I've also added the test for GroupByKey. It fails. It kind of makes Flink broken at the moment, isn't it?
I'm wondering.. may it be related to some Windowing issue? 2016-05-31 14:40 GMT+02:00 Pawel Szczur <[email protected]>: > I've just tested it. It fails. > > Also added the test to the repo: > https://github.com/orian/cogroup-wrong-grouping > > I reason, this means that GroupByKey is flawed? If you open an official > issue, please add it to discussion. > > 2016-05-31 11:55 GMT+02:00 Aljoscha Krettek <[email protected]>: > >> Does 2. work for the cases where CoGroupByKey fails? Reason I'm asking is >> that CoGroupByKey is essentially implemented like that internally: create >> tagged union -> flatten -> GroupByKey. >> >> On Tue, 31 May 2016 at 01:16 Pawel Szczur <[email protected]> wrote: >> >>> I've naively tried few other key types, it seems to be unrelated to key >>> type. >>> >>> As for now I have two workarounds and ignorance: >>> 1. If there is one dominant dataset and other datasets are small (size >>> << GB) then I use SideInput. >>> 2. If I have multiple datasets of similar size I enclose it in a common >>> container, flatten it and GroupByKey. >>> 3. I measure occurrences and ignore the bug for now. >>> >>> Do you have an idea how a test for this may be constructed? It seems >>> handy, I think. >>> >>> I also found two things, maybe they help you: >>> 1. issue doesn't appear without parallelism >>> 2. issue doesn't appear with a tiny datasets >>> >>> 2016-05-30 17:13 GMT+02:00 Aljoscha Krettek <[email protected]>: >>> >>>> You're right. I'm still looking into this, unfortunately I haven't made >>>> progress so far. I'll keep you posted. >>>> >>>> On Sun, 29 May 2016 at 18:20 Pawel Szczur <[email protected]> >>>> wrote: >>>> >>>>> Hi, >>>>> >>>>> I used the config as in the repo. >>>>> Please grep the the log for "hereGoesLongStringID0,2", you will see >>>>> that this key is processed multiple times. >>>>> >>>>> This is how I understand CoGroupByKey: one has two (or more) >>>>> PCollection<KV<K,?>>. Both sets are grouped by key. For each unique key a >>>>> KV<K, CoGbkResult> is produced, a given CoGbkResult contains all values >>>>> from all input PCollections which have the given key. >>>>> >>>>> But from the log it seems that each key produced more than one >>>>> CoGbkResult. >>>>> >>>>> The final counters didn't catch the bug because in your case, the >>>>> value from dataset1 was replicated for each key. >>>>> >>>>> Cheers, Pawel >>>>> >>>>> 2016-05-29 15:59 GMT+02:00 Aljoscha Krettek <[email protected]>: >>>>> >>>>>> Hi, >>>>>> I ran your data generator with these configs: >>>>>> p.apply(Create.of(new Config(3, 5, 600_000, 1))) >>>>>> .apply(ParDo.of(new Generator())).apply( >>>>>> AvroIO.Write.to >>>>>> ("/tmp/dataset1").withSchema(DumbData.class).withNumShards(6)); >>>>>> >>>>>> p.apply(Create.of(new Config(3, 5, 600_000, 2))). >>>>>> apply(ParDo.of(new Generator())).apply( >>>>>> AvroIO.Write.to >>>>>> ("/tmp/dataset2").withSchema(DumbData.class).withNumShards(6)); >>>>>> >>>>>> Then I ran the job with parallelism=6. I couldn't reproduce the >>>>>> problem, this is the log file from one of several runs: >>>>>> https://gist.github.com/aljoscha/ef1d804f57671cd472c75b92b4aee51b >>>>>> >>>>>> Could you please send me the exact config that you used. Btw, I ran >>>>>> it inside an IDE, do the problems also occur in the IDE for you or only >>>>>> when you execute on a cluster? >>>>>> >>>>>> Cheers, >>>>>> Aljoscha >>>>>> >>>>>> On Sun, 29 May 2016 at 01:51 Pawel Szczur <[email protected]> >>>>>> wrote: >>>>>> >>>>>>> Hi Aljoscha. >>>>>>> >>>>>>> I've created a repo with fake dataset to allow easily reproduce the >>>>>>> problem: >>>>>>> https://github.com/orian/cogroup-wrong-grouping >>>>>>> >>>>>>> What I noticed: if the dataset is too small the bug doesn't appear. >>>>>>> >>>>>>> You can modify the size of dataset, but in ideal case it should be >>>>>>> few hundred thousands records per key (I guess it depends on the machine >>>>>>> you run it). >>>>>>> >>>>>>> Cheers, Pawel >>>>>>> >>>>>>> 2016-05-28 12:45 GMT+02:00 Aljoscha Krettek <[email protected]>: >>>>>>> >>>>>>>> Hi, >>>>>>>> which version of Beam/Flink are you using. >>>>>>>> >>>>>>>> Could you maybe also provide example data and code that showcases >>>>>>>> the problem? If you have concerns about sending it to a public list >>>>>>>> you can >>>>>>>> also send it to me directly. >>>>>>>> >>>>>>>> Cheers, >>>>>>>> Aljoscha >>>>>>>> >>>>>>>> On Fri, 27 May 2016 at 20:53 Pawel Szczur <[email protected]> >>>>>>>> wrote: >>>>>>>> >>>>>>>>> *Data description.* >>>>>>>>> >>>>>>>>> I have two datasets. >>>>>>>>> >>>>>>>>> Records - the first, containes around 0.5-1M of records per >>>>>>>>> (key,day). For testing I use 2-3 keys and 5-10 days of data. What I >>>>>>>>> shoot >>>>>>>>> for is 1000+ keys. Each record contains key, timestamp in μ-seconds >>>>>>>>> and >>>>>>>>> some other data. >>>>>>>>> Configs - the second, is rather small. It describes the key in >>>>>>>>> time, e.g. you can think about it as a list of tuples: (key, start >>>>>>>>> date, >>>>>>>>> end date, description). >>>>>>>>> >>>>>>>>> For the exploration I've encoded the data as files of >>>>>>>>> length-prefixed Protocol Buffer binary encoded messages. Additionally >>>>>>>>> the >>>>>>>>> files are packed with gzip. Data is sharded by date. Each file is >>>>>>>>> around >>>>>>>>> 10MB. >>>>>>>>> >>>>>>>>> *Pipeline* >>>>>>>>> >>>>>>>>> First I add keys to both datasets. For Records dataset it's (key, >>>>>>>>> day rounded timestamp). For Configs a key is (key, day), where day is >>>>>>>>> each >>>>>>>>> timestamp value between start date and end date (pointing midnight). >>>>>>>>> The datasets are merged using CoGroupByKey. >>>>>>>>> >>>>>>>>> As a key type I use import org.apache.flink.api.java.tuple.Tuple2 >>>>>>>>> with a Tuple2Coder from this repo. >>>>>>>>> >>>>>>>>> *The problem* >>>>>>>>> >>>>>>>>> If the Records dataset is tiny like 5 days, everything seems fine >>>>>>>>> (check normal_run.log). >>>>>>>>> >>>>>>>>> INFO [main] (FlinkPipelineRunner.java:124) - Final aggregator >>>>>>>>> values: >>>>>>>>> INFO [main] (FlinkPipelineRunner.java:127) - item count : 4322332 >>>>>>>>> INFO [main] (FlinkPipelineRunner.java:127) - missing val1 : 0 >>>>>>>>> INFO [main] (FlinkPipelineRunner.java:127) - multiple val1 : 0 >>>>>>>>> >>>>>>>>> When I run the pipeline against 10+ days I encounter an error >>>>>>>>> pointing that for some Records there's no Config (wrong_run.log). >>>>>>>>> >>>>>>>>> INFO [main] (FlinkPipelineRunner.java:124) - Final aggregator >>>>>>>>> values: >>>>>>>>> INFO [main] (FlinkPipelineRunner.java:127) - item count : 8577197 >>>>>>>>> INFO [main] (FlinkPipelineRunner.java:127) - missing val1 : 6 >>>>>>>>> INFO [main] (FlinkPipelineRunner.java:127) - multiple val1 : 0 >>>>>>>>> >>>>>>>>> Then I've added some extra logging messages: >>>>>>>>> >>>>>>>>> (ConvertToItem.java:144) - 68643 items for KeyValue3 on: >>>>>>>>> 1462665600000000 >>>>>>>>> (ConvertToItem.java:140) - no items for KeyValue3 on: >>>>>>>>> 1463184000000000 >>>>>>>>> (ConvertToItem.java:123) - missing for KeyValue3 on: >>>>>>>>> 1462924800000000 >>>>>>>>> (ConvertToItem.java:142) - 753707 items for KeyValue3 on: >>>>>>>>> 1462924800000000 marked as no-loc >>>>>>>>> (ConvertToItem.java:123) - missing for KeyValue3 on: >>>>>>>>> 1462752000000000 >>>>>>>>> (ConvertToItem.java:142) - 749901 items for KeyValue3 on: >>>>>>>>> 1462752000000000 marked as no-loc >>>>>>>>> (ConvertToItem.java:144) - 754578 items for KeyValue3 on: >>>>>>>>> 1462406400000000 >>>>>>>>> (ConvertToItem.java:144) - 751574 items for KeyValue3 on: >>>>>>>>> 1463011200000000 >>>>>>>>> (ConvertToItem.java:123) - missing for KeyValue3 on: >>>>>>>>> 1462665600000000 >>>>>>>>> (ConvertToItem.java:142) - 754758 items for KeyValue3 on: >>>>>>>>> 1462665600000000 marked as no-loc >>>>>>>>> (ConvertToItem.java:123) - missing for KeyValue3 on: >>>>>>>>> 1463184000000000 >>>>>>>>> (ConvertToItem.java:142) - 694372 items for KeyValue3 on: >>>>>>>>> 1463184000000000 marked as no-loc >>>>>>>>> >>>>>>>>> You can spot that in first line 68643 items were processed for >>>>>>>>> KeyValue3 and time 1462665600000000. >>>>>>>>> Later on in line 9 it seems the operation processes the same key >>>>>>>>> again, but it reports that no Config was available for these Records. >>>>>>>>> The line 10 informs they've been marked as no-loc. >>>>>>>>> >>>>>>>>> The line 2 is saying that there were no items for KeyValue3 and >>>>>>>>> time 1463184000000000, but in line 11 you can read that the items for >>>>>>>>> this >>>>>>>>> (key,day) pair were processed later and they've lacked a Config. >>>>>>>>> >>>>>>>>> *Work-around (after more testing, doesn't work, staying with >>>>>>>>> Tuple2)* >>>>>>>>> >>>>>>>>> I've switched from using Tuple2 to a Protocol Buffer message: >>>>>>>>> >>>>>>>>> message KeyDay { >>>>>>>>> optional ByteString key = 1; >>>>>>>>> optional int64 timestamp_usec = 2; >>>>>>>>> } >>>>>>>>> >>>>>>>>> But using Tuple2.of() was just easier than: >>>>>>>>> KeyDay.newBuilder().setKey(...).setTimestampUsec(...).build(). >>>>>>>>> >>>>>>>>> // The original description comes from: >>>>>>>>> http://stackoverflow.com/questions/37473682/items-not-groupped-correctly-cogroupbykey >>>>>>>>> >>>>>>>> >>>>>>> >>>>> >>> >
