前言 Cassandra was open-sourced by Facebook in July 2008. This original version of Cassandra was written primarily by an ex-employee from Amazon and one from Microsoft. It was strongly influenceyd by Dynamo, Amazon's pioneering distributed key/value database. Cassandra implements a Dynamo-style replication model with no single point of failure, but adds a more powerful "column family" data model.
I became involved in December of that year, when Rackspace asked me to build them a scalable database. This was good timing, because all of today's important open source scalable databases were available for evaluation, Despite initially having only a single major use case, Cassandra's underlying architecture was the strongest, and I
directed my efforts toward improving the code and building a community.
Cassandra was accepted into the Apache Incubator, and by the time it graduated in March 2010, it had become a true open source success story, with committers from Rackspace, Digg, Twitter, and other companies that wouldn't have written their own
database from scratch, but together built something important.
Today's Cassandra is much more than the early system that powered (and still powers) Facebook's inbox search; it has become "the hands-down winner for transaction
processing performance:' to quote Tony Bain, with a deserved reputation for reliability and performance at scale.
As Cassandra matured and began attracting more mainstream users, it became clear that there was a need for commeraal support; thus, Matt Pfeil and I cofounded Riptano in April 2010. Helping drive Cassandra adoption has been very rewarding, espeaally seeing the uses that don't get discussed in public.
Another need has been a book like this one. Like many open source projects, Cassandra's documentation has historically been weak. And even when the documentation
ultimately improves, a book-length treatment like this will remain useful.
作者简介 Jeff Carpenter,精品国际酒店集团(Choice Hotels International)的一名系统架构师,在服务业和国防工业有着20年的从业经验。他的兴趣包括SOA/微服务、大规模系统架构设计以及数据架构。
以下为对购买帮助不大的评价