Timeline for Why Big Data Needs To Be Functional?
Current License: CC BY-SA 3.0
8 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Dec 7, 2013 at 19:43 | comment | added | Shivan Dragon | @SK-logic thanks, that's an excellent example you give! | |
| Dec 7, 2013 at 16:21 | comment | added | SK-logic | @ShivanDragon, for example, LHC is producing several gigabytes of data per second. Not sure a single machine can even handle such a throughput. | |
| Dec 7, 2013 at 15:54 | comment | added | user3047512 | Thank you for your input, I agree. Maybe I couldn't find a good simple example to demonstrate my point of view. "Big Data" still a way that developers use data to solve our daily problems taking in consideration the 3Vs definition. I will forget the 3V for a while and talk about the very simple aspect, dealing with Data. If we see that analyzing data in a functional way is expensive, why do we say that "Big Data" needs to be functional ? This is my point . | |
| Dec 7, 2013 at 15:12 | comment | added | Shivan Dragon | I'm sorry, I see your point now. Is it correct to say that what you're referring to is, more specifically, MapReduce which lives under the umbrella of BigData ? | |
| Dec 7, 2013 at 14:42 | comment | added | Michael Borgwardt | @ShivanDragon: The kind of problem that includes performance requirements that are utterly impossible to satisfy on a single system. Or where the data size is so big that no single system can even store it all. | |
| Dec 7, 2013 at 14:31 | comment | added | Shivan Dragon | "Big Data means that the problem sizes are so big that distributing the processing is not an optimization but a fundamental requirement." - I don't understand what kind of problem can't AT ALL be resolved using one machine, and requires at least N where N > 1... | |
| S Dec 7, 2013 at 13:53 | history | answered | Michael Borgwardt | CC BY-SA 3.0 | |
| S Dec 7, 2013 at 13:53 | history | made wiki | Post Made Community Wiki by Michael Borgwardt |