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From Chen Wang <chen.apache.s...@gmail.com>
Subject Re: seeking help on flume cluster deployment
Date Fri, 10 Jan 2014 04:43:41 GMT
Jeff,
I have read this ppt at the beginning, but didn't find solution to my user
case. To simplify my case, I only have 1 data source(composed of 5 socket
server)  and i am looking for a fault tolerant deployment of flume, that
can read from this single data source and sink to hdfs in fault tolerant
mode: when one node dies, another flume node can pick up and continue;
Thanks,
Chen


On Thu, Jan 9, 2014 at 7:49 PM, Jeff Lord <jlord@cloudera.com> wrote:

> Chen,
>
> Have you taken a look at this presentation on Planning and Deploying Flume
> from ApacheCon?
>
>
> http://archive.apachecon.com/na2013/presentations/27-Wednesday/Big_Data/11:45-Mastering_Sqoop_for_Data_Transfer_for_Big_Data-Arvind_Prabhakar/Arvind%20Prabhakar%20-%20Planning%20and%20Deploying%20Apache%20Flume.pdf
>
> It may have the answers you need.
>
> Best,
>
> Jeff
>
>
> On Thu, Jan 9, 2014 at 7:24 PM, Chen Wang <chen.apache.solr@gmail.com>wrote:
>
>> Thanks Saurabh.
>> If that is the case, I am actually thinking about using storm spout to
>> talk to our socket server so that the storm cluster can take care of the
>> reading socket server part. Then in each storm node, start a flume agent,
>> listening on a RPC port and write to HDFS(with fail over) .Then in the
>> storm bolt, simply send the data to RPC so that flume can get it.
>> How do you think of this setup? It takes care of both failover on the
>> source(by storm) and on the sink(by flume) But It looks a little
>> complicated for me.
>> Chen
>>
>>
>> On Thu, Jan 9, 2014 at 7:18 PM, Saurabh B <qna.list.141211@gmail.com>wrote:
>>
>>> Hi Chen,
>>>
>>> I think Flume doesn't have a way to configure multiple sources pointing
>>> to same data source. Of course you can do that, but you will end up with
>>> duplicate data. Flume offers fail over at the sink level.
>>>
>>> On Thu, Jan 9, 2014 at 6:56 PM, Chen Wang <chen.apache.solr@gmail.com>wrote:
>>>
>>>> Ok. so after more researching:) It seems that what i need is the
>>>> failover for agent source, (not fail over for sink):
>>>> If one agent dies, another same kind of agent will start running.
>>>> Does flume support this scenario?
>>>> Thanks,
>>>> Chen
>>>>
>>>>
>>>> On Thu, Jan 9, 2014 at 3:12 PM, Chen Wang <chen.apache.solr@gmail.com>wrote:
>>>>
>>>>> After reading more docs, it seems that if I want to achieve my goal,
i
>>>>> have to do the following:
>>>>> 1. Having one agent with the custom source running on one node. This
>>>>> agent reads from those 5 socket server, and sink to some kind of sink(maybe
>>>>> another socket?)
>>>>> 2. On another(or more) machines, setting up collectors that read from
>>>>> the agent sink in 1, and sink to hdfs.
>>>>> 3. Having a master node managing nodes in 1,2.
>>>>>
>>>>> But it seems to be overskilled in my case: in 1, i can already sink to
>>>>> hdfs. Since the data available at socket server are much faster than
the
>>>>> data translation part.  I want to be able to later add more nodes to
do the
>>>>> translation job. so what is the correct setup?
>>>>> Thanks,
>>>>> Chen
>>>>>
>>>>>
>>>>>
>>>>> On Thu, Jan 9, 2014 at 2:38 PM, Chen Wang <chen.apache.solr@gmail.com>wrote:
>>>>>
>>>>>> Guys,
>>>>>> In my environment, the client is 5 socket servers. Thus i wrote a
>>>>>> custom source spawning 5 threads reading from each of them infinitely,and
>>>>>> the sink is hdfs(hive table). The work fine by running flume-ng
>>>>>> agent.
>>>>>>
>>>>>> But how can i deploy this in distributed mode(cluster)? I am confused
>>>>>> about the 3 ties(agent,collector,storage) mentioned in the doc. Does
it
>>>>>> apply to my case? How can I separate my agent/collect/storage? Apparently
i
>>>>>> can only have one agent running: multiple agent will result in getting
>>>>>> duplicates from the socket server. But I want that if one agent dies,
other
>>>>>> agent can take it up. I would also like to be able to add horizontal
>>>>>> scalability for writing to hdfs. How can I achieve all this?
>>>>>>
>>>>>> thank you very much for your advice.
>>>>>> Chen
>>>>>>
>>>>>
>>>>>
>>>>
>>>
>>>
>>> --
>>> Mailing List Archives,
>>> QnaList.com
>>>
>>
>>
>

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