國立虎尾科技大學 |

SQL on Big Data = Technology, Architecture, and Innovation /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	SQL on Big Data/ by Sumit Pal.
Reminder of title:	Technology, Architecture, and Innovation /
Author:	Pal, Sumit.
Description:	XVII, 157 p. 80 illus., 52 illus. in color.online resource. :
Contained By:	Springer Nature eBook
Subject:	Big data. -
Online resource:	https://doi.org/10.1007/978-1-4842-2247-8
ISBN:	9781484222478

SQL on Big Data = Technology, Architecture, and Innovation /
Pal, Sumit.

SQL on Big DataTechnology, Architecture, and Innovation /[electronic resource] :by Sumit Pal. - 1st ed. 2016. - XVII, 157 p. 80 illus., 52 illus. in color.online resource.

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.

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.

ISBN: 9781484222478

Standard No.: 10.1007/978-1-4842-2247-8doiSubjects--Topical Terms:

981821
Big data.

LC Class. No.: QA76.9.B45

Dewey Class. No.: 005.7

SQL on Big Data = Technology, Architecture, and Innovation /
LDR:03447nam a22003855i 4500 001 979838
003 DE-He213
005 20200706164201.0
007 cr nn 008mamaa
008 201211s2016 xxu| s |||| 0|eng d
020 $a 9781484222478 $9 978-1-4842-2247-8
024 7 $a 10.1007/978-1-4842-2247-8 $2 doi
035 $a 978-1-4842-2247-8
050 4 $a QA76.9.B45
072 7 $a UN $2 bicssc
072 7 $a COM021000 $2 bisacsh
072 7 $a UN $2 thema
082 0 4 $a 005.7 $2 23
100 1 $a Pal, Sumit. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1115968
245 1 0 $a SQL on Big Data $h [electronic resource] : $b Technology, Architecture, and Innovation / $c by Sumit Pal.
250 $a 1st ed. 2016.
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
347 $a text file $b PDF $2 rda
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 Big data. $3 981821
650 0 $a Database management. $3 557799
650 0 $a Data structures (Computer science). $3 680370
650 0 $a Computer organization. $3 596298
650 1 4 $a Big Data. $3 1017136
650 2 4 $a Database Management. $3 669820
650 2 4 $a Data Structures. $3 669824
650 2 4 $a Computer Systems Organization and Communication Networks. $3 669309
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9781484222461
776 0 8 $i Printed edition: $z 9781484222485
856 4 0 $u https://doi.org/10.1007/978-1-4842-2247-8
912 $a ZDB-2-CWD
912 $a ZDB-2-SXPC
950 $a Professional and Applied Computing (SpringerNature-12059)
950 $a Professional and Applied Computing (R0) (SpringerNature-43716)