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Author: Alan Gates
ISBN : B0065KVFBM
New from $17.99
Format: PDF
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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
Download latest books on mediafire and other links compilation Free Programming Pig
- File Size: 1372 KB
- Print Length: 222 pages
- Page Numbers Source ISBN: 1449302645
- Simultaneous Device Usage: Unlimited
- Publisher: O'Reilly Media; 1 edition (September 29, 2011)
- Sold by: Amazon Digital Services, Inc.
- Language: English
- ASIN: B0065KVFBM
- Text-to-Speech: Enabled
X-Ray:
- Lending: Not Enabled
- Amazon Best Sellers Rank: #220,513 Paid in Kindle Store (See Top 100 Paid in Kindle Store)
- #97
in Books > Computers & Technology > Databases > Data Warehousing
- #97
in Books > Computers & Technology > Databases > Data Warehousing
Free Programming Pig
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.
By ts
The book is a very good introduction to Pig written by an insider. It does not assume any previous knowledge of the subject. However, you need some programming experience and familiarity with Hadoop concepts.
I don't give it 5 stars only because it is already not quite up-to-date.
By Anatoly Korzun
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