406 karma · joined December 17, 2011
This assumes that the scheduled workloads are created equal which isn't the case. The app owners do not have control over what else gets scheduled on the node which introduces uncontrollable variability in the performance of what should be identical replicas and environments. What helps here is .. limits. The requests-to-limits ratio allows application owners to reason about the variability risk they are willing to take in relation to the needs of the application (e.g. imagine a latency-sensitive workload on a critical path vs a BAU service vs a background job which just cares about throughput -- for each of these classes, the ratio would probably be very different). This way, you can still overcommit but not by a rule-of-thumb that is created centrally by the cluster ops team (e.g. aim for 1/4) but it's distributed across each workload owner (ie application ops) where this can be done a lot more accurately and with better results. This is what the parent post is also talking about.
Consensus can be used for SMR, atomic broadcast, leader election. One can argue all of these replicate a sort of state machine. However, that dilutes the meaning of state machine replication -- replication of state with durability and performance in mind
The substring change was done to address common real scenarios, as the author of the change described here: http://www.reddit.com/r/programming/comments/1qw73v/til_orac...
* Tushar Chandra believes soon ML primitives will be available to application developers just like nowadays distributed and db primitives are becoming available in a standard way
* There was an early design decision for Sibyl not to be build on top of a custom distributed system solution but instead to rely on existing primitives such as MapReduce and GFS.
* 100B+ training examples with 100s features per example, use cases with 50TB of data
* Because logging all the features of each examples can make the logs grow extremely fast and because some features might be experimentally used and come and go, the logs would contain only the example id and then before training the model, the data will be inner joined with the example database/GFS
* Examples were stored as columns (partition by features, each file containing 1 feature for many examples) instead of the more common approach of partitioning per row where you store all features of a batch of examples in the same file. This had great benefits in terms of faster feature transformations, less data to be read because some features were less useful than others, and better compression of the data. Further feature compression achieved by finding all unique feature values and mapping them to numbers in a Huffman encoding way. Total compression achieved was 3-5 times
Towards the end, the talk contains some use cases with big numbers (throughput per core, for e.g.) worth checking out
- by far the thing I like the most is the streak counter on the dailies. It's quite rewarding to see you've done your morning light workout 120+ days in a row -- there's just no chance that you are gonna break that chain just so that you nap 10 more minutes!
- low management overhead - I usually spend 1-2 minutes on the website
- character gamification: getting random food and pet drops and critical chance for gold rewards; upgrading items with that gold -- all of these are completely useless :) but even so, these things do give you a tiny mental push to do that extra remaining task. Health and Experience points have similar effects -- I've had days where my character was low health and it was getting towards the end of the day (you lose health if you missed some dailies), which made me consider whether I could quickly achieve one of the remaining tasks
- distinction between daily tasks that are a 'must' and habits that are 'nice to have' but I don't want to do every day.
I don't use the social aspect of it, so I cannot comment on that.
As for DP, I think it also comes very close to being the same as the above two. The one difference I can think of is that with DP you often have access to the entire build-up data structure you are creating, rather than only the latest (previous) level you have with an iterative process.
I had applied through Amazon's website for a graduate position nearly 2 months ago and according to the dashboard, my application is still under review but I have never heard from anyone. I think my application has been stuck in some limbo and is now invisible to HR. I tried looking for a relevant email so that I can follow-up but this has been impossible. Granted, I found a graduate email I had written down 1 year ago but so far haven't had any reply and the email seems deprecated because its not advertised on the website anymore. Even on on-campus events, Amazon recruiters would give only the website address, no emails.
Could anyone perhaps point me to someone I could ask to have a look?
edit: To clarify, I am certain the application has not been rejected. I also do believe I am at least worth looking into hehe ;)
Understandable given your size yet personally quite disappointing :( Any plans for sponsoring visas in the near future?
Quite a statement especially on the background of the other companies involved. Any substantial arguments for that? Until recently, Google had not filed even a single patent lawsuit [1] and so far still has not done so against Apple, MS, and the like, afaik. Meanwhile, the 'rockstars' have been going rampant [2].
[1] http://www.fosspatents.com/2013/02/google-files-first-patent...
Here's a more civil answer that does not convey what I think such whines should be treated with here. No, I don't find it ironical. In fact, I think it's great precisely because they have bad customer support. It means they recognize such problems and do want to improve things (sure, maybe with profit in mind. What's wrong with that). Yes, helpouts does not change their customer support the slightest bit. But how much of an issue is it for non-tech people, compared to any other kind of expert help one may need, ? Look outside the tech bubble for a second. I quite agree with kolya3's comment.
It's safe to say that part of the reason why Google has such a notoriously bad customer support is the scale at which they operate. And what do they do? They solve a much bigger problem with precisely this same scale. Isn't that at the very core of what Google does, is about, is?! For good and bad, Google == scale. So no, I don't find it ironical. I think it is exactly the kind of thing they should do. It doesn't matter if this works or not, does not matter if it's killed in 6 months or not, it does not matter if the NSA sees that a guy showed you how to flip pizza dough in the air. It is precisely the kind of attitude they should have.
Last thing. I look at the comments in this thread and it's bitter negativity all the way down. Can seriously none of you see any value in this?! None of you, members and readers of this community about STARTUPS see any business opportunity here?! A chance to create value and grow?! And no, just because it may get killed soon does not immediately mean such opportunity should be ignored. For a niche business leveraging Google's userbase even for a month can mean massive growth. If the service dies, so what, your new clients already know you exist and (hopefully) satisfied with your work.
> "Its not been integrated into Mesa or Wine yet. It'll be 1yr+ til that happens and more until it feeds into Ubuntu and other distros. Even then, you'll only be able to play the game through WINE, since this allows native DirextX9c thru Wine, not magically making all games work in Linux. Before Wine has converted DirectX9c to OpenGL then to gpu drivers, which caused slow down and incompatibility issues, now its going to be Wine with DirectX9c native to gpu driver, which should reduce lag and incompatibility issues. Only opensource drives will get this benefit though, since this state tracker is just for gallium3D opensource drivers."