Hi Aljoscha,
Thanks.
I have used the following code for testing:
main
keyedStream.keyBy(4)
.window(SlidingEventTimeWindows.of(Time.minutes6), Time.minutes(2))) // 6
min window with 2 min sliding window
.apply(new CustomSlidingWindowFunction());
keyedStream.addSink(new SinkFunction<Tuple5<String, String, Float, Float,
String>>() {
/**
*
*/
private static final long serialVersionUID = 1L;
public void invoke(Tuple5<String, String, Float, Float, String> value) {
System.out.println(value.f1.toString().trim()+", " +
value.f0 + ", "+value.f2 + ", " + value.f3);
}
});
in WindowFunction apply
...
// Condition for selecting a window
if(d.after(x) && d.before(y)){
for (Tuple5<String, String, Float,
Float, String> tr: input){
// Write the window to Collector
out.collect(new Tuple5<>(tr.f0, tr.f1, tr.f2, tr.f3, tr.f4));
}
I am getting all input records instead of those windows selected by
the condition. Is there something I am doing wrong? Does this need to be
done in a different way?
Please let me know.
Thanks.
*Sujit Sakre*
Senior Technical Architect
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Please consider the environment before printing this email
On 10 January 2017 at 20:24, Aljoscha Krettek <aljos...@apache.org> wrote:
> Hi,
> instead of writing to files, could you please simply output a value using
> the Collector and then write the result stream of the window operation to a
> sink (such as a file sink) to see how many windows are being processed.
> Having side effects (especially output) in user functions can lead to
> programs with quite unexpected behaviour and I would highly discourage
> doing that.
>
> Cheers,
> Aljoscha
>
> On Tue, 10 Jan 2017 at 13:44 Sujit Sakre <sujit.sa...@northgateps.com>
> wrote:
>
>> Hi,
>>
>> In the link (http://stackoverflow.com/questions/41143518/sliding-
>> processing-time-window-computes-inconsistent-results), Fabian has
>> mentioned that if Event Time is used, consistent results are possible.
>>
>> However, that's not the case with us. We are getting very random results.
>>
>> Please suggest.
>>
>>
>> *Sujit Sakre*
>>
>>
>> On 9 January 2017 at 22:27, Sujit Sakre <sujit.sa...@northgateps.com>
>> wrote:
>>
>> 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.
>>
>>
>> *Sujit Sakre*
>>
>>
>>
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