Sorry I didn't make it clear in my response but market data messages are 
typically very small, received super-fast and (in my situation) coming from a 
number of sources that trigger other processes in addition to being aggregated 
up for large-set, real-time analysis the results of which might be run through 
a separate Storm Topology. 

Craig Charleton
[email protected]

> On Nov 18, 2015, at 8:24 AM, <[email protected]> 
> <[email protected]> wrote:
> 
> Hi,
>  
> There was a point in the question that, I think, translates to : Will Storm 
> be useful if my data packets are small(“Messages are typically short ones”), 
> but they add up to the size of Big Data ?
>  
> The answer is Yes.
>  
> The other parts of the questions have been answered by others, I hope.
>  
> Regards,
> Prajod
>  
> From: Craig Charleton [mailto:[email protected]] 
> Sent: 18 November 2015 18:39
> To: [email protected]
> Cc: John Fang <[email protected]>
> Subject: Re: Storm typical application
>  
> Aliza,
>  
> If I may, I would like to share A few random thoughts about your question. 
>  
> I worked for a large enterprise software company and our customers were 
> always struggling with how to use the massive amounts of data that were being 
> input/created by their systems to understand their business and make 
> decisions. Traditionally the data had to come to its final resting place 
> before it could be analyzed for decision support.  There was no way to 
> reformat, clean, analyze, aggregate the data as it was flowing through the 
> systems, let alone for different user populations to apply their own 
> perspective to the "streams" without affecting the operations of others. 
>  
> That is where I see the value to large organizations.  In fact, it was the 
> limitations of traditional enterprise systems that became obvious once 
> companies like Twitter, Linked-In, Google, Yahoo, Facebook needed to do 
> things to large volumes of data in real time.  They not only needed to 
> perform these operations quickly, the load was continually growing, so 
> solutions needed to be able to scale beyond one server on an ongoing basis.
>  
> This is what Storm is for in my opinion. I am currently implementing it to 
> perform a lot of operations on stock trade and quote information as it is 
> received from the markets. The number of stocks that need to be handled by 
> the system is unknown. Therefore I am able to use Storm to write the 
> operations once and then scale the load across an unlimited number of servers.
>  
> Hope this wasn't too boring. 
> 
> 
> Craig Charleton
> [email protected]
> 
> On Nov 18, 2015, at 3:25 AM, Aliza Nagauker <[email protected]> 
> wrote:
> 
> Hi,
>  
> Thanks for your response. I will try the examples.
>  
> I understand that Storm can do the functionality required in my application, 
> yet my question is whether it is the right platform.
> So far we worked with Karaf-framework for our applications, and I am trying 
> to understand what should be the motivations to move to Storm framework?
> Is it for cases of:
> ·        large amount of real time data processing (Big Data: files, DB, WEB 
> pages) over distributed machines?
> ·        Large amount of real time events processing – usually control 
> protocols (network protocols – like routing protocol, VOIP protocols, SNMP, 
> REST) over distributed machines?
>  
> Thanks, Aliza
>  
> From: John Fang [mailto:[email protected]] 
> Sent: Wednesday, November 18, 2015 2:21 AM
> To: [email protected]
> Subject: 答复: Storm typical application
>  
> Yes,storm can do it. I suggest you read some storm’ example.: 
> https://github.com/apache/storm/tree/master/examples/storm-starter
>  
>  
> 发件人: Aliza Nagauker [mailto:[email protected]] 
> 发送时间: 2015年11月17日 23:23
> 收件人: [email protected]
> 主题: Storm typical application
>  
> Hello all,
>  
> I am new at Storm. I read Storm Doc and tutorial as published in storm site 
> and have few basic questions.
> I am trying to learn and understand whether Storm is suitable for my 
> application.
>  
> Is Storm mainly intended for distributed real time applications that has to 
> handle "massive input data" and apply "data analytics over this data"?
> Is it indented to application where the data-size is large and need analytic 
> over the data itself (word count, search words, convert formats, write it to 
> DB etc.)?
>  
> Assuming my application is a kind of a Controller that:
> &#0;.     receive messages from multiple sources: Management Systems, Network 
> Elements, Internal timers, Internal modules
> &#0;.     Act upon these messages: update protocol –state-machines, it may 
> send messages to other servers/applications.
> &#0;.     Messages are typically short ones – control protocols messages (Not 
> HTTP pages, Not Documents, Not Database info).
> &#0;.     We may need to run this application in multiple machines.
>  
> In this case, is Storm is the right choice for this application?
> I understand that Storm is indeed very recommended for Distributed Real Time 
> application, yet, I am not sure it is intended for network applications that 
> are mainly control application and not Data Processing Applications (Not Big 
> Data applications)
>  
> I'll appreciate your consult on this.
>  
> Thanks, Aliza
>  
>  
>  
>  
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