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
