國立虎尾科技大學 |

On Consistent and Efficient Graph Data Management.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	On Consistent and Efficient Graph Data Management./
Author:	Dubey, Ayush.
Description:	1 online resource (154 pages)
Notes:	Source: Dissertation Abstracts International, Volume: 79-10(E), Section: B.
Contained By:	Dissertation Abstracts International79-10B(E).
Subject:	Computer science. -
Online resource:	click for full text (PQDT)
ISBN:	9780438025776

On Consistent and Efficient Graph Data Management.
Dubey, Ayush.

On Consistent and Efficient Graph Data Management. - 1 online resource (154 pages)

Source: Dissertation Abstracts International, Volume: 79-10(E), Section: B.

Thesis (Ph.D.)--Cornell University, 2018.

Includes bibliographical references

This dissertation describes techniques to store and process large graphs in modern datacenters with high performance and strong consistency guarantees. Graph-structured data is ubiquitous: social networks, content networks, cryptocurrency transaction histories, and business analytics routinely store and manipulate large graphs. For reasons of scale, both in terms of data size as well as workload volume, it is necessary to store such large graphs in a distributed fashion. Moreover, graph workloads have unique characteristics, such as long running read queries interspersed with shorter updates, that naturally lead to a programming interface consisting of a hybrid of transactions and analytics. Providing efficient and consistent access to graph-structured data is a significant challenge.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9780438025776Subjects--Topical Terms:

573171
Computer science.
Index Terms--Genre/Form:

554714
Electronic books.

On Consistent and Efficient Graph Data Management.
LDR:02885ntm a2200337Ki 4500 001 916639
005 20180927111920.5
006 m o u
007 cr mn||||a|a||
008 190606s2018 xx obm 000 0 eng d
020 $a 9780438025776
035 $a (MiAaPQ)AAI10747175
035 $a (MiAaPQ)cornellgrad:10733
035 $a AAI10747175
040 $a MiAaPQ $b eng $c MiAaPQ $d NTU
100 1 $a Dubey, Ayush. $3 1190436
245 1 0 $a On Consistent and Efficient Graph Data Management.
264 0 $c 2018
300 $a 1 online resource (154 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Dissertation Abstracts International, Volume: 79-10(E), Section: B.
500 $a Adviser: Emin G. Sirer.
502 $a Thesis (Ph.D.)--Cornell University, 2018.
504 $a Includes bibliographical references
520 $a This dissertation describes techniques to store and process large graphs in modern datacenters with high performance and strong consistency guarantees. Graph-structured data is ubiquitous: social networks, content networks, cryptocurrency transaction histories, and business analytics routinely store and manipulate large graphs. For reasons of scale, both in terms of data size as well as workload volume, it is necessary to store such large graphs in a distributed fashion. Moreover, graph workloads have unique characteristics, such as long running read queries interspersed with shorter updates, that naturally lead to a programming interface consisting of a hybrid of transactions and analytics. Providing efficient and consistent access to graph-structured data is a significant challenge.
520 $a This dissertation makes three contributions. First, it describes a novel technique to order distributed transactions by introducing the concept of an ordering service. An ordering service seeks to simplify the design of modern distributed systems by factoring out the task of ordering from the core system into a separate service. Second, it details techniques that scale up the performance of a centralized ordering service by combining it with a lightweight timestamping mechanism. Third, it describes a full implementation of Weaver, a new distributed, transactional graph store that includes mechanisms for practical and efficient graph data management, such as dynamic resharding of graph partitions and caching of query results. Overall, these techniques lead to a scalable and consistent graph store that is capable of supporting modern distributed applications with high performance.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Computer science. $3 573171
655 7 $a Electronic books. $2 local $3 554714
690 $a 0984
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a Cornell University. $b Computer Science. $3 1179602
773 0 $t Dissertation Abstracts International $g 79-10B(E).
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10747175 $z click for full text (PQDT)