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From Pawel Szczur <pawelszc...@gmail.com>
Subject Re: Items not groupped correctly - CoGroupByKey - FlinkPipelienRunner
Date Tue, 31 May 2016 12:51:27 GMT
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 <pawelszczur@gmail.com>:

> 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 <aljoscha@apache.org>:
>
>> 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 <pawelszczur@gmail.com> 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 <aljoscha@apache.org>:
>>>
>>>> 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 <pawelszczur@gmail.com>
>>>> 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 <aljoscha@apache.org>:
>>>>>
>>>>>> 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 <pawelszczur@gmail.com>
>>>>>> 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 <aljoscha@apache.org>:
>>>>>>>
>>>>>>>> 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 <pawelszczur@gmail.com>
>>>>>>>> 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
>>>>>>>>>
>>>>>>>>
>>>>>>>
>>>>>
>>>
>

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