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Cassandra: The Definitive Guide [Format Kindle]

Eben Hewitt

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Présentation de l'éditeur

What could you do with data if scalability wasn't a problem? With this hands-on guide, you'll learn how Apache Cassandra handles hundreds of terabytes of data while remaining highly available across multiple data centers -- capabilities that have attracted Facebook, Twitter, and other data-intensive companies. Cassandra: The Definitive Guide provides the technical details and practical examples you need to assess this database management system and put it to work in a production environment.

Author Eben Hewitt demonstrates the advantages of Cassandra's nonrelational design, and pays special attention to data modeling. If you're a developer, DBA, application architect, or manager looking to solve a database scaling issue or future-proof your application, this guide shows you how to harness Cassandra's speed and flexibility.

  • Understand the tenets of Cassandra's column-oriented structure
  • Learn how to write, update, and read Cassandra data
  • Discover how to add or remove nodes from the cluster as your application requires
  • Examine a working application that translates from a relational model to Cassandra's data model
  • Use examples for writing clients in Java, Python, and C#
  • Use the JMX interface to monitor a cluster's usage, memory patterns, and more
  • Tune memory settings, data storage, and caching for better performance

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Amazon.com: 3.1 étoiles sur 5  17 commentaires
65 internautes sur 68 ont trouvé ce commentaire utile 
3.0 étoiles sur 5 Filled with information but not necessarily the information you want 8 décembre 2010
Par John Armstrong - Publié sur Amazon.com
Format:Broché
I'm not a database person but I've worked with SQL databases (esp. MySQL) and have read a few papers about non-relational databases, particularly Google's Bigtable. I understand the "web-scale" data challenge and see how a distributed, fault-tolerant, tunable open-source database like Cassandra can be an incredibly useful tool for addressing it. Therefore I was really looking forward to the publication of Eben Hewitt's Cassandra, The Definitive Guide. I was hoping that it would lay out all the important things a person would need to know in order to decide whether Cassandra made sense for their project and, if it did, how specifically they would use it.

Now that the book's out and I've had a chance to read it once through, I have to say that it does not meet my expectations. The author is clearly very interested in his subject and also very anxious to share insights not only into Cassandra but into modern non-relational databases in general (to the extent of including a 25-page appendix "The Nonrelational Landscape" at the end of the book). He does a pretty good job of explaining how Cassandra works at the level of distributed storage including scaling as well as availability and consistency. And though I haven't gone through the steps, he seems to give pretty good instructions for installing, configuring and monitoring a Cassandra cluster.

What he doesn't cover nearly as well as I was hoping (and would have expected from an O'Reilly book) is data modeling in Cassandra and the actual APIs for putting data into the database and getting data out (i.e. querying). It's not that he doesn't cover these subjects at all. In fact he devotes two chapters to data modeling (Chapter 3 The Cassandra Data Model and Chapter 4 Sample Application) and two to APIs (Chapter 7 Reading and Writing Data and Chapter 8 Clients), and these chapters contain a lot of useful information. The problem is that the information I really want is either mixed in with other, for me, less important information and/or is too limited or even not present at all.

Here are some things that I would have expected to be presented in reasonably full, coherent form in a "definitive guide" to Cassandra:

Data modeling:

Column families, supercolumns and columns - what are they for, how do you use them effectively? Especially supercolumns, which, in conjunction with the intrinsically sparse data representation, allow you to blur the distinction between structure and data and store data in "wide" format and even as out-and-out row-specific lists. He touches on matters of this sort, including in the design patterns at the end of his Data Modeling chapter, but doesn't integrate them into a coherent account of how to use the Cassandra data representation model.

Lack of joins - what are the alternatives? He addresses this issue too, but mostly says, denormalize your tables and design for common queries - or even more bluntly, precompute the results of your common queries and put them into your database. This may be a good approach in some situations, but leaves a lot of questions like, when do you precompute your query results, where and how, what triggers the computation, and how do you handle data changes that invalidate previously precomputed query results (one of the problems that normalization and joins were originally designed to solve). Also, I believe he does not say very much about implementing joins and other complex queries on the client side. Does Cassandra have properties that determine more vs. less efficient ways of doing this? How important is planning for locality in your column family organization? And supercolumns for maintaining lists/sets so that you don't have to assemble them at query time?

APIs:

Primary API - what is it? As the author explains, Cassandra doesn't have a query language, so he can't offer a chapter on the Cassandra equivalent of, say, SQL for relational databases. But Cassandra does have an API that lets you put data in and get data out, if not also other things like creating and deleting column families, supercolumns and columns. I was really expecting a chapter (or appendix or whatever) listing out the complete set of API requests and responses, either in some language-neutral format or in terms of the "native" Cassandra language, i.e. Java, ideally with additional information on "bindings" for other client-side languages like PHP, Python and so on. Again the information is sort of there, but not pulled together.

Higher-level wrappers - what are they about? The author talks about Thrift and Avro as (at least somewhat) high-level languages for communicating with Cassandra, but doesn't lay out in any coherent what those languages are. These tools may be very familiar to some, but I'm sure not to all. He does provide enough information - especially in the form of external links - to make it possible to start exploring these tools, but I would have expected the book to give a pretty good idea of what they're about without having to go off and read other material.

While I am, overall, dissatisfied with the book, I found it both an interesting read and an engaging introduction to the world of Cassandra. It also undeniably offers a wealth of information, even if it's not exactly the information a person may be looking for. For this reason I'm rating it 3 stars.
23 internautes sur 23 ont trouvé ce commentaire utile 
2.0 étoiles sur 5 Disappointing: premature, lacks organization and support 5 janvier 2011
Par Aiden Mark Humpheys - Publié sur Amazon.com
Format:Broché
The information in this book is solid enough but its chaotic structure and lack of support for the code examples make it hard to justify a purchase.

The book was written to against version 0.7b2 of Cassandra. That beta status alone should be warning of the perils of premature publication. None of the code examples work (or indeed compile) with the current API (0.7b5). Downloading the latest code from the author's spartan support site offers little gain. The zip ball contains a readme file noting that the code did work once and suggesting the reader fixes it themselves.

There is a consistent pattern of requiring the reader to understand terms which are first defined several chapters later. Slices for example, or setting up the Cassandra JMX interface which is required for data loading in chapter 4 but first described in chapter 8.

Annoying, especially as there is solid information here and it's not badly written. Had the O'Reilly editors been more pro-active, ignored the me-first commercial pressures, delayed publication until the API stabilized and sorted out the structural problems in the writing this could have been a solid read.
9 internautes sur 10 ont trouvé ce commentaire utile 
2.0 étoiles sur 5 Nothing definite about this Guide 4 mars 2013
Par Rajeev Jha - Publié sur Amazon.com
Format:Broché
First up, I have nothing against the author. The author comes across as a genuine guy who is actually willing to invest energy in explanations. I just wish he had taken up a different topic. Now I am really fed-up of this whole genre of O'reilly books that do not add anything to what you can otherwise learn on the Internet for free. I bought the Indian edition (and paid only 9$)

#1) The edition I have talks about cassandra-0.7 that is already obsolete (now on 4 March, 2013 - we have 1.2)
The preferred way of accessing the store may be CQL3 now.

#2) As an application developer - The biggest concern I had was around solving my problem or data modeling. I do not want to delve too much into how to create a cluster and all. The example model of Hotel reservation is too simplistic. You are better off reading Jay Patel's Ebay tech blogs or Datastax's metric collection sample on the subject. They do a much better job of explaining the cassandra data model.

Also, any effort to introduce cassandra data modeling in terms of "equivalent RDBMS terms " is fraught with danger as cassandra is actually a big map. The book comes short on my data modeling expectations.

#3) Apart from storage, many people would be looking to run analytic on top of cassandra. It would have been great to explain how to run Hadoop/Pig on top of latest cassandra in detail.

#4) I do not/ cannot comment on how this book is for clustering and administration - because that is not my interest - please check other reviews for that.

The fact that we invest in books because they stand the test of time does not apply here. You cannot pull out this book from shelf two years down the line to check some fact or jog your memory. O'reilly sucks big time. These kinds of book are nothing but an effort to ride the latest wave of technology.
8 internautes sur 9 ont trouvé ce commentaire utile 
3.0 étoiles sur 5 Good guide to Cassandra itself but hampered by lack of clients 2 août 2011
Par Brian Tarbox - Publié sur Amazon.com
Format:Broché|Achat vérifié
This book is a fine introduction to Cassandra itself, and even to the whole genre of non relational databases. Where it falls down is if you want to actually start using Cassandra for an actual product. The fault doesn't lie with the book, but with the confused state of Cassandra clients. Basically no one codes directly to Cassandra: people code to one of the various Cassandra clients such as Thrift, Avro, Hector, Chirper, Pelops, etc. Cassandra has many clients none of which is the clear leader, and none of which really solve the full problem of writing to Cassandra.

Given that the only real way to learn system is to code to it this presents a real challenge. The current book will give you an overview and feel for Cassandra but will not by itself allow you to start using it.
1 internautes sur 1 ont trouvé ce commentaire utile 
3.0 étoiles sur 5 Interesting, not completely current, some code does not work 20 février 2011
Par John Brady - Publié sur Amazon.com
Format:Broché
Cassandra: The Definitive Guide is one of the few in-depth books available on Cassandra at the moment. For that reason, it's a good purchase in e-book format for those interested in Cassandra, and it provides a decent introduction to the approach to data used in the product. I would not purchase the paper book, because it's already outdated.

The initial chapters on downloading and installing the product get the reader started using Cassandra immediately. Then the bumps in the road appear. The current version of Cassandra requires a semicolon to end each statement in the command line interface (CLI) client - that 's missing in the book. This is noted in the errata on the O'Reilly site as "unconfirmed", and if you're coming from a MySQL/Oracle background it's something you might try, otherwise, it's frustrating.

A similar issue crops up two chapters later when the user is told to "start jconsole" to load a YAML schema file. Granted jconsole is not a core Cassandra component, but for the non-Java programmer, this probably entails another trip to Google searching for direction.

This book would be well-served by having an active web site backing it to keep pace with the changes in Cassandra. For now, it's an interesting read, but not very satisfying.

Disclaimer, I was provided access by O'Reilly Publishing to an electronic copy of this book for purposes of review.
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