .option("subscribe", inputTopic)
+ .option("startingOffsets", "earliest")
+ .load()
+
+ def startQuery(): StreamingQuery = {
+ reader.writeStream
+ .format("kafka")
+ .option("checkpointLocation", dir.getCanonicalPath)
+ .option("kafka.bootstrap.servers", testUtils.brokerAddress)
+ .option("kafka.max.block.ms", "5000")
+ .option("topic", outputTopic)
+ .option(ASYNC_PROGRESS_TRACKING_ENABLED, true)
+ .option(ASYNC_PROGRESS_TRACKING_CHECKPOINTING_INTERVAL_MS, 1000)
+ .queryName("kafkaStream")
+ .start()
+ }
+
+ def readResults(): ListBuffer[String] = {
Review Comment:
The output would be same but the code and actual execution would be much
simpler in batch query. See below code when we just go with batch query:
```
val data = spark.read.format("kafka")...load().select("CAST(value AS
string)").toDS().collect().map(_._1)
```
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