Review fix

Author: gaborgsomogyi

docs/structured-streaming-programming-guide.md

@@ -553,7 +553,7 @@ Here are the details of all the sources in Spark.
         NOTE: Both archiving (via moving) or deleting completed files will introduce overhead (slow down, even if it's happening in separate thread) in each micro-batch, so you need to understand the cost for each operation in your file system before enabling this option. On the other hand, enabling this option will reduce the cost to list source files which can be an expensive operation.<br/>
         Number of threads used in completed file cleaner can be configured with<code>spark.sql.streaming.fileSource.cleaner.numThreads</code>.<br/>
         NOTE 2: The source path should not be used from multiple sources or queries when enabling this option.<br/>
-        NOTE 3: Both delete and move actions are best effort. Failing to delete or move files will not fail the streaming query.
+        NOTE 3: Both delete and move actions are best effort. Failing to delete or move files will not fail the streaming query. Spark may not clean up some source files in some circumstances - e.g. the application doesn't shut down gracefully, too many files are queued to clean up.
         <br/><br/>
         For file-format-specific options, see the related methods in <code>DataStreamReader</code>
         (<a href="api/scala/index.html#org.apache.spark.sql.streaming.DataStreamReader">Scala</a>/<a href="api/java/org/apache/spark/sql/streaming/DataStreamReader.html">Java</a>/<a href="api/python/pyspark.sql.html#pyspark.sql.streaming.DataStreamReader">Python</a>/<a

sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/FileStreamSource.scala

@@ -350,7 +350,7 @@ object FileStreamSource {
       SQLConf.get.getConf(SQLConf.FILE_SOURCE_CLEANER_NUM_THREADS)
     )
 
-    def stop(): Unit = cleanThreadPool.shutdown()
+    def stop(): Unit = ThreadUtils.shutdown(cleanThreadPool)
 
     def clean(entry: FileEntry): Unit
   }