Sakr, Sherif.

Big Data 2.0 Processing Systems : A Survey - Cham : Springer International Publishing, 2016. - 1 online resource (111 p.) - eBooks on Demand SpringerBriefs in Computer Science . - SpringerBriefs in Computer Science .

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 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 -- References

9783319387765 54.99 (NL),54.99 (1U)


Big data.


Electronic books.

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