jm + riak + cap   3

Call me maybe: Carly Rae Jepsen and the perils of network partitions
Kyle "aphyr" Kingsbury expands on his slides demonstrating the real-world failure scenarios that arise during some kinds of partitions (specifically, the TCP-hang, no clear routing failure, network partition scenario). Great set of blog posts clarifying CAP
distributed  network  databases  cap  nosql  redis  mongodb  postgresql  riak  crdt  aphyr 
may 2013 by jm
Alex Feinberg's response to Damien Katz' anti-Dynamoish/pro-Couchbase blog post
Insightful response, worth bookmarking. (the original post is at http://damienkatz.net/2013/05/dynamo_sure_works_hard.html ).
while you are saving on read traffic (online reads only go to the master), you are now decreasing availability (contrary to your stated goal), and increasing system complexity.
You also do hurt performance by requiring all writes and reads to be serialized through a single node: unless you plan to have a leader election whenever the node fails to meet a read SLA (which is going to result a disaster -- I am speaking from personal experience), you will have to accept that you're bottlenecked by a single node. With a Dynamo-style quorum (for either reads or writes), a single straggler will not reduce whole-cluster latency.
The core point of Dynamo is low latency, availability and handling of all kinds of partitions: whether clean partitions (long term single node failures), transient failures (garbage collection pauses, slow disks, network blips, etc...), or even more complex dependent failures.
The reality, of course, is that availability is neither the sole, nor the principal concern of every system. It's perfect fine to trade off availability for other goals -- you just need to be aware of that trade off.
cap  distributed-databases  databases  quorum  availability  scalability  damien-katz  alex-feinberg  partitions  network  dynamo  riak  voldemort  couchbase 
may 2013 by jm
Riak, CAP, and eventual consistency
Good (albeit draft) write-up of the implications of CAP, allow_mult, and last_write_wins conflict-resolution policies in Riak:
As Brewer's CAP theorem established, distributed systems have to make hard choices. Network partition is inevitable. Hardware failure is inevitable. When a partition occurs, a well-behaved system must choose its behavior from a spectrum of options ranging from "stop accepting any writes until the outage is resolved" (thus maintaining absolute consistency) to "allow any writes and worry about consistency later" (to maximize availability). Riak leans toward the availability end of the spectrum, but allows the operator and even the developer to tune read and write requests to better meet the business needs for any given set of data.
riak  cap  eventual-consistency  distcomp  distributed-systems  partition  last-write-wins  voldemort  allow_mult 
april 2013 by jm

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