Cover Image

Building a columnar database on RAMCloud database design for the low-latency enabled data center /

This book examines the field of parallel database management systems and illustrates the great variety of solutions based on a shared-storage or a shared-nothing architecture.

Main Author: Tinnefeld, Christian,
Other Authors: SpringerLink (Online service)
Format: eBook
Language: English
Published: Cham : Springer, [2015]
Physical Description: 1 online resource (xix, 130 pages) : illustrations.
Series: In-memory data management research.
Subjects:
Database design.
Database management.
Cloud computing.
LEADER 08207cam a2201189 i 4500
001 913742438
003 OCoLC
005 20240223121953.0
006 m o d
007 cr cnu|||unuuu
008 150713t20152016sz a ob 000 0 eng d
015 |a GBB8O2434  |2 bnb 
016 7 |a 019179641  |2 Uk 
020 |a 9783319207117  |q (electronic bk.) 
020 |a 3319207113  |q (electronic bk.) 
020 |z 9783319207100 
035 |a (OCoLC)913742438 
037 |a com.springer.onix.9783319207117  |b Springer Nature 
040 |a N$T  |b eng  |e rda  |e pn  |c N$T  |d GW5XE  |d N$T  |d IDEBK  |d YDXCP  |d OCLCF  |d CDX  |d EBLCP  |d DEBBG  |d KSU  |d JG0  |d IAD  |d JBG  |d ICW  |d ILO  |d ICN  |d OCLCQ  |d ESU  |d IAS  |d IOG  |d U3W  |d MERUC  |d INT  |d OCLCQ  |d WYU  |d UKMGB  |d OCLCQ  |d BRX  |d SNK  |d UKAHL  |d OCLCQ  |d WURST  |d S2H  |d OCLCO  |d OCLCQ  |d OCLCO  |d OCLCL 
049 |a COM6 
050 4 |a QA76.9.D26 
072 7 |a COM  |x 062000  |2 bisacsh 
082 0 4 |a 005.74/3  |2 23 
100 1 |a Tinnefeld, Christian,  |e author. 
245 1 0 |a Building a columnar database on RAMCloud :  |b database design for the low-latency enabled data center /  |c Christian Tinnefeld. 
264 1 |a Cham :  |b Springer,  |c [2015] 
264 4 |c ©2016. 
300 |a 1 online resource (xix, 130 pages) :  |b illustrations. 
336 |a text  |b txt  |2 rdacontent. 
337 |a computer  |b c  |2 rdamedia. 
338 |a online resource  |b cr  |2 rdacarrier. 
490 1 |a In-memory data management research,  |x 2196-8055. 
504 |a Includes bibliographical references. 
588 0 |a Online resource; title from PDF title page (SpringerLink, viewed July 16, 2015). 
505 0 0 |g Machine generated contents note:  |g 1.  |t Introduction --  |g 1.1.  |t Motivation --  |g 1.2.  |t Research Questions and Scope --  |g 1.3.  |t Outline --  |g 2.  |t Related Work and Background --  |g 2.1.  |t Current Computing Hardware Trends --  |g 2.1.1.  |t Larger and Cheaper Main Memory Capacities --  |g 2.1.2.  |t Multi-Core Processors and the Memory Wall --  |g 2.1.3.  |t Switch Fabric Network and Remote Direct Memory Access --  |g 2.2.  |t In-Memory Database Management Systems --  |g 2.2.1.  |t Column-and Row-Oriented Data Layout --  |g 2.2.2.  |t Transactional Versus Analytical Versus Mixed Workload Processing --  |g 2.2.3.  |t State-of-the-Art In-Memory Database Management Systems --  |g 2.3.  |t Parallel Database Management Systems --  |g 2.3.1.  |t Shared-Memory Versus Shared-Disk Versus Shared-Nothing --  |g 2.3.2.  |t State-of-the-Art Parallel Database Management Systems --  |g 2.3.3.  |t Database-Aware Storage Systems --  |g 2.3.4.  |t Operator Placement for Distributed Query Processing --  |g 2.4.  |t Cloud Storage Systems --  |g 2.4.1.  |t State-of-the-Art Cloud Storage Systems --  |g 2.4.2.  |t Combining Database Management and Cloud Storage Systems --  |g 2.5.  |t Classification --  |g pt. I  |t Database System Architecture for a Shared Main Memory-Based Storage --  |g 3.  |t System Architecture --  |g 3.1.  |t System Architecture -- Requirements, Assumptions, and Overview --  |g 3.2.  |t AnalyticsDB --  |g 3.3.  |t Stanford's RAMCloud --  |g 4.  |t Data Storage --  |g 4.1.  |t Mapping from Columnar Data to RAMCloud Objects --  |g 4.2.  |t Main Memory Access Costs and Object Sizing --  |g 5.  |t Data Processing --  |g 5.1.  |t Database Operators in AnalyticsDB --  |g 5.2.  |t Operator Push-Down into RAMCloud --  |g 5.3.  |t From SQL Statement to Main Memory Access --  |g pt. II  |t Database Operator Execution on a Shared Main Memory-Based Storage --  |g 6.  |t Operator Execution on One Relation --  |g 6.1.  |t Evaluating Operator Execution Strategies --  |g 6.2.  |t Optimizing Operator Execution --  |g 6.3.  |t Implications of Data Partitioning --  |g 7.  |t Operator Execution on Two Relations --  |g 7.1.  |t Grace Join --  |g 7.2.  |t Distributed Block Nested Loop Join --  |g 7.3.  |t Cyclo Join --  |g 7.4.  |t Join Algorithm Comparison --  |g 7.5.  |t Parallel Join Executions --  |g pt. III  |t Evaluation --  |g 8.  |t Performance Evaluation --  |g 8.1.  |t Analytical Workload: Star Schema Benchmark --  |g 8.2.  |t Mixed Workload: Point-of-Sales Customer Data --  |g 9.  |t High-Availability Evaluation --  |g 10.  |t Elasticity Evaluation --  |g pt. IV  |t Conclusions --  |g 11.  |t Conclusions. 
520 3 |a This book examines the field of parallel database management systems and illustrates the great variety of solutions based on a shared-storage or a shared-nothing architecture. 
520 3 |a Constantly dropping memory prices and the desire to operate with low-latency responses on large sets of data paved the way for main memory-based parallel database management systems. 
520 3 |a However, this area is currently dominated by the shared-nothing approach in order to preserve the in-memory performance advantage by processing data locally on each server. 
520 3 |a The main argument this book makes is that such an unilateral development will cease due to the combination of the following three trends: a) Today's network technology features remote direct memory access (RDMA) and narrows the performance gap between accessing main memory on a server and of a remote server to and even below a single order of magnitude. 
520 3 |a B) Modern storage systems scale gracefully, are elastic, and provide high-availability. 
520 3 |a C) A modern storage system such as Stanford's RAMCloud even keeps all data resident in the main memory. 
520 3 |a Exploiting these characteristics in the context of a main memory-based parallel database management system is desirable. 
520 3 |a The book demonstrates that the advent of RDMA-enabled network technology makes the creation of a parallel main memory DBMS based on a shared-storage approach feasible. 
650 0 |a Database design. 
650 0 |a Database management. 
650 0 |a Cloud computing. 
650 6 |a Bases de données  |x Conception. 
650 6 |a Bases de données  |x Gestion. 
650 6 |a Infonuagique. 
650 7 |a Databases.  |2 bicssc. 
650 7 |a Storage media & peripherals.  |2 bicssc. 
650 7 |a Data mining.  |2 bicssc. 
650 7 |a Business mathematics & systems.  |2 bicssc. 
650 7 |a COMPUTERS  |x Data Modeling & Design.  |2 bisacsh. 
650 7 |a Cloud computing.  |2 fast. 
650 7 |a Database design.  |2 fast. 
650 7 |a Database management.  |2 fast. 
653 0 0 |a economie. 
653 0 0 |a economics. 
653 0 0 |a bedrijfswetenschap. 
653 0 0 |a management science. 
653 0 0 |a geheugen. 
653 0 0 |a memory. 
653 0 0 |a databasebeheer. 
653 0 0 |a database management. 
653 0 0 |a gegevensverwerking. 
653 0 0 |a data processing. 
653 0 0 |a informatietechnologie. 
653 0 0 |a information technology. 
653 0 0 |a bedrijven. 
653 0 0 |a businesses. 
653 1 0 |a Management studies, Business Administration, Organizational Science (General) 
653 2 0 |a Economics (General) 
653 1 0 |a Management, bedrijfskunde, organisatiekunde (algemeen) 
653 2 0 |a Economie (algemeen) 
710 2 |a SpringerLink (Online service) 
776 0 8 |i Erscheint auch als:  |n Druck-Ausgabe  |a Tinnefeld, Christian. Building a Columnar Database on RAMCloud .  |t Database Design for the Low-Latency Enabled Data Center. 
830 0 |a In-memory data management research. 
907 |a .b49868706  |b multi  |c -  |d 160303  |e 240320 
998 |a (3)cue  |a cu  |b 240227  |c m  |d z   |e -  |f eng  |g sz   |h 0  |i 2 
948 |a MARCIVE Overnight, in 2024.03 
948 |a MARCIVE Comp, in 2023.01 
948 |a MARCIVE Over, 07/2021 
948 |a MARCIVE Comp, 2019.12 
948 |a MARCIVE Comp, 2018.05 
948 |a MARCIVE August, 2017 
948 |a MARCIVE extract Aug 5, 2017 
994 |a 92  |b COM 
995 |a Loaded with m2btab.ltiac in 2024.03 
995 |a Loaded with m2btab.elec in 2024.02 
995 |a Loaded with m2btab.ltiac in 2023.01 
995 |a Loaded with m2btab.ltiac in 2021.07 
995 |a Loaded with m2btab.elec in 2021.06 
995 |a Loaded with m2btab.ltiac in 2019.12 
995 |a Loaded with m2btab.ltiac in 2018.06 
995 |a Loaded with m2btab.ltiac in 2017.09 
995 |a Loaded with m2btab.elec in 2016 
995 |a Loaded with m2btab.elec in 2016 
995 |a OCLC offline update by CMU 
999 |e z 
999 |a cue 
989 |d cueme  |e  - -   |f  - -   |g -   |h 0  |i 0  |j 200  |k 240227  |l $0.00  |m    |n  - -   |o -  |p 0  |q 0  |t 0  |x 0  |w SpringerLink  |1 .i15042680x  |u http://ezproxy.coloradomesa.edu/login?url=https://link.springer.com/10.1007/978-3-319-20711-7  |3 SpringerLink  |z Click here for access 

In Prospector

Similar Items