'Optimistic concurrency control' presentation slideshows

15-446 Distributed Systems Spring 2009

698 views • 57 slides

798 views • 53 slides

Review Concurrency

Review Concurrency. Enterprise Systems architecture and infrastructure DT211 4 . Desirable Properties of Transactions. 1. Atomicity : A transaction is an atomic unit of processing; it is either performed in its entirety or not performed at all.

629 views • 52 slides

Dr. King-Ip Lin

CSIS 7102 Spring 2004 Lecture 5 : Non-locking based concurrency control (and some more lock-based ones, too). Dr. King-Ip Lin. Table of contents. Limitation of locking techniques Timestamp ordering View serializability Optimistic concurrency control Graph-based locking

671 views • 50 slides

Mobile Computing

Mobile Computing. Panos Papadimitratos Wireless Networks Lab Department of Electrical Engineering Cornell University. Problem Context. Mobile Computing Environment. Limited Bandwidth High Latency Intermittent Connectivity Lower Reliability Low Physical Security

871 views • 41 slides

CODA: A HIGHLY AVAILABLE FILE SYSTEM FOR A DISTRIBUTED WORKSTATION ENVIRONMENT

CODA: A HIGHLY AVAILABLE FILE SYSTEM FOR A DISTRIBUTED WORKSTATION ENVIRONMENT. M. Satyanarayanan, J. J. Kistler, P. Kumar, M. E. Okasaki, E. H. Siegel, D. C. Steere Carnegie-Mellon University. Paper highlights.

442 views • 35 slides

Distributed Transactions

Distributed Transactions. Structures of Distributed Transactions. Source: G. Coulouris et al., Distributed Systems: Concepts and Design, Third Edition. A Nested Banking Transaction. Source: G. Coulouris et al., Distributed Systems: Concepts and Design, Third Edition.

557 views • 35 slides

Transactional Concurrency Control

396 views • 28 slides

Optimistic Methods for Concurrency Control By : H.T. Kung & John T. Robinson Presenters: Munawer Saeed

Optimistic Methods for Concurrency Control By : H.T. Kung & John T. Robinson Presenters: Munawer Saeed. What is Concurrency Control. Process of managing simultaneous execution of transactions in a shared database, to ensure the serializability of transactions, is known as concurrency control.

509 views • 27 slides

Temporal and Real-Time Databases: A Survey

Temporal and Real-Time Databases: A Survey. by Gultekin Ozsoyoglu and Richard T. Snodgrass. Presentation by Didi Yao. Introduction. Survey two areas that can benefit from cross infusion: temporal and real-time DBs Temporal: time-varying info Real-time: transactions w/ time constraints

644 views • 27 slides

Concurrent Revisions: A deterministic concurrency model.

Concurrent Revisions: A deterministic concurrency model. Daan Leijen & Sebastian Burckhardt Microsoft Research (OOPSLA 2010, ESOP 2011). Consider Common Application Scenario: Shared Data and Parallel Tasks. Reader. Mutator. R. R. R. R. Reader. Shared Data. Reader. Mutator. Mutator.

492 views • 26 slides

Working of Google App Engine

Working of Google App Engine. Prof. A.R. Rele. What Is Google App Engine?. Google App Engine lets users run web applications on Google's infrastructure. App Engine applications are easy to build, easy to maintain, and easy to scale as your traffic and data storage needs grow.

727 views • 25 slides

Concurrency Control In Dynamic Database Systems

Concurrency Control In Dynamic Database Systems. Laurel Jones. Overview. Quick Review of what we already know Some Concurrency Control Model for Static Databases Concurrency Control Models for Dynamic Databases. Basic Definitions. Concurrency Control :

607 views • 22 slides

Transaction and concurrency controll

325 views • 22 slides

CIS 720

CIS 720. Concurrency Control. Timestamp-based concurrency control. Assign a timestamp ts(T) to each transaction T. Each data item x has two timestamps: rt(x): timestamp of the last transaction that read x wt(x): timestamp of the last transaction that

355 views • 21 slides

Supporting Persistent Objects In Python Jeremy Hylton jeremy@zope.com

Supporting Persistent Objects In Python Jeremy Hylton jeremy@zope.com. What is persistence?. Data lives longer than programs Files, pipes, relational databases, etc. But, discontinuity of representation Orthogonal persistence Automatic management of program state

402 views • 19 slides

379 views • 17 slides

CAP Theorem

CAP Theorem. Justin DeBrabant. Properties of Distributed Systems. Consistency all nodes have up-to-date view of data Availability every request receives a response Partition Tolerance system will continue to function if partitions are isolated from each other

857 views • 12 slides

Merger of Semi-Committed Transactions From Several Partitions Combine DCG, DCG 2 , --- DCG N

Merger of Semi-Committed Transactions From Several Partitions Combine DCG, DCG 2 , --- DCG N (minimize rollback if cycle exists) NP-complete (Davidson, Princeton) (minimum feedback vertex set problem) Consider each DCG as a single transaction Check acyclicity of this N node graph

195 views • 8 slides

Merger of Semi-Committed Transactions From Several Partitions Combine DCG, DCG 2 , --- DCG N

Merger of Semi-Committed Transactions From Several Partitions Combine DCG, DCG 2 , --- DCG N (minimize rollback if cycle exists) NP-complete (Davidson, Princeton) (minimum feedback vertex set problem) Consider each DCG as a single transaction Check acyclicity of this N node graph

151 views • 8 slides