On Wed, Nov 5, 2014 at 9:56 AM, Ori Livneh <o...@wikimedia.org> wrote:
> Facebook just published this summary of a summit for database researchers
> held at Menlo Park last September. I recommend it. It contains a clear and
> concise description of Facebook's data infrastructure, and a description of
> the open problems they are thinking about, which is even more interesting.
>
> https://research.facebook.com/blog/1522692927972019/facebook-s-top-open-data-problems/
>
> To whet your appetite, here are the problems (the summaries mostly my own
> paraphrase):
>
> * Mobile: How should the shift toward mobile devices affect Facebook’s data
> infrastructure?
>
> * Reducing replication: How can we reduce the number of round trips between
> the application and data layers?
>
> * Impact of Caching on Availability (aka "oh no, we just restarted
> memcached"): How do we harness the efficiency gains provided by caching
> without being brought to our knees by a sudden drop in cache hit rate?
>
> * Sampling at logging time in a distributed environment: How should we
> sample log streams if we want to maintain accuracy and flexibility to answer
> post-hoc queries?
>
> * Trading storage space and CPU: TL;DR: gzip --best or gzip --fast?
>
> * Reliability of pipelines: Pipelines are less reliable than the sum of
> their parts. A pipeline composed of two systems, each 0.999 reliable, is
> 0.989 reliable. Much sadness. What to do?

<nitpicking>0.999*0.999=0.998001~=0.998</nitpicking>

>
> * Globally distributed warehouse: consistency models and synchronization
> problems.
>
> * Time series correlation and anomaly detection: AKA: I want an alert for
> that massive memcached bytes_out spike that doesn't also wake me up with
> false positives at 2AM.
>
>
>
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