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 >>>>>>> >>>>>> >>>>> >>> >
