1,074 karma · joined April 23, 2012
Kafka is amazing, the new open source dotnet as well, and this brings both together.
https://media.ccc.de/v/32c3-7171-when_hardware_must_just_wor...
Software design and testing is hard, but what happens when each bug fix can cost months of delay and millions of dollars? In this talk we’ll take a behind-the-scenes look at the challenges in the design of a very complex, yet critical piece of hardware: the modern x86 CPU.You point about the SPOF is that you prefer distributed state inside the individual services over having events stored in the message bus? Then you're back to high coupling between the inventory manager and notifier, if the former is down the latter won't be able to send out any notifications.
When the screen is locked with password, if I hold ENTER after some
seconds the screen freezes and the lock screen crashes. After that I
have the computer fully unlocked.GNU social is a free social networking platform. It helps people in a community, company or group to exchange short status updates, do polls, announce events, or other social activities (and you can add more!). Users can choose which people to "follow" and receive only their friends' or colleagues' status messages. It provides a similar service to sites like Twitter, Google+ or Facebook, but is much more awesome.
I would love to see a derivate of it with proper async support and more useful error messages.
Write means append, to a timeseries which is keyed by a timestamp, and is identified by some name? If a write succeeds only partially, different servers have different data. And a read might return any of these versions. After some time the anti-entropy repair will kick in, and merge the diverging timeseries. Merging means taking the union of all data points.
Where do the timestamps come from, the client? So if a client retries a partially successful write, it'll have the same timestamp and will be merged during repair. Are timestamps within a timeseries monotonically increasing?
The hinted handoff sounds like it is motivated by a similar problem that the Kafka in sync replica set tackles. Do you have any views on the pros/cons of your approach via ISR sets? I think Kafka uses ZK for the ISR management which means it wouldn't work with the availability requirements of InfluxDB, but could a modified version work?
So overall InfluxDB is sacrificing lots of consistency for availability. Since the CP part of the system is actually cached, the entire system is really AP? If not, what parts are not AP? Modification of the CP part, like creation of new timeseries?
From a users perspective I could see it being useful to have a historical part of the timeseries that's guaranteed to be stable, and an in-flux part where the system hasn't settled yet. Then one could run run expensive analytics on the historical part, without having to recalculate everything on the next read since the data could have changed since then. You're already hashing your data and building a Merkle Tree, maybe that would make it possible to implement something like that.
I'm currently using Password Hasher (https://chrome.google.com/webstore/detail/password-hasher-pl...), but that only works well because I mostly use just one machine.
`:20150425.csv 0: csv 0: (`Name; `$"Credit Card") xcol select name,creditcard from (.j.k raze read0`:data.json) where 0n<>first each creditcard
I'm going to ditch LL/SC implementations, in part because they're just too unreliable and in part because they prevent the library from being able to simply offer the caller a choice - "garbage collection or not?" which in turn removes a TON of stuff which otherwise has to be explained to the end user.
As a German living in the UK i currently juggle two SIM cards, and whenever I fly back home I have to mess with the data flatrate there since it's worth activating the monthly flatrate plan even if I just use it for a day. And then I have to make sure that I don't forget to cancel the flatrate when I leave again. Not to mention that this means I have two phone numbers, and I'm not reachable on at least one of them all the time.
Cool stuff! I can see a single machine running this being loads faster than a whole elaborate cluster of php/perl/python/node servers even with some caching.
Could this also work with just the integrated web server in q? I never tried it, but I wonder why lua is involved? Is it supposed to run parts of the logic in lua? Or does just using nginx as a reverse proxy not work well?
Also, ctrl-x-e
That sounds absolutely reasonable and like a good policy.
This work might also be useful to keep 2011 MBPs with a damaged dedicated GPU working with just the Intel card. If you have a 2011 MBP and are willing to spend some time developing a software workaround that at least lets you use it with Intel only, check out https://github.com/ah-/gmux-scripts/issues/1#issuecomment-68... and https://github.com/codykrieger/gfxCardStatus/issues/150
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