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Pig Design Patterns [Englisch] [Taschenbuch]

Pradeep Pasupuleti

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Kurzbeschreibung

17. April 2014

Simplify Hadoop programming to create complex end-to-end Enterprise Big Data solutions with Pig

Overview

  • Quickly understand how to use Pig to design end-to-end Big Data systems
  • Implement a hands-on programming approach using design patterns to solve commonly occurring enterprise Big Data challenges
  • Enhances users's capabilities to utilize Pig and create their own design patterns wherever applicable

In Detail

Pig Design Patterns is a comprehensive guide that will enable readers to readily use design patterns that simplify the creation of complex data pipelines in various stages of data management. This book focuses on using Pig in an enterprise context, bridging the gap between theoretical understanding and practical implementation. Each chapter contains a set of design patterns that pose and then solve technical challenges that are relevant to the enterprise use cases.

The book covers the journey of Big Data from the time it enters the enterprise to its eventual use in analytics, in the form of a report or a predictive model. By the end of the book, readers will appreciate Pig's real power in addressing each and every problem encountered when creating an analytics-based data product. Each design pattern comes with a suggested solution, analyzing the trade-offs of implementing the solution in a different way, explaining how the code works, and the results

What you will learn from this book

  • Understand Pig's relevance in an enterprise context
  • Use Pig in design patterns that enable the data movement across platforms during and after analytical processing
  • See how Pig can co-exist with other components of the Hadoop ecosystem to create Big Data solutions using design patterns
  • Simplify the process of creating complex data pipelines using transformations, aggregations, enrichment, cleansing, filtering, reformatting, lookups, and data type conversions
  • Apply the knowledge of Pig in design patterns that deal with integration of Hadoop with other systems to enable multi-platform analytics
  • Comprehend the design patterns and use Pig in cases related to complex analysis of pure structured data

Produktinformation


Produktbeschreibungen

Über den Autor und weitere Mitwirkende

Pradeep Pasupuleti

Pradeep Pasupuleti has over 16 years of experience in architecting and developing distributed and real-time data-driven systems. Currently, his focus is on developing robust data platforms and data products that are fuelled by scalable machine-learning algorithms, and delivering value to customers by addressing business problems by juxtaposing his deep technical insights into Big Data technologies with future data management and analytical needs. He is extremely passionate about Big Data and believes that it will be the cradle of many innovations that will save humans their time, money, and lives.

He has built solid data product teams with experience spanning through every aspect of data science, thus successfully helping clients to build an end-to-end strategy around how their current data architecture can evolve into a hybrid pattern that is capable of supporting analytics in both batch and real time—all of this is done using the lambda architecture. He has created COE's (Center of Excellence) to provide quick wins with data products that analyze high-dimensional multistructured data using scalable natural language processing and deep learning techniques.

He has performed roles in technology consulting advising Fortune 500 companies on their Big Data strategy, product management, systems architecture, social network analysis, negotiations, conflict resolution, chaos and nonlinear dynamics, international policy, high-performance computing, advanced statistical techniques, risk management, marketing, visualization of high dimensional data, human-computer interaction, machine learning, information retrieval, and data mining. He has a strong experience of working in ambiguity to solve complex problems using innovation by bringing smart people together.

His other interests include writing and reading poetry, enjoying the expressive delights of ghazals, spending time with kids discussing impossible inventions, and searching for archeological sites.

You can reach him at http://www.linkedin.com/in/pradeeppasupuleti and pasupuleti.pradeepkumar@gmail.com.


In diesem Buch (Mehr dazu)
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Buchdeckel | Copyright | Inhaltsverzeichnis | Auszug | Stichwortverzeichnis | Rückseite
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Amazon.com: 5.0 von 5 Sternen  3 Rezensionen
2 von 2 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen great book with real world use cases 17. Juni 2014
Von mingxue wang - Veröffentlicht auf Amazon.com
Format:Taschenbuch
As usual from Packt Publishing, this book has a lot of practical tutorials and code examples. It is easy to follow and get things work. This book covers solving patterns for almost all problems which were encountered during my work. It is definitely a must-have Pig user manual.

I give it 5 stars, because of its use cases and machine learning algorithm implementations. It is not simple to design and implement advanced analytic algorithms in Pig. This book covers a large amount of machine learning use cases which I like it a lot.
2 von 2 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen Book for serious Pig programmers 27. Juli 2014
Von Angelo Khatib - Veröffentlicht auf Amazon.com
Format:Taschenbuch
It's not easy to find books about Apache Pig, searching on the web examples that fit your needs is a hard job.
Finally "Pig Design Patterns" has arrived and has, immediately, become my source book where I have found answers to a lot of my questions.
I've discovered different patterns that exactly fit what I was looking for.
This book should be adopted by every 'serious Pig programmer'.
5.0 von 5 Sternen Helped me tremendously! 3. Oktober 2014
Von Srini M - Veröffentlicht auf Amazon.com
Format:Taschenbuch
Well structured and articulated. A must read for all bigdata developers, data scientists as well as the tech exec. Kudos to Pradeep for organizing the subject such that it builds on itself and takes the readers to whatever depth of knowledge they are seeking. This book has become my "go-to" for architecture, ideas and reference. Great addition to my library.
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