Description
Practical Hadoop Migration, 1st ed.
How to Integrate Your RDBMS with the Hadoop Ecosystem and Re-Architect Relational Applications to NoSQL
Author: Lakhe Bhushan
Language: EnglishSubjects for Practical Hadoop Migration:
Keywords
RDBMS; SSADM; NoSQL; Hadoop; Lambda architecture; enterprise data warehouse; data lake; concurrency; denormalization; HDFS; SQOOP; Flume; ETL; data structures
Approximative price 42.19 €
In Print (Delivery period: 15 days).
Add to cart the book of Lakhe Bhushan305 p. · 15.5x23.5 cm · Paperback
Description
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Re-architect relational applications to NoSQL, integrate relational database management systems with the Hadoop ecosystem, and transform and migrate relational data to and from Hadoop components. This book covers the best-practice design approaches to re-architecting your relational applications and transforming your relational data to optimize concurrency, security, denormalization, and performance.
Winner of IBM?s 2012 Gerstner Award for his implementation of big data and data warehouse initiatives and author of Practical Hadoop Security, author Bhushan Lakhe walks you through the entire transition process. First, he lays out the criteria for deciding what blend of re-architecting, migration, and integration between RDBMS and HDFS best meets your transition objectives. Then he demonstrates how to design your transition model.
Lakhe proceeds to cover the selection criteria for ETL tools, the implementation steps for migration with SQOOP- and Flume-based data transfers, and transition optimization techniques for tuning partitions, scheduling aggregations, and redesigning ETL. Finally, he assesses the pros and cons of data lakes and Lambda architecture as integrative solutions and illustrates their implementation with real-world case studies.
Hadoop/NoSQL solutions do not offer by default certain relational technology features such as role-based access control, locking for concurrent updates, and various tools for measuring and enhancing performance. Practical Hadoop Migration shows how to use open-source tools to emulate such relational functionalities in Hadoop ecosystem components.
What You'll Learn
- Decide whether you should migrate your relational applications to big data technologies or integrate them
- Transition your relational applications to Hadoop/NoSQL platforms in terms of logical design and physical implementation
- Discover RDBMS-to-HDFS integration, data transformation, and optimization techniques
- Consider when to use Lambda architecture and data lake solutions
- Select and implement Hadoop-based components and applications to speed transition, optimize integrated performance, and emulate relational functionalities
Chapter 1: RDBMS Meets Hadoop: Integrating, Re-Architecting, and Transitioning
Part I: Relational Database Management Systems: A Review of Design Principles, Models, and Best Practices
Chapter 2: Understanding RDBMS Design Principles
Chapter 3: Using SSADM for Relational Design
Chapter 4: RDBMS Design and Implementation Tools
Part II: Hadoop: A Review of the Hadoop Ecosystem, NoSQL Design Principles and Best Practices
Chapter 5: The Hadoop Ecosystem
Chapter 6: Re-Architecting for NoSQL Design Principles, Models, and Best Practices
Part III: Integrating Relational Database Management Systems with the Hadoop Distributed File System
Chapter 7: Data Lake Integration Design Principles
Chapter 8: Implementing SQOOP and Flume-based Data Transfers
Part IV: Transitioning from Relational to NoSQL Design Models
Chapter 9: Lambda Architecture for Real-time Hadoop Applications
Chapter 10: Implementing and Optimizing the Transition
Part V: Case Study for Designing and Implementing a Hadoop-based Solution
Chapter 11: Case Study: Implementing Lambda Architecture
Covers the requirements and design methodologies of relational data and NoSQL models.
Written by an acknowledged Hadoop expert.
Contains many different examples from the Hadoop ecosystem.
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