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From Chao Wang <chaow...@wustl.edu>
Subject Re: Experiencing long latency while using sockets
Date Wed, 09 Aug 2017 20:52:42 GMT
It seems that the observed long latencies were due to certain one-time 
internal mechanism that only occurred after Flink has received the first 
message. Based on my measurement that mechanism took around 100 ms.

Now I setup my application the following way, and I observed that the 
end-to-end latency is similar to that of using raw sockets (off by less 
than 1 ms): Send the first message to Flink and then wait for 110 ms 
before sending the second message. And for the subsequent sends we can 
remove the 110 ms wait.


Chao

On 08/09/2017 10:57 AM, Chao Wang wrote:
>
> Thank you, Fabian.
>
> Maybe there's also some buffers sit between data source and the first 
> operator? I observed that in my implementation of SourceFunction 
> (using a socket server, as listed in the previous email), for 
> receiving two messages, in terms of event time, it took 0.2 ms before 
> the SourceFunction receives the first message but then it took 97 ms 
> to receive the second message. The interval between the two sends is 
> 0.07 ms at the sending side, which is a java socket client.
>
> Or could it be that there is a timeout setting for scheduling data 
> source in Flink?
>
>
> Thanks,
>
> Chao
>
>
> On 08/08/2017 02:58 AM, Fabian Hueske wrote:
>> One pointer is the StreamExecutionEnvironment.setBufferTimeout() 
>> parameter.
>> Flink's network stack collects records in buffers to send them over 
>> the network. A buffer is sent when it is completely filled or after a 
>> configurable timeout.
>> So if your program does not process many records, these records might 
>> "get stuck" in the buffers and be emitted after the timeout flushes 
>> the buffer.
>> The default timeout is 100ms. Try to reduce it.
>>
>> Best, Fabian
>>
>> 2017-08-08 1:06 GMT+02:00 Chao Wang <chaowang@wustl.edu 
>> <mailto:chaowang@wustl.edu>>:
>>
>>     Following the original post, I've tried stripping down my Flink
>>     app to only the following, and then it still exhibits long
>>     latencies: after the second source socket write, it took 90+
>>     milliseconds from data source to the socket-front in Flink. I
>>     would like to ask for pointers about how to investigate the
>>     latency issue like this, and in general how to properly benchmark
>>     Flink latencies. Thank you very much!
>>
>>
>>     The main method:
>>
>>
>>       public static void main(String[] args) throws Exception {
>>         final StreamExecutionEnvironment env =
>>     StreamExecutionEnvironment.getExecutionEnvironment();
>>         DataStream<EventGroup> inEventGroupStream = env.addSource(new
>>     SocketEventGroupStreamFunction(6065, 512));
>>         inEventGroupStream.writeToSocket("DestHost", 6066, new
>>     MySeGroup<EventGroup>());
>>         env.execute("event processing");
>>      }
>>
>>
>>     where all the custom classes are as follows (for
>>     serialization/deserialization and socket server functionality):
>>
>>
>>       public static class MySeGroup<T> implements
>>     SerializationSchema<EventGroup> {
>>
>>         @Override
>>         public byte[] serialize(EventGroup arg0) {
>>           int tLength = EKFFFTAES.getSizeTimepoint();
>>           //Note: report error if tLength != arg0.getT().length
>>           if (tLength != arg0.getT().length) {
>>             System.out.println ("Serialization error: Timepoint size
>>     discrepancy.");
>>             System.out.println ("tLength = " + tLength);
>>             System.out.println ("arg0.getT().length = " +
>>     arg0.getT().length);
>>           }
>>           byte[] buffer = new byte[1 + arg0.getT().length +
>>     arg0.getP().length];
>>           buffer[0] = arg0.type;
>>           System.arraycopy(arg0.getT(), 0, buffer, 1, tLength);
>>           System.arraycopy(arg0.getP(), 0, buffer, 1 + tLength,
>>     arg0.getP().length);
>>           return buffer;
>>         }
>>       }
>>
>>       public static class Event extends
>>     SimpleImmutableEntry<byte[],byte[]> {
>>
>>         Event(byte[] timestamp, byte[] payload){
>>           super(timestamp, payload);
>>         }
>>         public byte[] getT() { // get the timestamp
>>           return getKey();
>>         }
>>         public byte[] getP() { // get the payload
>>           return getValue();
>>         }
>>       }
>>
>>       public static class EventGroup extends Event {
>>         public byte type;
>>         EventGroup(byte type, byte[] timestamp, byte[] payload){
>>           super(timestamp, payload);
>>           this.type = type;
>>         }
>>       }
>>
>>
>>       public static class SocketEventGroupStreamFunction implements
>>     SourceFunction<EventGroup> {
>>
>>         private transient ServerSocket serverSocket;
>>         private int serverPort;
>>         private int dataLength;
>>         private byte[] inbuf;
>>         private byte[] timestamp;
>>         private byte[] payload;
>>         private int tLength = EKFFFTAES.getSizeTimepoint();
>>         private volatile boolean isRunning = true;
>>
>>         public SocketEventGroupStreamFunction(int port, int length) {
>>           serverPort = port;
>>           dataLength = length;
>>           inbuf = new byte[1 + dataLength + tLength];
>>           timestamp = new byte[tLength];
>>           payload = new byte[dataLength];
>>         }
>>
>>         @Override
>>         public void run(SourceContext<EventGroup> ctx) throws Exception {
>>           while(isRunning) {
>>             serverSocket = new ServerSocket(serverPort, 100,
>>     InetAddress.getByName("192.168.1.13"));
>>             serverSocket.setSoTimeout(1000000);
>>             System.out.println("Waiting for incoming connections on
>>     port " +
>>               serverSocket.getLocalPort() + "...");
>>             Socket server = serverSocket.accept();
>>
>>             System.out.println("Just connected to " +
>>     server.getRemoteSocketAddress());
>>             DataInputStream in = new
>>     DataInputStream(server.getInputStream());
>>
>>             while(isRunning) {
>>               in.readFully(inbuf, 0, inbuf.length);
>>               System.arraycopy(inbuf, 1, timestamp, 0, tLength);
>>               System.arraycopy(inbuf, 1+tLength, payload, 0, dataLength);
>>
>>               System.out.print("Got an event " + inbuf[0] + ": ");
>>               displayElapsedTime(timestamp);
>>
>>               ctx.collect(new EventGroup(inbuf[0], timestamp, payload));
>>             }
>>           }
>>         }
>>
>>         @Override
>>         public void cancel() {
>>           isRunning = false;
>>           ServerSocket theSocket = this.serverSocket;
>>           if (theSocket != null) {
>>             try {
>>               theSocket.close();
>>             }catch(SocketTimeoutException s) {
>>               System.out.println("Socket timed out!");
>>             }catch(IOException e) {
>>               e.printStackTrace();
>>             }
>>           }
>>         }
>>       }
>>
>>
>>     and finally, EKFFFTAES is my cpp library implementing the
>>     timestamping facility:
>>
>>
>>     int timePointLength = sizeof(std::chrono::system_clock::time_point);
>>
>>     JNIEXPORT jint JNICALL
>>     Java_eventProcessing_EKFFFTAES_getSizeTimepoint
>>       (JNIEnv *, jclass)
>>     {
>>       return ::timePointLength;
>>     }
>>
>>     JNIEXPORT void JNICALL
>>     Java_eventProcessing_EKFFFTAES_displayElapsedTime
>>       (JNIEnv *env, jclass, jbyteArray inArray)
>>     {
>>       std::chrono::system_clock::time_point end =
>>         std::chrono::system_clock::now();
>>       jbyte *inCArray = env->GetByteArrayElements(inArray, NULL);
>>       std::chrono::system_clock::time_point start;
>>       std::memcpy (&start, inCArray, ::timePointLength);
>>       std::cout <<
>>     std::chrono::duration_cast<std::chrono::microseconds>(end -
>>     start).count() << std::endl;
>>     }
>>
>>
>>     Thank you,
>>
>>     Chao
>>
>>
>>     On 08/07/2017 03:20 PM, Chao Wang wrote:
>>
>>         Hi,
>>
>>         I have been trying to benchmark the end-to-end latency of a
>>         Flink 1.3.1 application, but got confused regarding the
>>         amount of time spent in Flink. In my setting, data source and
>>         data sink dwell in separated machines, like the following
>>         topology:
>>
>>         Machine 1 Machine 2      Machine 3
>>         data source (via a socket client)   ->      Flink ->    data
>>         sink (via a socket server)
>>
>>         I observed 200-400 milliseconds end-to-end latency, while the
>>         execution time of my stream transformations took no more than
>>         two milliseconds, and the socket-only networking latency
>>         between machines is no more than one millisecond, and I used
>>         ptpd so that the clock offset between machines were also no
>>         more than one millisecond.
>>
>>         Question: What took those hundreds of milliseconds?
>>
>>         Here are the details of my setting and my observation so far:
>>
>>         On Machine 2, I implemented a socket server as a data source
>>         to Flink (by implementing SourceFunction), and I splited the
>>         incoming stream into several streams (by SplitStream) for
>>         some transformations (implementing MapFuction and
>>         CoFlatMapFunction), where the results were fed to socket
>>         (using writeToSocket). I used c++11's chrono time library
>>         (through JNI) to take timestamps and determine the elapsed
>>         time, and I have verified that the overhead of timestamping
>>         this way is no more than one millisecond.
>>
>>         I observed that for the four consecutive writes from Machine
>>         1, with the time between two writes no more than 0.3
>>         milliseconds, on Machine 2 Flink got the first write in 0.2
>>         milliseconds, but then it took 90 milliseconds for Flink to
>>         get the next write, and another 4 milliseconds for the third
>>         write, and yet another 4 milliseconds for the fourth write.
>>
>>         And then it took more than 70 milliseconds before Flink
>>         started processing my plan's first stream transformation. And
>>         after my last transformation, it took more than 70
>>         milliseconds before the result was received at Machine 3.
>>
>>
>>         Thank you,
>>
>>         Chao
>>
>>
>>
>>
>


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