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Programming Pig [Englisch] [Taschenbuch]

Alan Gates

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Kurzbeschreibung

2. November 2011
This guide is an ideal learning tool and reference for Apache Pig, the open source engine for executing parallel data flows on Hadoop. With Pig, you can batch-process data without having to create a full-fledged application—making it easy for you to experiment with new datasets. Programming Pig introduces new users to Pig, and provides experienced users with comprehensive coverage on key features such as the Pig Latin scripting language, the Grunt shell, and User Defined Functions (UDFs) for extending Pig. If you need to analyze terabytes of data, this book shows you how to do it efficiently with Pig.* Delve into Pig’s data model, including scalar and complex data types* Write Pig Latin scripts to sort, group, join, project, and filter your data* Use Grunt to work with the Hadoop Distributed File System (HDFS)* Build complex data processing pipelines with Pig’s macros and modularity features* Embed Pig Latin in Python for iterative processing and other advanced tasks* Create your own load and store functions to handle data formats and storage mechanisms* Get performance tips for running scripts on Hadoop clusters in less time

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Alan Gates, a member of Yahoo's Pig development team, is responsible for company's implementation of the language, including programming interfaces and the overall design. He has presented Pig at numerous conferences and user groups, universities, and at companies using Pig. Alan oversaw the rewriting of nearly the entire code base when Pig moved from a research project to a production project.

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Amazon.com: 4.0 von 5 Sternen  13 Rezensionen
14 von 14 Kunden fanden die folgende Rezension hilfreich
2.0 von 5 Sternen Lacks Editorial Oversight 27. März 2013
Von ts - Veröffentlicht auf Amazon.com
Format:Taschenbuch|Verifizierter Kauf
The book presents an advanced introduction to PIG. Its a book by an insider for insiders and not an introduction to PIG itself. You may end up producing code to run through some data, but may not necessarily gain any understanding.

The book reads like a blog. Beyond spell check, it has no editorial oversight whatsover. the content order is adhoc it goes from one topic to another without any apparent continuity. for example, right after a cursory introduction to Map Reduce and PIG, the discussion goes into an arcane details of commandline and flag settings without any context.

the book covers a whole lot of concepts, but the introduction of these concepts itself is weak. For example, projections are introduced as something PIG has in common with SQL.

book itself is -2 stars. -1 for amazon's kindle & oreilly. the publishing quality in this book is horrible. the code fonts smaller than main text, uneven spacing etc. default settings on freely available web publishing softwares produces better content than what amazon and orielly have produced here.
1 von 1 Kunden fanden die folgende Rezension hilfreich
3.0 von 5 Sternen Just OK 17. September 2013
Von Siddhardha - Veröffentlicht auf Amazon.com
Format:Taschenbuch
The company I was working for started using Big Data technologies recently and we were all expected to come up to speed quickly. For PIG, this is the only book I could find. Luckily it's available on Safari, so I didn't have to buy it myself (I didn't feel that the content justified the cost of purchasing this book). You can find a good chunk of the content in this book in online blogs, tutorials, and wikis, but it helped to have this book by my side when we were working on a project since all the relevant information is in a single location. Some of the information in this book is outdated. For instance, it talks about Boolean data type not being supported but the recent versions of PIG do, so be sure to refer to PIG docs from time to time to make sure you have the latest information. PIG is a relatively immature framework - the authors admit this to a certain extent in the book by mentioning that much of the tuning/optimization effort is outsourced to the user (unlike databases which make an effort to optimize queries). This book includes some insights into how to tune for performance (e.g: what types of JOINs to use and when, writing UDFs for performance) which is certainly helpful but the general tone is along the lines "here are somethings to look for but you need to test and find what works best yourself" - in other words, comprehensive examples illustrating the concepts are missing. Like a lot of other books, some typos exist in this book although it's not too hard to figure out. A basic understanding of hadoop is necessary to use this book but a solid foundation for hadoop is not necessarily required (although it helps a lot). All in all, if you are looking for a single place to refer to for PIG related docs, get this book.
3.0 von 5 Sternen Mediocre primer. 7. August 2014
Von AOL Jack - Veröffentlicht auf Amazon.com
Format:Kindle Edition|Verifizierter Kauf
Has some good info especially on how to extend pig functionality, but it leaves a lot to be desired as a primer on how to use pig. Most of the examples are poorly explained. To be honest I learned more about some of the thinking behind pig than I learned about how actually use pig. This book needs a new seriously upgraded edition. It only got three stars because it has no competition.
4.0 von 5 Sternen Good & Comprehensive, but lacks the last bit of analytic capability I was hoping for 26. Juni 2014
Von Frank D. Evans - Veröffentlicht auf Amazon.com
Format:Kindle Edition|Verifizierter Kauf
The book is written pretty well, and the examples are clear and easy to follow for the most part. The only lacking aspect in my opinion was a deeper delve into the analytic capabilities for Pig. This is minor, and may actually be a good prompt for a follow-up "Pig Cookbook". Other than that, this is a great reference and has proven very useful.
5.0 von 5 Sternen A wonderfully clear, concise and short book. 21. Juni 2014
Von Daniel F. Montagnese - Veröffentlicht auf Amazon.com
Format:Taschenbuch|Verifizierter Kauf
In learning 'pig', I was at first stalled in learning about accessing the data structures. Reading this book saved me much time in gaining the necessary understanding.
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