Thanks for the information. Strange enough, after I set the time
characteristic to EventTime, the events are leaking into the previous
window:
...
Mon, 04 Jul 2016 19:10:49 CST
Mon, 04 Jul 2016 19:10:50 CST # ?
Mon, 04 Jul 2016 19:10:50 CST
Mon, 04 Jul 2016 19:10:50 CST
Mon, 04 Jul 2016 19:10:50 CST
Mon, 04 Jul 2016 19:10:50 CST
Mon, 04 Jul 2016 19:10:50 CST
100 events in this window
Mon, 04 Jul 2016 19:10:50 CST
Mon, 04 Jul 2016 19:10:50 CST
Mon, 04 Jul 2016 19:10:50 CST
Mon, 04 Jul 2016 19:10:50 CST
Mon, 04 Jul 2016 19:10:51 CST
Mon, 04 Jul 2016 19:10:51 CST
On 4 July 2016 at 16:15, Aljoscha Krettek <aljos...@apache.org> wrote:
> Hi,
> I think it should be as simple as setting event time as the stream time
> characteristic:
>
> env.setStreamTimeCharacteristic(TimeCharacteristic.EventTime)
>
> The problem is that .timeWindow(Time.seconds(10)) will use processing time
> if you don't specify a time characteristic. You can enforce using an
> event-time window using this:
>
> stream.window(EventTimeTumblingWindows.of(Time.seconds(10)))
>
> Cheers,
> Aljoscha
>
>
> On Mon, 4 Jul 2016 at 06:00 Yukun Guo <gyk....@gmail.com> wrote:
>
>> Hi,
>>
>> I wrote a program which constructs a WindowedStream to compute periodic
>> data statistics every 10 seconds. However, I found that events have not
>> been strictly grouped into windows of 10s duration, i.e., some events are
>> leaking into the adjacent window.
>>
>> The output is like this:
>>
>> Mon, 04 Jul 2016 11:11:50 CST # 1
>> Mon, 04 Jul 2016 11:11:50 CST # 2
>> # removed for brevity
>> Mon, 04 Jul 2016 11:11:59 CST # 99
>> 99 events in this window
>> Mon, 04 Jul 2016 11:11:59 CST # This event has been put in the wrong
>> window
>> Mon, 04 Jul 2016 11:12:00 CST
>>
>> Here is the code:
>>
>> import org.apache.commons.lang3.time.FastDateFormat;
>> import org.apache.flink.api.common.functions.FoldFunction;
>> import org.apache.flink.api.common.functions.MapFunction;
>> import org.apache.flink.api.java.functions.KeySelector;
>> import org.apache.flink.streaming.api.datastream.DataStream;
>> import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
>> import
>> org.apache.flink.streaming.api.functions.AssignerWithPeriodicWatermarks;
>> import
>> org.apache.flink.streaming.api.functions.source.RichParallelSourceFunction;
>> import org.apache.flink.streaming.api.watermark.Watermark;
>> import org.apache.flink.streaming.api.windowing.time.Time;
>>
>> public class TimeWindow {
>>
>> private static class TimestampAssigner implements
>> AssignerWithPeriodicWatermarks<Long> {
>> private final long DELAY = 500;
>> private long currentWatermark;
>>
>> @Override
>> public Watermark getCurrentWatermark() {
>> return new Watermark(currentWatermark);
>> }
>>
>> @Override
>> public long extractTimestamp(Long event, long l) {
>> currentWatermark = Math.max(currentWatermark, event - DELAY);
>> return event;
>> }
>> }
>>
>> public static void main(String[] args) throws Exception {
>> final FastDateFormat formatter = FastDateFormat.getInstance("EEE, dd
>> MMM yyyy HH:mm:ss z");
>> StreamExecutionEnvironment env =
>> StreamExecutionEnvironment.createLocalEnvironment();
>>
>> DataStream<Long> stream = env.addSource(new
>> RichParallelSourceFunction<Long>() {
>> private volatile boolean isRunning = true;
>>
>> @Override
>> public void run(SourceContext<Long> sourceContext) throws
>> Exception {
>> while (isRunning) {
>> sourceContext.collect(System.currentTimeMillis());
>> Thread.sleep(200);
>> }
>>
>> sourceContext.close();
>> }
>>
>> @Override
>> public void cancel() {
>> isRunning = false;
>> }
>> });
>>
>> stream
>> .assignTimestampsAndWatermarks(new TimestampAssigner())
>> .keyBy(new KeySelector<Long, Integer>() {
>> @Override
>> public Integer getKey(Long x) throws Exception {
>> return 0;
>> }
>> })
>> .timeWindow(Time.seconds(10))
>> .fold(0, new FoldFunction<Long, Integer>() {
>> @Override
>> public Integer fold(Integer count, Long x) throws
>> Exception {
>> System.out.println(formatter.format(x));
>> return count + 1;
>> }
>> })
>> .map(new MapFunction<Integer, Void>() {
>> @Override
>> public Void map(Integer count) throws Exception {
>> System.out.println(count + " events in this window");
>> return null;
>> }
>> });
>>
>> env.execute();
>> }
>> }
>>
>>
>> It doesn't always happen, but if you run the program long enough it can
>> be observed for sure.
>> Adjusting the DELAY value of watermark generation does not change the
>> behavior.
>>
>
