chaoqin-li1123 commented on code in PR #46651:
URL: https://github.com/apache/spark/pull/46651#discussion_r1606249464
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sql/core/src/test/scala/org/apache/spark/sql/execution/python/PythonStreamingDataSourceSuite.scala:
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@@ -763,6 +799,36 @@ class PythonStreamingDataSourceSuite extends
PythonDataSourceSuiteBase {
}
}
+ // Verify that commit runner work correctly with large timeout interval.
+ test(s"data source stream write, trigger interval=20 seconds") {
+ assume(shouldTestPandasUDFs)
+ val dataSource =
+ createUserDefinedPythonDataSource(dataSourceName,
simpleDataStreamWriterScript)
+ spark.dataSource.registerPython(dataSourceName, dataSource)
+ val inputData = MemoryStream[Int](numPartitions = 3)
+ val df = inputData.toDF()
+ withTempDir { dir =>
+ val path = dir.getAbsolutePath
+ val checkpointDir = new File(path, "checkpoint")
+ checkpointDir.mkdir()
+ val outputDir = new File(path, "output")
+ outputDir.mkdir()
+ val q = df
+ .writeStream
+ .format(dataSourceName)
+ .option("checkpointLocation", checkpointDir.getAbsolutePath)
+ .trigger(ProcessingTimeTrigger(20 * 1000))
+ .start(outputDir.getAbsolutePath)
+ eventually(timeout(waitTimeout * 5)) {
+ inputData.addData(1 to 3)
Review Comment:
A batch in memory stream actually doesn't correspond to a
microbatch(https://github.com/apache/spark/blob/88eb9ebe8524676631c6a4a6cfaf9172acd23818/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/memory.scala#L231),
but I figure out a way to do something similar.
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