SQL on Big Data Technology, Architecture, and Innovation /

Learn various commercial and open source products that perform SQL on Big Data platforms. You will understand the architectures of the various SQL engines being used and how the tools work internally in terms of execution, data movement, latency, scalability, performance, and system requirements. Th...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριος συγγραφέας: Pal, Sumit (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Berkeley, CA : Apress : Imprint: Apress, 2016.
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
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020 |a 9781484222478  |9 978-1-4842-2247-8 
024 7 |a 10.1007/978-1-4842-2247-8  |2 doi 
040 |d GrThAP 
100 1 |a Pal, Sumit.  |e author. 
245 1 0 |a SQL on Big Data  |h [electronic resource] :  |b Technology, Architecture, and Innovation /  |c by Sumit Pal. 
264 1 |a Berkeley, CA :  |b Apress :  |b Imprint: Apress,  |c 2016. 
300 |a XVII, 157 p. 80 illus., 52 illus. in color.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
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505 0 |a Chapter 1: Introduction—Why SQL on Big Data/Hadoop? -- Chapter 2: SQL on Big Data/Hadoop—Challenges and Solutions -- Chapter 3: Architectures – Batch.-Chapter 4: Architectures – Interactive -- Chapter 5: Architectures – Streaming -- Chapter 6: Innovations -- Chapter 7: Appendix. 
520 |a Learn various commercial and open source products that perform SQL on Big Data platforms. You will understand the architectures of the various SQL engines being used and how the tools work internally in terms of execution, data movement, latency, scalability, performance, and system requirements. This book consolidates in one place solutions to the challenges associated with the requirements of speed, scalability, and the variety of operations needed for data integration and SQL operations. After discussing the history of the how and why of SQL on Big Data, the book provides in-depth insight into the products, architectures, and innovations happening in this rapidly evolving space. SQL on Big Data discusses in detail the innovations happening, the capabilities on the horizon, and how they solve the issues of performance and scalability and the ability to handle different data types. The book covers how SQL on Big Data engines are permeating the OLTP, OLAP, and Operational analytics space and the rapidly evolving HTAP systems. You will learn the details of: Batch Architectures—an understanding of the internals and how the existing Hive engine is built and how it is evolving continually to support new features and provide lower latency on queries Interactive Architectures—an understanding of how SQL engines are architected to support low latency on large data sets Streaming Architectures—an understanding of how SQL engines are architected to support queries on data in motion using in-memory and lock-free data structures Operational Architectures—an understanding of how SQL engines are architected for transactional and operational systems to support transactions on Big Data platforms Innovative Architectures—an exploration of the rapidly evolving newer SQL engines on Big Data with innovative ideas and concepts. 
650 0 |a Computer science. 
650 0 |a Computer organization. 
650 0 |a Data structures (Computer science). 
650 0 |a Database management. 
650 1 4 |a Computer Science. 
650 2 4 |a Big Data. 
650 2 4 |a Database Management. 
650 2 4 |a Data Structures. 
650 2 4 |a Computer Systems Organization and Communication Networks. 
710 2 |a SpringerLink (Online service) 
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776 0 8 |i Printed edition:  |z 9781484222461 
856 4 0 |u http://dx.doi.org/10.1007/978-1-4842-2247-8  |z Full Text via HEAL-Link 
912 |a ZDB-2-CWD 
950 |a Professional and Applied Computing (Springer-12059)