Aljoscha (in CC), do you have an idea about this issue? Thanks, Fabian
2018-01-24 7:06 GMT+01:00 Navneeth Krishnan <reachnavnee...@gmail.com>: > Thanks Fabian but for 1.5k messages per second per TM there are several > million Internal & TimerWindow objects created within a period of 5 > seconds. Is there a way to get debug this issue? > > Regards, > Navneeth > > On Tue, Jan 23, 2018 at 2:09 AM, Fabian Hueske <fhue...@gmail.com> wrote: > >> Hi, >> >> TimeWindows and Timers are created for each window, i.e., every 5 seconds >> for every distinct key that a task is processing. >> Event-time windows are completed and cleaned up when a watermark is >> received that passes the window end timestamp. >> Therefore, there might be more than one window per key depending on the >> watermarks. >> >> Hope this helps, >> Fabian >> >> 2018-01-21 6:48 GMT+01:00 Navneeth Krishnan <reachnavnee...@gmail.com>: >> >>> Hi, >>> >>> I'm facing issues with frequent young generation garbage collections in >>> my task manager which happens approximately every few seconds. I have 3 >>> task managers with 12GB heap allocated on each and I have set the config to >>> use G1GC. My program ingests binary data from kafka source and the message >>> rate is around 4.5k msgs/sec with around 400 bytes per msg. Below are the >>> operators used in the program. >>> >>> kafka src -> keyby -> CoProcess -> keyby -> Tumbling Window (5secs) -> >>> FlatMap -> Sink >>> >>> I captured the below histograms at 5 second intervals and analyzed the >>> heap as well. It looks like a lot InternalTimer and TimeWindow objects are >>> created. >>> >>> Also, I see a high usage in org.apache.flink.streaming. >>> api.operators.HeapInternalTimerService. >>> >>> *Window code:* >>> dataStream.keyBy(new MessageKeySelector()) >>> .window(TumblingEventTimeWindo >>> ws.of(Time.seconds(5))) >>> .apply(new Aggregate()); >>> >>> *Captured at time T:* >>> >>> num #instances #bytes class name >>> ---------------------------------------------- >>> 1: 2074427 481933816 [B >>> 2: 357192 339368592 [D >>> 3: 12759222 204147552 java.lang.Integer >>> 4: 31416 85151832 [I >>> 5: 900982 83872240 [C >>> 6: 631888 20220416 java.util.HashMap$Node >>> 7: 804203 19300872 java.lang.String >>> 8: 541651 17332832 org.apache.flink.streaming.api >>> .operators.InternalTimer >>> 9: 540252 17288064 org.apache.flink.streaming.api >>> .windowing.windows.TimeWindow >>> >>> >>> *Captured at T1 (T + 5 seconds):* >>> >>> num #instances #bytes class name >>> ---------------------------------------------- >>> 1: 12084258 2282849264 <(228)%20284-9264> [B >>> 2: 1922018 1828760896 [D >>> 3: 68261427 1092182832 java.lang.Integer >>> 4: 2712099 291488736 [C >>> 5: 54201 98798976 [I >>> 6: 2028250 48678000 java.lang.String >>> 7: 66080 43528136 [[B >>> 8: 1401915 35580168 [Ljava.lang.Object; >>> 9: 949062 30369984 java.util.HashMap$Node >>> 10: 570832 18266624 org.apache.flink.streaming.api >>> .operators.InternalTimer >>> 11: 549979 17599328 org.apache.flink.streaming.api >>> .windowing.windows.TimeWindow >>> >>> >>> *Captured at T2 (T1+ 5 seconds):* >>> >>> num #instances #bytes class name >>> ---------------------------------------------- >>> 1: 9911982 2920384472 [B >>> 2: 1584406 1510958520 [D >>> 3: 56087337 897397392 java.lang.Integer >>> 4: 26080337 834570784 java.util.HashMap$Node >>> 5: 25756748 824215936 org.apache.flink.streaming.api >>> .operators.InternalTimer >>> 6: 25740086 823682752 org.apache.flink.streaming.api >>> .windowing.windows.TimeWindow >>> >>> Thanks. >>> >>> >> >
