During testing you will typically be using some finite data. You want the stream to shut down automatically when that data has been consumed so your test shuts down gracefully.
Of course once the code is running in production you'll want it to keep waiting for new records. So whether the stream shuts down when there's no more data should be configurable. On Tue, Feb 23, 2016 at 11:09 AM, Ashutosh Kumar <kmr.ashutos...@gmail.com> wrote: > Just out of curiosity I will like to know why a streaming program should > shutdown when no new data is arriving? I think it should keep waiting for > arrival of new records. > > Thanks > Ashutosh > > On Tue, Feb 23, 2016 at 9:17 PM, Hemant Bhanawat <hemant9...@gmail.com> > wrote: > >> A guess - parseRecord is returning None in some case (probaly empty >> lines). And then entry.get is throwing the exception. >> >> You may want to filter the None values from accessLogDStream before you >> run the map function over it. >> >> Hemant >> >> Hemant Bhanawat <https://www.linkedin.com/in/hemant-bhanawat-92a3811> >> www.snappydata.io >> >> On Tue, Feb 23, 2016 at 6:00 PM, Ted Yu <yuzhih...@gmail.com> wrote: >> >>> Which line is line 42 in your code ? >>> >>> When variable lines becomes empty, you can stop your program. >>> >>> Cheers >>> >>> On Feb 23, 2016, at 12:25 AM, Femi Anthony <femib...@gmail.com> wrote: >>> >>> I am working on Spark Streaming API and I wish to stream a set of >>> pre-downloaded web log files continuously to simulate a real-time stream. I >>> wrote a script that gunzips the compressed logs and pipes the output to nc >>> on port 7777. >>> >>> The script looks like this: >>> >>> BASEDIR=/home/mysuer/data/datamining/internet_traffic_archive >>> zipped_files=`find $BASEDIR -name "*.gz"` >>> >>> for zfile in $zipped_files >>> do >>> echo "Unzipping $zfile..." >>> gunzip -c $zfile | nc -l -p 7777 -q 20 >>> >>> done >>> >>> I have streaming code written in Scala that processes the streams. It >>> works well for the most part, but when its run out of files to stream I get >>> the following error in Spark: >>> >>> 16/02/19 23:04:35 WARN ReceiverSupervisorImpl: >>> Restarting receiver with delay 2000 ms: Socket data stream had no more data >>> 16/02/19 23:04:35 ERROR ReceiverTracker: Deregistered receiver for stream 0: >>> Restarting receiver with delay 2000ms: Socket data stream had no more data >>> 16/02/19 23:04:35 WARN BlockManager: Block input-0-1455941075600 replicated >>> to only 0 peer(s) instead of 1 peers >>> .... >>> 16/02/19 23:04:40 ERROR Executor: Exception in task 2.0 in stage 15.0 (TID >>> 47) >>> java.util.NoSuchElementException: None.get >>> at scala.None$.get(Option.scala:313) >>> at scala.None$.get(Option.scala:311) >>> at >>> com.femibyte.learningsparkaddexamples.scala.StreamingLogEnhanced$$anonfun$2.apply(StreamingLogEnhanced.scala:42) >>> at >>> com.femibyte.learningsparkaddexamples.scala.StreamingLogEnhanced$$anonfun$2.apply(StreamingLogEnhanced.scala:42) >>> >>> How to I implement a graceful shutdown so that the program exits >>> gracefully when it no longer detects any data in the stream ? >>> >>> My Spark Streaming code looks like this: >>> >>> object StreamingLogEnhanced { >>> def main(args: Array[String]) { >>> val master = args(0) >>> val conf = new >>> SparkConf().setMaster(master).setAppName("StreamingLogEnhanced") >>> // Create a StreamingContext with a n second batch size >>> val ssc = new StreamingContext(conf, Seconds(10)) >>> // Create a DStream from all the input on port 7777 >>> val log = Logger.getLogger(getClass.getName) >>> >>> sys.ShutdownHookThread { >>> log.info("Gracefully stopping Spark Streaming Application") >>> ssc.stop(true, true) >>> log.info("Application stopped") >>> } >>> val lines = ssc.socketTextStream("localhost", 7777) >>> // Create a count of log hits by ip >>> var ipCounts=countByIp(lines) >>> ipCounts.print() >>> >>> // start our streaming context and wait for it to "finish" >>> ssc.start() >>> // Wait for 600 seconds then exit >>> ssc.awaitTermination(10000*600) >>> ssc.stop() >>> } >>> >>> def countByIp(lines: DStream[String]) = { >>> val parser = new AccessLogParser >>> val accessLogDStream = lines.map(line => parser.parseRecord(line)) >>> val ipDStream = accessLogDStream.map(entry => >>> (entry.get.clientIpAddress, 1)) >>> ipDStream.reduceByKey((x, y) => x + y) >>> } >>> >>> } >>> >>> Thanks for any suggestions in advance. >>> >>> >> >
