At the Forge - Cassandra
Cassandra provides a non-relational storage and retrieval mechanism (NoSQL database) that features tremendous scalability, speed and flexibility. The inclusion of super columns (and super-column families, which I didn't discuss here) gives you just enough flexibility to store a great deal of information about many users. So long as you never have to search on anything other than the primary key or join information from different users at the database level, Cassandra is a good choice.
That said, Cassandra is significantly harder to understand and administer than other non-relational databases. I think the investment of time and effort are worth it, but you shouldn't expect to be able to work with Cassandra as quickly and easily as with, say, CouchDB or MongoDB. The flip side of this issue is that administration allows you to fine-tune a number of aspects of Cassandra's networking and consistency until you reach a level with which you're comfortable.
Next month, I'll continue exploring and discussing Cassandra, looking at ways to connect multiple Cassandra boxes to a cluster—and what happens when you do so.
The Cassandra home page is at cassandra.apache.org. You might find references to another Cassandra page; it only recently “graduated” to become a full-fledged Apache project, rather than an “incubator” project; thus, some references will be out of date. This page contains download links, documentation, an actively maintained wiki and links to papers, tutorials and drivers in a number of languages.
Cassandra is based on Amazon's Dynamo, the original paper for which is useful in understanding some of the design decisions. You can read this paper at www.allthingsdistributed.com/2007/10/amazons_dynamo.html.
Two complementary video talks describing Cassandra, but aimed more at the network storage aspects (rather than the practical day-to-day usage) are at www.parleys.com/#sl=1&st=5&id=1866 and vimeo.com/5185526.
Finally, although I still find the Cassandra documentation to be a bit lacking, a growing number of blogs, tutorials and testimonials have made their way onto the Web. Three that I particularly enjoyed were Arin Sarkissian's “WTF is a SuperColumn? An Intro to the Cassandra Data Model” (arin.me/blog/wtf-is-a-supercolumn-cassandra-data-model), Evan Weaver's “Up and Running with Cassandra” (blog.evanweaver.com/articles/2009/07/06/up-and-running-with-cassandra) and Dominic Williams' “HBase vs Cassandra: why we moved” (ria101.wordpress.com/2010/02/24/hbase-vs-cassandra-why-we-moved).
Reuven M. Lerner is a longtime Web developer, architect and trainer. He is a PhD candidate in learning sciences at Northwestern University, researching the design and analysis of collaborative on-line communities. Reuven lives with his wife and three children in Modi'in, Israel.
Practical Task Scheduling Deployment
July 20, 2016 12:00 pm CDT
One of the best things about the UNIX environment (aside from being stable and efficient) is the vast array of software tools available to help you do your job. Traditionally, a UNIX tool does only one thing, but does that one thing very well. For example, grep is very easy to use and can search vast amounts of data quickly. The find tool can find a particular file or files based on all kinds of criteria. It's pretty easy to string these tools together to build even more powerful tools, such as a tool that finds all of the .log files in the /home directory and searches each one for a particular entry. This erector-set mentality allows UNIX system administrators to seem to always have the right tool for the job.
Cron traditionally has been considered another such a tool for job scheduling, but is it enough? This webinar considers that very question. The first part builds on a previous Geek Guide, Beyond Cron, and briefly describes how to know when it might be time to consider upgrading your job scheduling infrastructure. The second part presents an actual planning and implementation framework.
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With all the industry talk about the benefits of Linux on Power and all the performance advantages offered by its open architecture, you may be considering a move in that direction. If you are thinking about analytics, big data and cloud computing, you would be right to evaluate Power. The idea of using commodity x86 hardware and replacing it every three years is an outdated cost model. It doesn’t consider the total cost of ownership, and it doesn’t consider the advantage of real processing power, high-availability and multithreading like a demon.
This ebook takes a look at some of the practical applications of the Linux on Power platform and ways you might bring all the performance power of this open architecture to bear for your organization. There are no smoke and mirrors here—just hard, cold, empirical evidence provided by independent sources. I also consider some innovative ways Linux on Power will be used in the future.Get the Guide