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From Mike Keane <mke...@conversantmedia.com>
Subject RE: Deal with duplicates in Flume with a crash.
Date Thu, 04 Dec 2014 21:09:35 GMT
UUID is on the FlumeEvent header. 10,000 FlumeEvents per second = 10,000 check & puts to
HBase.

Each FlumeEvent has 200 log lines in it. If I was NOT doing a check & put to HBase for
each FlumeEvent, each duplicated FlumeEvent results in all 200 log lines being duplicated.

We evolved away from the UUID interceptor when we refactored our servers to use the EmbeddedAgent
in our server stack as the starting point for all of our flume flows.

At the highest level here is what we do:

1. Servers generating log data add to a LinkedBlockingQueue.
2. LinkedBlockingQueue appends logLines to StringBuffer until 200 lines added or 1 second
is reached
3. Create a FlumeEvent with a UUID header
Map<String, String> hdrs = new HashMap<String, String>();
hdrs.put(EVENT_UNIQUE_ID, eventUniqueId);
embeddedAgent.put(EventBuilder.withBody(<StringBuffer from LinkedBlockingQueue>, hdrs));
4. Add FlumeEvent to EmbeddedAgent object in server.
5.  Embedded agent sinks to collector tier
6.  Collector Tier Sinks to Storage Tier with custom sink that does the check and put.

Prior to the EmbeddedAgent refactor our servers would create a FlumeEvent and use an RpcClient
to send the event to a Application Tier agent which would use the UUID interceptor to add
the UUID.   Our server refactory replaced the ApplicationTier agent with the EmbeddedAgent
in our servers.  For a diagram of the Tiers check out the Apache flume blog: https://blogs.apache.org/flume/entry/flume_performance_tuning_part_1


-Mike




________________________________________
From: Guillermo Ortiz [konstt2000@gmail.com]
Sent: Thursday, December 04, 2014 2:14 AM
To: user@flume.apache.org
Subject: Re: Deal with duplicates in Flume with a crash.

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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>




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