Big Data 2 0 Processing Systems A Survey 1st edition by Sherif Sakr 3319387758 9783319387758

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ISBN 10:3319387758
ISBN 13:9783319387758
Author: Sherif Sakr

 

This book provides readers the “big picture” and a comprehensive survey of the domain of big data processing systems. For the past decade, the Hadoop framework has dominated the world of big data processing, yet recently academia and industry have started to recognize its limitations in several application domains and big data processing scenarios such as the large-scale processing of structured data, graph data and streaming data. Thus, it is now gradually being replaced by a collection of engines that are dedicated to specific verticals (e.g. structured data, graph data, and streaming data). The book explores this new wave of systems, which it refers to as Big Data 2.0 processing systems. After Chapter 1 presents the general background of the big data phenomena, Chapter 2 provides an overview of various general-purpose big data processing systems that allow their users to develop various big data processing jobs for different application domains. In turn, Chapter 3 examines various systems that have been introduced to support the SQL flavor on top of the Hadoop infrastructure and provide competing and scalable performance in the processing of large-scale structured data. Chapter 4 discusses several systems that have been designed to tackle the problem of large-scale graph processing, while the main focus of Chapter 5 is on several systems that have been designed to provide scalable solutions for processing big data streams, and on other sets of systems that have been introduced to support the development of data pipelines between various types of big data processing jobs and systems. Lastly, Chapter 6 shares conclusions and an outlook on future research challenges. Overall, the book offers a valuable reference guide for students, researchers and professionals in the domain of big data processing systems. Further, its comprehensive content will hopefully encourage readers to pursue further research on the subject.

 Big Data 2 0 Processing Systems A Survey 1st Table of contents:

1 Introduction

1.1 The Big Data Phenomenon

1.2 Big Data and Cloud Computing

1.3 Big Data Storage Systems

1.4 Big Data Processing and Analytics Systems

1.5 Book Roadmap

2 General-Purpose Big Data Processing Systems

2.1 The Big Data Star: The Hadoop Framework

2.1.1 The Original Architecture

2.1.2 Enhancements of the MapReduce Framework

2.1.3 Hadoop’s Ecosystem

2.2 Spark

2.3 Flink

2.4 Hyracks/ASTERIX

3 Large-Scale Processing Systems of Structured Data

3.1 Why SQL-On-Hadoop?

3.2 Hive

3.3 Impala

3.4 IBM Big SQL

3.5 SPARK SQL

3.6 HadoopDB

3.7 Presto

3.8 Tajo

3.9 Google Big Query

3.10 Phoenix

3.11 Polybase

4 Large-Scale Graph Processing Systems

4.1 The Challenges of Big Graphs

4.2 Does Hadoop Work Well for Big Graphs?

4.3 Pregel Family of Systems

4.3.1 The Original Architecture

4.3.2 Giraph: BSP + Hadoop for Graph Processing

4.3.3 Pregel Extensions

4.4 GraphLab Family of Systems

4.4.1 GraphLab

4.4.2 PowerGraph

4.4.3 GraphChi

4.5 Other Systems

4.6 Large-Scale RDF Processing Systems

5 Large-Scale Stream Processing Systems

5.1 The Big Data Streaming Problem

5.2 Hadoop for Big Streams?!

5.3 Storm

5.4 Infosphere Streams

5.5 Other Big Stream Processing Systems

5.6 Big Data Pipelining Frameworks

5.6.1 Pig Latin

5.6.2 Tez

5.6.3 Other Pipelining Systems

6 Conclusions and Outlook

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