HeartSaVioR commented on a change in pull request #33763:
URL: https://github.com/apache/spark/pull/33763#discussion_r699727889
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File path:
sql/core/src/test/scala/org/apache/spark/sql/streaming/FileStreamSourceSuite.scala
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@@ -1304,6 +1304,140 @@ class FileStreamSourceSuite extends
FileStreamSourceTest {
}
}
+ test("SPARK-36533: Trigger.AvailableNow") {
+ withTempDirs { (src, target) =>
+ val checkpoint = new File(target, "chk").getCanonicalPath
+ val targetDir = new File(target, "data").getCanonicalPath
+ var lastFileModTime: Option[Long] = None
+
+ /** Create a text file with a single data item */
+ def createFile(data: Int): File = {
+ val file = stringToFile(new File(src, s"$data.txt"), data.toString)
+ if (lastFileModTime.nonEmpty) file.setLastModified(lastFileModTime.get
+ 1000)
+ lastFileModTime = Some(file.lastModified)
+ file
+ }
+
+ createFile(1)
+ createFile(2)
+ createFile(3)
+
+ // Set up a query to read text files one at a time
+ val df = spark
+ .readStream
+ .option("maxFilesPerTrigger", 1)
+ .text(src.getCanonicalPath)
+
+ def startQuery(): StreamingQuery = {
+ df.writeStream
+ .format("parquet")
+ .trigger(Trigger.AvailableNow)
+ .option("checkpointLocation", checkpoint)
+ .start(targetDir)
+ }
+ val q = startQuery()
+
+ try {
+ assert(q.awaitTermination(streamingTimeout.toMillis))
+ assert(q.recentProgress.count(_.numInputRows != 0) == 3)
+ checkAnswer(sql(s"SELECT * from parquet.`$targetDir`"), (1 to
3).map(_.toString).toDF)
+ } finally {
+ q.stop()
+ }
+
+ createFile(4)
+ createFile(5)
+
+ // run a second query
+ val q2 = startQuery()
+ try {
+ assert(q2.awaitTermination(streamingTimeout.toMillis))
+ assert(q2.recentProgress.count(_.numInputRows != 0) == 2)
+ checkAnswer(sql(s"SELECT * from parquet.`$targetDir`"), (1 to
5).map(_.toString).toDF)
+ } finally {
+ q2.stop()
+ }
+ }
+ }
+
+ test("SPARK-36533: Trigger.AvailableNow - checkpointing") {
+ withTempDirs { (src, target) =>
+ val checkpoint = new File(target, "chk").getCanonicalPath
+ var lastFileModTime: Option[Long] = None
+
+ /** Create a text file with a single data item */
+ def createFile(data: Int): File = {
+ val file = stringToFile(new File(src, s"$data.txt"), data.toString)
+ if (lastFileModTime.nonEmpty) file.setLastModified(lastFileModTime.get
+ 1000)
+ lastFileModTime = Some(file.lastModified)
+ file
+ }
+
+ createFile(1)
+ createFile(2)
+ createFile(3)
+
+ // Set up a query to read text files one at a time
+ val df = spark
+ .readStream
+ .option("maxFilesPerTrigger", 1)
+ .text(src.getCanonicalPath)
+
+ def startTriggerOnceQuery(): StreamingQuery = {
+ df.writeStream
+ .foreachBatch((_: Dataset[Row], _: Long) => {})
+ .trigger(Trigger.Once)
+ .option("checkpointLocation", checkpoint)
+ .start()
+ }
+
+ // run a query with Trigger.Once first
+ val q = startTriggerOnceQuery()
+
+ try {
+ assert(q.awaitTermination(streamingTimeout.toMillis))
+ } finally {
+ q.stop()
+ }
+
+ var index = 3 // We have processed the first 3 rows in the first query
Review comment:
nit: probably better to add the comment that it tracks the number of
micro-batch execution starting from here. The code is intuitive but worth
having elaboration given the importance of this variable.
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