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“So there’s an exponential explosion in terms of the number of events you have to look at. “Now when we give them this kind of infrastructure, it really allows us to open up and look at what other attributes we want to put in there,” Hoang tells Datanami.
![persecond minecraft clock persecond minecraft clock](https://i.imgur.com/bowiXN1.png)
With DataTorrent, companies can perform the same type of processing, but do so in real time, and potentially go much deeper into the data. There can be more than two dozen attributes available, but there’s rarely the time to go that deep. Companies crunch the various attributes of clickstream data, including which publisher, which advertisers, the ad size, the format, and location, to come up with an optimal blend. In the online advertising scenario, batch-oriented MapReduce applications running on Hadoop enabled advertisers to optimize the delivery of ads to people based on a number of factors. In other words, what kind of processing do they want to do when they bring the event in?” It’s what they’re thinking about or struggling with. “When you talk to some of these customers, it’s not about the incoming rate of streaming throughput. Hoang sees a bright future for DataTorrent processing data coming off the Internet of Things (IoT), as well as “classic” big data use cases, such as online advertising analysis. How much further do we need to go? How much data do we really need to process? “These things are coming faster than we think.” “I believe we can go further,” DataTorrent co-founder and CEO Phu Hoang says regarding the throughput figure. (Those numbers come from DataTorrent itself.) If the future of Hadoop is real-time data processing, then the folks at DataTorrent have to feel pretty good about where they are.
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RTS runs 1,000 times faster than Apache Storm, and about 100x faster than Spark Streaming. “None of the prospects we work with have gotten anywhere near the headroom we provide with 1.5 billion events per second.” “We feel we’re at a point with 1.5 billion events per second where we have plenty of head room,” says John Fanelli, vice president of marketing at DataTorrent. Not that anybody is asking for that much event-processing capacity at the moment. To put that into perspective, DataTorrent says that processing 1 billion data events per second is the equivalent of processing 46 cumulative hours of streaming Twitter data in one second. When all the levels of operators and events are added up, RTS handled a total of 1.5 billion events per second. Each node is able to process tens of thousands of incoming events (call data records, machine data, and clickstream data are common targets) per second, and in turn generates hundreds of thousands of secondary events that are then processed again using one of the 400 operators that DataTorrent makes available as part of its in-memory, big-data kit. That 1.5-billion-events-per-second figure was recorded on DataTorrent’s internal Hadoop cluster, which sports 34 nodes. Now that RTS is generally available–DataTorrent announced its general availability today at Hadoop Summit in San Jose–we may soon find out. The 5600g is slightly slower than the 5600x but if you're never going to get a graphics card, or maybe one months/years later, the 5600g will prove its value.What would you do with a system that could process 1.5 billion events per second? That’s the mind-boggling rate at which DataTorrent’s Real-Time Streaming (RTS) offering for Hadoop was recently benchmarked. If you don't have a graphics card or won't get one, the 5600g is a good choice. As said by others, if you already have a dedicated graphics card, the 5600x is the clear choice.
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