- Taschenbuch: 324 Seiten
- Verlag: Packt Publishing (15. Juli 2011)
- Sprache: Englisch
- ISBN-10: 1849515123
- ISBN-13: 978-1849515122
- Größe und/oder Gewicht: 19 x 1,9 x 23,5 cm
- Durchschnittliche Kundenbewertung: Schreiben Sie die erste Bewertung
- Amazon Bestseller-Rang: Nr. 545.142 in Fremdsprachige Bücher (Siehe Top 100 in Fremdsprachige Bücher)
Cassandra High Performance Cookbook (Quick Answers to Common Problems) (Englisch) Taschenbuch – 15. Juli 2011
|Neu ab||Gebraucht ab|
Dieses Buch gibt es in einer neuen Auflage:
Es wird kein Kindle Gerät benötigt. Laden Sie eine der kostenlosen Kindle Apps herunter und beginnen Sie, Kindle-Bücher auf Ihrem Smartphone, Tablet und Computer zu lesen.
Geben Sie Ihre Mobiltelefonnummer ein, um die kostenfreie App zu beziehen.
Wenn Sie dieses Produkt verkaufen, möchten Sie über Seller Support Updates vorschlagen?
Über den Autor und weitere Mitwirkende
Edward Capriolo is currently System Administrator at Media6degrees where he helps design and maintain distributed data storage systems for the internet advertising industry. Edward is a member of the Apache Software Foundation and a committer for the Hadoop-Hive project. He has experience as a developer as well Linux and network administrator and enjoys the rich world of open source software.
Die hilfreichsten Kundenrezensionen auf Amazon.com
And then it's a typical Packt book - i.e. no proofreading whatsoever, not even with a MS Word spell-checker. Some people don't mind typos, they drive me nuts.
1. Lists out the kinds of things you should probably want to do with Cassandra.
2. Gives clear step-by-step guidance on how to do them.
3. Gives a brief explanation of the 'why' to do it.
This is great, because, there is plenty of writing out there on the theory of 'big data', but not that many sources of concrete information on how to do it yourself. The book has plenty of cross-referencing to other sections of the book. This helped me because instead of thinking to myself: "Didn't we just work with this setting a little while ago? How does this guidance jive with that guidance?", I was able to go look at the other sections as they are listed in the See Also section of the recipe (just like a man page!).
Although there have been some changes in Cassandra since this book was published, there were only a few examples I found where there are newer/different settings than the ones described in the book. And even then, the translation from pre-1.0 to post-1.0 was pretty easy to understand.
I recommend the book to anyone looking to learn Cassandra.
Do you remember how the GoF published real software patterns and soon folks started calling any language best practice a "pattern"? They filled books with these common sense "patterns" (reference an ArrayList using the interface Array or Collection, etc). That is the impression that I have of this book. Once I've used Cassandra heavily, I may return to this book to read the little ADD snippets of code and improve my mastery of best practices...a literal cookbook. However, there are few places where more than five sentences are strung together. This book has no exposition, so do not buy it if you are interested in casually reading about or understanding Cassandra.
One thing I particularly liked about the book is that the author does not only provide recipes or code but he also explains what is going on, frequently with pointers to papers for a more in-depth treatment of what is happening under the hood. Therefore, by reading through the book you not only learn how to solve many of the problems that arise when designing a Cassandra schema or trying to troubleshoot performance but you also get to understand the design of and technology behind Cassandra better.
Another helpful aspect of the book is that it mentions a number of third-party tools (e.g. cacti) that can be useful in troubleshooting performance. Overall, a great and highly recommended book!
One suggestion to the author: adding case studies of performance improvements of real Cassandra clusters would make the book even more useful, particularly for those readers who are running larger and more complex deployments.