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From Guillermo Ortiz <konstt2...@gmail.com>
Subject Re: Deal with duplicates in Flume with a crash.
Date Thu, 04 Dec 2014 08:14:11 GMT
What I don't understand it's that you are getting an UUID for sets of
1000 lines, am I right? how could you know if there're duplicates if
you are evaluating set of lines and not line per line with UUID?

I thought that what you were doing:
1.Get a line from the Source X.
2.Calculate an UUID for a single line with an interceptor
3.Another interceptor checks this UUID in HBase. If it doesn't exist,
you send to the channel and put the UUID in Hbase,

If you are grouping the lines.. aren't you checking duplicates to set level??

Maybe you're checking the UUID in the Sink, although I see the same
problem. Where am I wrong??

2014-12-04 0:50 GMT+01:00 Mike Keane <mkeane@conversantmedia.com>:
> I'm not sure I understand your question but I'll be the first to admit this is not fool
proof.
>
> That said here are a couple inherent risks I am taking.  Assume FlumeEventA is one of
1000 events in a batch.  If FlumeEventA makes it to FlumeAgent1 but the batch fails it is
entirely possible when the batch is resent it goes to FlumeAgent2.  Now this event is on 2
separate file channels, separate jvms and separate servers.  It is possible but extremely
unlikely that FlumeEventA is processed at the exact same time in FlumeAgent1 and FlumeAgent2.
 Both agents pop the event off the channel, pull the UUID off the header and check if it is
in HBase.  Both do not find it so both write to HDFS and we have a duplicate.  Considering
the archetecture we believe the odds of this are incredibly small and we are OK with the risk.
>
> Since the write to HDFS is in a transaction if it fails I don't do a HBase put of the
UUID, the transaction rolls back and we try again.  I did a fair amount studying the sink
and bucketwriter code at the time to understand what the fail conditions are when writing
to HDFS.  If I remember right it could fail creating the file, writing to the file, closing
the file and renaming the file.  We all have or own SLAs to meet.  After a pretty thorough
review and amount of testing we were comfortable this met our SLA better than a mapreduce
job to dedupe 90 billion log lines per day.
>
> Joey Echeverria <joey@cloudera.com> wrote:
>
>
> What happens if the write to HDFS succeeds before the HBase put?
>
> -Joey
>
> On Wed, Dec 3, 2014 at 2:35 PM, Mike Keane <mkeane@conversantmedia.com> wrote:
>> We effectively mitigated this problem by using the UUID interceptor and customizing
the HDFS Sink to do a check and put of the UUID to HBase.  In the customized sink we check
HBase to see if we have seen the UUID before, if we have it is a duplicate and we log a new
duplicate metric with the existing sink metrics and throw the event away.  If we have not
seen the UUID before we write the Event to HDFS and do a put of the UUID to hbase.
>>
>> Because of our volume to minimize the number of check/puts to HBase we put multiple
logs in a single FlumeEvent.
>>
>>
>> -Mike
>>
>> ________________________________________
>> From: Guillermo Ortiz [konstt2000@gmail.com]
>> Sent: Wednesday, December 03, 2014 4:15 PM
>> To: user@flume.apache.org
>> Subject: Re: Deal with duplicates in Flume with a crash.
>>
>> I didn't know anything about a Hive Sink, I'll check the JIRA about it, thanks.
>> The pipeline is Flume-Kafka-SparkStreaming-XXX
>>
>> So I guess I should deal in SparkStreaming with it, right? I guess
>> that it would be easy to do it with an UUID interceptor or is there
>> another way easier?
>>
>> 2014-12-03 22:56 GMT+01:00 Roshan Naik <roshan@hortonworks.com>:
>>> Using the UUID interceptor at the source closest to data origination.. it
>>> will help identify duplicate events after they are delivered.
>>>
>>> If it satisfies your use case, the upcoming Hive Sink will mitigate the
>>> problem a little bit (since it uses transactions to write to destination).
>>>
>>> -roshan
>>>
>>>
>>> On Wed, Dec 3, 2014 at 8:44 AM, Joey Echeverria <joey@cloudera.com> wrote:
>>>>
>>>> There's nothing built into Flume to deal with duplicates, it only
>>>> provides at-least-once delivery semantics.
>>>>
>>>> You'll have to handle it in your data processing applications or add
>>>> an ETL step to deal with duplicates before making data available for
>>>> other queries.
>>>>
>>>> -Joey
>>>>
>>>> On Wed, Dec 3, 2014 at 5:46 AM, Guillermo Ortiz <konstt2000@gmail.com>
>>>> wrote:
>>>> > Hi,
>>>> >
>>>> > I would like to know if there's a easy way to deal with data
>>>> > duplication when an agent crashs and it resends same data again.
>>>> >
>>>> > Is there any mechanism to deal with it in Flume,
>>>>
>>>>
>>>>
>>>> --
>>>> Joey Echeverria
>>>
>>>
>>>
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>>
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>
>
>
> --
> Joey Echeverria
>
>
>
>
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