Big data 2.0 processing systems [electronic resource] : a survey / Sherif Sakr.

Foreword; Preface; Acknowledgements; Contents; About the Author; 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 SQL3.6 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; References