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From Peyman Mohajerian <mohaj...@gmail.com>
Subject Re: Realtime sensor's tcpip data to hadoop
Date Thu, 15 May 2014 13:50:23 GMT
Whether you use Storm/kafka or any other realtime processing or not, you
may still need to persist the data which can be done directly to hbase from
any of these realtime system or from the source.


On Thu, May 8, 2014 at 9:25 PM, Hardik Pandya <smarty.juice@gmail.com>wrote:

> If I were you I would ask following questions to get the answer
>
> > forget about for a minute and ask yourself how tcpip data are currently
> being stored - in fs/rdbmbs?
> > hadoop is for offiline batch processing - if you are looking for real
> time streaming solution - there is a storm (from linkedin) that can go well
> with kafka (messaging queue) or spark streaming (which is in memory
> map-reduce) and takes real time streams - has in built twitter api but you
> need to write your own service to poll data every few seconds and send it
> in RDD format
> > storm is complementary to hadoop - spark in conjuction with hadoop will
> allow you to do both offline and real time data analytics
>
>
>
>
> On Tue, May 6, 2014 at 10:48 PM, Alex Lee <eliyart@hotmail.com> wrote:
>
>> Sensors' may send tcpip data to server. Each sensor may send tcpip data
>> like a stream to the server, the quatity of the sensors and the data rate
>> of the data is high.
>>
>> Firstly, how the data from tcpip can be put into hadoop. It need to do
>> some process and store in hbase. Does it need through save to data files
>> and put into hadoop or can be done in some direct ways from tcpip. Is there
>> any software module can take care of this. Searched that Ganglia Nagios and
>> Flume may do it. But when looking into details, ganglia and nagios are
>> more for monitoring hadoop cluster itself. Flume is for log files.
>>
>> Secondly, if the total network traffic from sensors are over the limit of
>> one lan port, how to share the loads, is there any component in hadoop to
>> make this done automatically.
>>
>> Any suggestions, thanks.
>>
>
>

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