bloodredsun : The long and short of it is that Cassandra is a fantastic system for write heavy situations. What it is not good at are read heavy situations where deterministic low latency is required, which is pretty much what the pinterest guys were dealing with.
@ viktorklang : "The e-mail message could not be delivered because the user's mailfolder is full." <-- EMAIL HAS BACKPRESSURE OMG
Interesting Behind the Scenes: . … Neighborhoods
Data in Cassandra looks like a multi-level dict.
By default, Cassandra eats 1/2 of your RAM. You might want to change that ;)
He uses pycassa for his client. It's the simplest approach.
telephus is a Cassandra client for Twisted.
cassandra-dbapi2 is a Cassandra client that supports DBAPI2. It's based on Cassandra's new CQL interface.
Don't use pure Thrift to talk to Cassandra.
Cassandra is good about scaling up linearly.
There's a batch …
…completion of that migration, we started a second migration, this time from F1 ). Both of these transitions have been successful, but have involved integration pain points …to Cassandra. The first transition was key to our move from our own data center to ' cloud. The second was key to our expansion from one AWS Region to multiple geographically-distributed Regions -- today serves traffic out of two AWS Regions, one in , the other in (
…to do as effectively in prose alone. the Cassandra storage engine at is a good example. Starting at about 22:00, he explains how Cassandra uses log-structured merge trees to turn random writes into sequential i/ o. Compare that with the treatment in the Bigtable paper , or the original 2012 LSTM paper . Sylvain's explanation is much more clear by virtue of how it's presented.'s talk on
I avoid audio or video during my …
…'s , 's , and Cassandra amongst others are all using a variant or a direct copy of this very architecture.
Simple on the surface, but as usual, implementation details matter a great deal. Thankfully, Jeff Dean and Sanjay Ghemawat , the original contributors to the and BigTable infrastructure at Google released , which is more or less an exact replica of the architecture we've … earlier last year
…he ported a relational database to threedata stores: , Cassandra and .
- Greg Unrein demonstrates how to make Openmix decisions with data.
- explains how to use 3.2 with 1.9.3 on .
- two-year plan for .shares their
- shares four things you should consider when selecting a cloud provider.
…Amazon has built all of the above on top of the basic Dynamo ingredients, Cassandra living proof that it's possible. But if Amazon did reuse a lot of the existing Dynamo code base, they hid it really well. All the evidence points to at least heavy usage of a sorted storage system under the covers, which works very well with SSDs, as they make sequential writes and reads nice and fast.
No matter what it is, Amazon has done something pretty great here. They hide most of the complexity …
…went to town. The result was a combination of Google Protocol Buffers, node.js, and Cassandra. Elegant, scalable, and totally unmaintainable.
"How many devices do we expect to have?"
"Well, we hope to sell 500 in 12 months."
"How often will they need to report in?"
Are future updates included?
Yes, as content gets added, typos get fixed, and new databases pop up, I'll send updates to everyone buying the book. The updates are free. Consider buying the book a subscription for more chapters on other databases.
Are you extending the book with more databases over time?
Yes, I have an insatiable thirst to …
They use Cassandra in multiple regions, and it works well for them.
EBS snapshots can't cross regions.
There is no one size fits all solution.
The most common approaches they see involve multi-AZ configurations with a solid DR plan.
This talk summarizes the history of Amazon retail from 1995 to 2011. I think the switch to AWS was in 2011.