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Cassandra High Performance Cookbook [Englisch] [Taschenbuch]

Edward Capriolo

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Kurzbeschreibung

15. Juli 2011

Over 150 recipes to design and optimize large scale Apache Cassandra deployments

  • Get the best out of Cassandra using this efficient recipe bank
  • Configure and tune Cassandra components to enhance performance
  • Deploy Cassandra in various environments and monitor its performance
  • Well illustrated, step-by-step recipes to make all tasks look easy!

In Detail

Apache Cassandra is a fault-tolerant, distributed data store which offers linear scalability allowing it to be a storage platform for large high volume websites.

This book provides detailed recipes that describe how to use the features of Cassandra and improve its performance. Recipes cover topics ranging from setting up Cassandra for the first time to complex multiple data center installations. The recipe format presents the information in a concise actionable form.

The book describes in detail how features of Cassandra can be tuned and what the possible effects of tuning can be. Recipes include how to access data stored in Cassandra and use third party tools to help you out. The book also describes how to monitor and do capacity planning to ensure it is performing at a high level. Towards the end, it takes you through the use of libraries and third party applications with Cassandra and Cassandra integration with Hadoop.

What you will learn from this book

  • Interact with Cassandra using the command line interface
  • Write programs that access data in Cassandra
  • Configure and tune Cassandra components to enhance performance
  • Model data to optimize storage and access
  • Use tunable consistency to optimize data access
  • Deploy Cassandra in single and multiple data center environments
  • Monitor the performance of Cassandra
  • Manage a cluster by joining and removing nodes
  • Use libraries and third party applications with Cassandra
  • Integrate Cassandra with Hadoop

Approach

This is a cookbook and all tasks are approached as recipes. A recipe describes a task and outlines the steps necessary to complete this task.

Some recipes in the book are examples of writing code. An example of this is a recipe that stores and accesses the entries of a phone book in Cassandra. The recipe consists of a description of the program, a full code example is given, the example is run, the output is displayed, and finally the how it works section describes the process or code in greater detail.

Other recipes in the book describe a task. An example of this is a recipe that takes a snapshot back up of data in Cassandra. This recipe contains a description of the process, it then shows how to run the snapshot command and confirm that it worked, it then explains what the snapshot command does behind the scenes, finally the 'see also' section references other related recipes such as the recipe to restore a snapshot.

Who this book is written for

This book is designed for administrators, developers, and data architects who are interested in Apache Cassandra for redundant, highly performing, and scalable data storage. Typically these users should have experience working with a database technology, multiple node computer clusters, and high availability solutions.


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Produktbeschreibungen

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.


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In diesem Buch (Mehr dazu)
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Buchdeckel | Copyright | Inhaltsverzeichnis | Auszug | Rückseite
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Amazon.com: 4.0 von 5 Sternen  9 Rezensionen
6 von 6 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen Concise, clear and very useful 20. August 2011
Von Mark - Veröffentlicht auf Amazon.com
Format:Taschenbuch
If you are planning to or already are running a Cassandra cluster, you should read this book. Like a real cookbook, it contains many recipes to carry out tasks that do come up when running Cassandra, from simple stuff like garbage collecting nodes to more complicated performance related tasks. It is immensely useful as it tells you step by step what to do, and the steps and the code contained in the book do in fact work. Besides common tasks, it also discusses more advanced topics like schema design and shows how to approach commonly occurring problems, for instance how to represent time series efficiently in Cassandra. As such, it is immensely useful once you are progressing from Cassandra novice to move serious Cassandra use where performance counts.
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.
4 von 4 Kunden fanden die folgende Rezension hilfreich
2.0 von 5 Sternen Somewhat disappointed... 21. Dezember 2012
Von Dmitri Tarassenko - Veröffentlicht auf Amazon.com
Format:Taschenbuch|Von Amazon bestätigter Kauf
The most important thing you need to know about this book is that it was written when Cassandra was at 0.7. If you are a bit familiar with Cassandra, it does NOT cover CQL (neither 2 nor 3) and it doesn't cover the use of composite types. There is still some info on SuperColumns, although officially they are not recommended anymore. I would say only about 30% of it was applicable for what I needed it for - i.e. there is some stuff still that is relevant and interesting, but if you ask me whether I got my money's worth, I would probably say no.

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.
4 von 4 Kunden fanden die folgende Rezension hilfreich
3.0 von 5 Sternen accidentally bought another packt book 3. Juli 2012
Von Jess Evans - Veröffentlicht auf Amazon.com
Format:Taschenbuch|Von Amazon bestätigter Kauf
I bought this book assuming that there would be discourse on the implementation of Cassandra and how this informs patterns for maximizing performance. I failed to recognize that it was published by Packt. What I received, as usual for Packt, is not so much a book as a developer's raw stream of consciousness stuffed with printed code that will be defunct in a few releases.

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.
2 von 2 Kunden fanden die folgende Rezension hilfreich
4.0 von 5 Sternen A clear, concise hands on walkthrough. 9. September 2011
Von Henry McBride - Veröffentlicht auf Amazon.com
Format:Taschenbuch
As a big fan of hands on books such as the `From Scratch' and `Cookbook' series I am always excited to get a chance to review new books in subjects I am interested in. Recently I was given the chance to review the Cassandra High Performance Cookbook by Edward Capriolo. And since I have been exploring several NoSQL solutions this year including MongoDB, CouchDB, Riak, HBase and Cassandra this turned out to be a good opportunity.

Like most `cookbook' style books this book is good for those who are just getting started with Cassandra as well as those with experience with it. Like a real cookbook this book gives you over 150 `receipies' that range from beginner tasks such as how to install to advanced topics such as performance tuning. So along with more common tasks, it also discusses more advanced topics like multi Datacenter deployments and working with Hadoop. The range of tasks makes it very useful once you are progressing from Cassandra novice to move serious Cassandra use.

This book also contains some value adds comming in many hands on books. Such as it covers third party tools. Also like most good hands on style book it gives you the code to look at and play with. The author also does a good job of explaining things in a in-depth manner and links to other documents when he feels it would be useful. This helps to give the reader a better understanding of how things work and makes for a more useful reading experience. Overall I thought the book was useful and worth a read!
2 von 2 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen Clear Steps That Work 4. August 2011
Von brent - Veröffentlicht auf Amazon.com
Format:Taschenbuch
By following the steps contained in this book I have been able to setup a simple single node Cassandra installation on MacOS 10.5.8. The instructions call for a Linux environment, however the clear and organized methods have allowed me to replicate this environment on a Mac. The book does a great job of laying out a clear path for each recipe. By adhering to the software requirements and recipe instructions I was able to start a Cassandra instance and test that instance all within 10 minutes. As I continue to walk through the recipes I will be sure to update this review.
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