Big Data 2.0 Processing Systems: A Survey (SpringerBriefs in Computer Science)

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.

本書為讀者提供了大數據處理系統領域的整體概述和全面調查。在過去的十年中，Hadoop框架主導了大數據處理領域，然而最近學術界和工業界開始認識到它在多個應用領域和大數據處理場景（如結構化數據、圖形數據和流數據的大規模處理）中的局限性。因此，它正逐漸被一系列專注於特定垂直領域（如結構化數據、圖形數據和流數據）的引擎所取代。本書探討了這一新的系統浪潮，將其稱為大數據2.0處理系統。

第1章介紹了大數據現象的一般背景，第2章概述了各種通用的大數據處理系統，這些系統允許用戶為不同的應用領域開發各種大數據處理任務。接著，第3章介紹了各種在Hadoop基礎設施上支持SQL風格並在大規模結構化數據處理方面提供競爭性和可擴展性性能的系統。第4章討論了幾個設計用於解決大規模圖形處理問題的系統，而第5章的主要重點是幾個設計用於處理大數據流的可擴展解決方案，以及其他一些用於支持不同類型的大數據處理任務和系統之間的數據管道開發的系統。最後，第6章提供了結論和對未來研究挑戰的展望。

總的來說，本書為大數據處理系統領域的學生、研究人員和專業人士提供了一個有價值的參考指南。希望其全面的內容能夠鼓勵讀者進一步研究該主題。