December 2013
Intermediate to advanced
564 pages
19h 54m
English
Content preview from Big Data Computing
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310 Big Data Computing
MapReduce is able to start running jobs as soon as the required data are
available in the le system. First of all, jobs are initialized by creating a series
of map and reduce tasks. The number of map tasks is usually determined
by the number of splits into which the input data are divided. Splitting the
input is what makes it possible to parallelize the map phase and can have a
great impact on the performance, so splits can also be thought of as the rst
level of granularity of the system, and it also shows how the le system and
MapReduce are integrated. For instance, if the input consists of a single 6.25
GB le ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.