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Early Release Book | Hadoop Application Architectures “Designing Real World Big Data Applications”

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Hadoop Application Architectures

Designing Real World Big Data Applications

By Mark Grover, Ted Malaska, Jonathan Seidman, Gwen Shapira

Publisher: O’Reilly Media /Release Date: July 2014

Pages: 250

Hadoop Application Arch Book cov

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With Early Release ebooks, you get books in their earliest form — the author’s raw and unedited content as he or she writes — so you can take advantage of these technologies long before the official release of these titles. You’ll also receive updates when significant changes are made, new chapters as they’re written, and the final ebook bundle.

Get expert guidance on architecting end-to-end data management solutions with Apache Hadoop. While many sources explain how to use various components in the Hadoop ecosystem, this practical book takes you through architectural considerations necessary to tie those components together into a complete tailored application, based on your particular use case.

To reinforce those lessons, the book’s second section provides detailed examples of architecture used in some of the most commonly found Hadoop applications. Whether you’re designing and implementing a new Hadoop application, or planning to integrate Hadoop into your existing data infrastructure, Hadoop Application Architectures will skillfully guide you through the process.

The Early Release edition begins with chapters that concentrate on design considerations for Data Modeling and Data Movement in Hadoop:

Explore whether your application should store data on Hadoop Distributed File System (HDFS) or HBase
Get best practices for designing an HDFS or HBase schema
Learn how to design schemas for SQL-on-Hadoop (e.g. Hive, Impala, HCatalog) tables

Table of Contents

  1. Chapter 1 Data Modeling (Available Now)

  2. Chapter 2 Data Movement (Available Now)

  3. Chapter 3 Accessing and Processing Data

  4. Chapter 4 Application Orchestration and Scheduling

  5. Chapter 5 Real-time Applications

  6. Chapter 6 Data Warehousing

  7. Chapter 7Fraud Detection

  8. Chapter 8 Clickstream Analysis

Authors:

  1. Mark Grover

    Mark is a committer on Apache Bigtop and a committer and PMC member on Apache Sentry (incubating) and a contributor to Apache Hadoop, Apache Hive, Apache Sqoop and Apache Flume projects. He is also a section author of O’Reilly’s book on Apache Hive – ProgrammingHive.

    View Mark Grover’s full profile page.

  2. Ted Malaska

    Ted is a Senior Solutions Architect at Cloudera helping clients be successful with Hadoop and the Hadoop ecosystem. Previously, he was a Lead Architect at the Financial Industry Regulatory Authority (FINRA), helping build out a number of solutions from web applications and Service Oriented Architectures to big data applicatons. He has also contributed code to Apache Flume, Apache Avro, Yarn, and Apache Pig.

    View Ted Malaska’s full profile page.

  3. Jonathan Seidman

    Jonathan is a Solutions Architect at Cloudera working with partners to integrate their solutions with Cloudera’s software stack. Previously, he was a technical lead on the big data team at Orbitz Worldwide, helping to manage the Hadoop clusters for one of the most heavily traffickedsites on the internet. He’s also a co-­founder of the Chicago Hadoop User Group and Chicago Big Data, technical editor for Hadoop in Practice, and has spoken at a number of industry conferences on Hadoop and big data,

    View Jonathan Seidman’s full profile page.

  4. Gwen Shapira

    Gwen is a Solutions Architect at Cloudera. She has 15 years of experience working with customers to design scalable data architectures. Formerly a senior consultant at Pythian,Oracle ACE Director and board member at NoCOUG. Gwen is a frequent speaker at industry conferences and maintains a popular blog.

    View Gwen Shapira’s full profile page.

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