Practical Hadoop migration : how to integrate your RDBMS with the Hadoop ecosystem and re-architect relational applications to NoSQL / Bhushan Lakhe.
Lakhe, Bhushan, author.
2016
QA76.9.D338
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Title Practical Hadoop migration : how to integrate your RDBMS with the Hadoop ecosystem and re-architect relational applications to NoSQL / Bhushan Lakhe.
Author Lakhe, Bhushan, author.
ISBN 9781484212875 (electronic book)
1484212878 (electronic book)
9781484212882
DOI https://doi.org/10.1007/978-1-4842-1287-5
Published [Berkeley, CA] : Apress, 2016.
Distributor New York, NY : Distributed to the book trade worldwide by Springer,
Copyright ©2016
Language English
Description 1 online resource (xxiv, 305 pages) : illustrations.
Item Number 10.1007/978-1-4842-1287-5 doi
Call Number QA76.9.D338
Dewey Decimal Classification 005.74
004
Summary 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 The requirements and design methodologies of relational data and NoSQL models How to decide whether you should migrate your relational applications to big data technologies or integrate them How to transition your relational applications to Hadoop/NoSQL platforms in terms of logical design and physical implementation RDBMS-to-HDFS integration, data transformation, and optimization techniques The situations in which Lambda architecture and data lake solutions should be considered How to select and implement Hadoop-based components and applications to speed transition, optimize integrated performance, and emulate relational functionalities Who This Book Is For The primary readership for Practical Hadoop Migration is database developers, database administrators, enterprise architects, Hadoop/NoSQL developers, and IT leaders. Its secondary readership is project and program managers and advanced students of database and management information systems.
Note Includes index.
Access Note Access limited to authorized users.
Digital File Characteristics text file PDF
Source of Description Online resource; title from PDF title page (SpringerLink, viewed August 24, 2016).
Available in Other Form Print version: 9781484212882
Linked Resources Online Access
Record Appears in Online Resources > Ebooks
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At a Glance; Contents; Foreword; About the Author; About the Technical Reviewer; Acknowledgments; Introduction; Chapter 1: RDBMS Meets Hadoop: Integrating, Re-Architecting, and Transitioning; Conceptual Differences Between Relational and HDFS NoSQL Databases; Relational Design and Hadoop in Conjunction: Advantages and Challenges; Type of Data; Data Volume; Business Need; Deciding to Integrate, Re-Architect, or Transition; Type of Data; Type of Application; Business Objectives; How to Integrate, Re-Architect, or Transition; Integration; Re-Architecting Using Lambda Architecture

Batch LayerServing Layer; Speed Layer; Transition to Hadoop/NoSQL; Type of Data; Data Volume; Data Distribution; Migrating the Data; Summary; Part I: Relational Database Management Systems: A Review of Design Principles, Models and Best Practices; Chapter 2: Understanding RDBMS Design Principles; Overview of Design Methodologies; Top-down; Bottom-up; SSADM; Exploring Design Methodologies; Top-down; Bottom-up; SSADM; Feasibility Study; Investigation of the Current Environment; Business System Options; Requirements Specification; Technical System Options; Logical Design; Physical Design

Pros and Cons of SSADMComponents of Database Design; Normal Forms; First Normal Form; Second Normal Form; Third Normal Form; Keys in Relational Design; Optionality and Cardinality; Supertypes and Subtypes; Summary; Chapter 3: Using SSADM for Relational Design; Feasibility Study; Project Initiation Plan; Requirements and User Catalogue; Requirements Catalogue; User Catalogue; Current Environment Description; Current System Description; Current Physical Data Flow Model; Current Logical Data Model; Proposed Environment Description; Business Activity Model; Data Specification

Function SpecificationProblem Definition; Feasibility Study Report; Requirements Analysis; Investigation of Current Environment; Current Data Flow Model; Current Logical Data Model; Requirements Catalogue; User Catalogue; Logical Data Store/Entity Cross-Reference; Logical View of Current Services and System Scope; Business System Options; Requirements Specification; Data Flow Model; Logical Data Model; Function Definitions; GetPlayerInjuryInfo; GetPlayerChronicCondInfo; GetPlayerContractDetails; GetPlayerScheduleInfo; CalculateLossOfPlayPremium; EvalLossOfPlayClaim

Effect Correspondence Diagrams (ECDs)Entity Life Histories (ELHs); Logical System Specification; Technical Systems Options; Logical Design; Update Processing Model; Enquiry Processing Model; Data Catalogue; Physical Design; Logical to Physical Transformation; Space Estimation Growth Provisioning; Optimizing Physical Design; Summary; Chapter 4: RDBMS Design and Implementation Tools; Database Design Tools; CASE tools; Building and Using Design Layers; Categorizing Design Using Subject Areas; Display Level of a Model; Forward and Reverse Engineering; Creating Reusable Components

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