Sliding Event Time Window Processing: Window Function inconsistent behavior

[Sujit Sakre]

Hi,

We are using Sliding Event Time Window with Kafka Consumer. The window size is 6 minutes, and slide is 2 minutes. We have written a window function to select a particular window out of multiple windows for a keyed stream, e.g. we select about 16 windows out of multiple windows for the keyed stream based on a particular condition. 

Upon a normal execution, we get 16 windows for processing inside the condition (in window function mentioned). These windows we are putting in different files, named after window start and end times.

the code is as below:

Calling code

public class RealTimeProcessingSlidingWindow{

public static void main(String[] args) throws Exception {

// set up the execution environment

StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

env.setStreamTimeCharacteristic(TimeCharacteristic.EventTime);

// configure the Kafka consumer

Properties kafkaProps = new Properties();

kafkaProps.setProperty("zookeeper.connect", LOCAL_ZOOKEEPER_HOST);

kafkaProps.setProperty("bootstrap.servers", LOCAL_KAFKA_BROKER);

kafkaProps.setProperty("group.id", DEMO_GROUP);

// always read the Kafka topic from the start

kafkaProps.setProperty("auto.offset.reset" ,"earliest");

                FlinkKafkaConsumer09<Tuple5<String, String, Float, Float, String>> consumer = new FlinkKafkaConsumer09<>(

"test",            // kafka topic name

new dataSchema(),

kafkaProps);

                DataStream<Tuple5<String, String, Float, Float, String>> stream1 = env.addSource(consumer);

                DataStream<Tuple5<String, String, Float, Float, String>> keyedStream = stream1.assignTimestampsAndWatermarks(new BoundedOutOfOrdernessGenerator2());

                keyedStream.keyBy(4)

.window(SlidingEventTimeWindows.of(Time.minutes6), Time.minutes(2)))   // 6 min window with 2 min sliding window

.apply(new CustomSlidingWindowFunction());

                env.execute("Sliding Event Time Window Processing");

           }

}

public static class CustomSlidingWindowFunction implements WindowFunction<Tuple5<String, String, Float, Float, String>, Tuple5<String, String, Float, Float, String>, Tuple, TimeWindow>{

@Override

public void apply(Tuple key, TimeWindow window, Iterable<Tuple5<String, String, Float, Float, String>> input,

Collector<Tuple5<String, String, Float, Float, String>> out) throws Exception {

HashMap<String, Tuple5<String, String, Float, Float, String>> windowMap= new HashMap<String,Tuple5<String, String, Float, Float, String>>();

for (Tuple5<String, String, Float, Float, String> wr: input){

windowMap.put(wr.f1.toString().trim(), wr);

}

                        ...

SimpleDateFormat sf = new SimpleDateFormat(IndianDateTimeFormat);

if(windowMap.containsKey(tk)){

Tuple5<String, String, Float, Float, String> t = (Tuple5<String, String, Float, Float, String>) windowMap.get(tk);

Date d = sf.parse(t.f0.trim());

                                ...

                                // Condition for selecting a window

if(d.after(x) && d.before(y)){

// Write the window output to separate files named after window Lat and Lon

writeWindowToFile(t, window, input);

                                    }

                         }

                }

        }

// Get the buffered writer

private static synchronized BufferedWriter getWriter(String fileName) throws IOException{

return new BufferedWriter(new FileWriter(fileName, true));

}

// Writes an entire window to file for the records in that window

private static synchronized void writeWindowToFile(Tuple5<String, String, Float, Float, String> target, TimeWindow window, Iterable<Tuple5<String, String, Float, Float, String>> input) throws IOException{

// Create a file to write a window to

String fileName = target.f2.toString() + "-" + target.f3.toString()+".csv";

BufferedWriter br = getWriter(fileName);

// Iterate and put the records in file

for (Tuple5<String, String, Float, Float, String> tr: input){

br.write(tr.f1.toString().trim()+", "+

convertLongIntoDate(window.getStart())+", "+convertLongIntoDate(window.getEnd())+", "+

tr.f0+", "+tr.f2+", "+tr.f3+'\n');

}

// flush the writer and close it

br.close();

}

We have written the code to be threadsafe while creating and writing to file

In this code, If we execute the code multiple times on the Kafka Stream (with certain records) most times we get 16 files with corresponding window records, which is the correct behavior.

However sometimes only 4 files get created or 1 file or any number less than 16 gets created randomly, this is anomalous behavior.

What could be the cause of such behavior? How do we resolve this?

Please, could you identify and suggest a solution/s.

Thanks.

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