Saturday 18th August, 2012
6:15pm to 6:45pm
One of the biggest challenges when handling big data is making sure your
system is coherent after an unexpected crash or machine failure. Designing
your system for idempotency will make sure you can reprocess parts of your
data to fill in the gaps without accidentally affecting the good data.
Once you've got the idempotency down, you are free to venture boldly into
a veritable Narnia* of scaling solutions.
This talk will describe the problem and offer a couple of solutions by
looking at some real-life implementations.
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