PPT-Chapter 23: Parallel and Distributed Transaction Processing

Distributed Transactions Local transactions Accessupdate data at only one database Global transactions Accessupdate data at more than one database Key issue how to ensure ACID properties for transactions in a system with global transactions spanning multiple database. Sadhna Kumari. OUTLINE. ACID Properties. 2-Phase Commit Protocol. TPS. Serializability. Concurrency Control Protocols. Current Research. Future. References. ACID PROPERTIES. Atomicity: . A . transaction is . -. Bhavya. . Kilari. Dr. . Yanqing. Zhang, . CSc. 8320. PREVIEW. P. ART. I. : . I. NTRODUCTION. Transaction Processing System. [. R. Chow & T. Johnson, 1997. S. Sudarshan. IIT Bombay. Derived from an earlier talk by S. . Sudarshan, presented . at the. MSRI Summer School on Distributed Systems, May/June 2012. Why Distributed Data Storage a.k.a. Cloud Storage. Andrew Lumsdaine. Indiana University. lums@osl.iu.edu. My Goal in Life. Performance with elegance. Introduction. Overview of our high-performance, industrial strength, graph library. Comprehensive features. Improving Computer Performance. What performance translates into:. Time taken to do computation. Improving performance . → reducing time taken. What key benefits improving performance can bring:. Can solve “now-computationally-attainable” problems in . THE ONLY THING I CAN. TRUST. @. ANDY_PAVLO. Thirty Years Ago…. 2. S. mall # of . CPU. . C. ores. S. mall . M. emory. . S. izes. I. NTERACTIVE . T. ransactions. Check whether user has already voted.. . Distributed transactions. 13.1 Introduction. 13.2 Flat and nested distributed transactions. 13.3 Atomic commit protocols. 13.4 Concurrency control in distributed transactions. 13.5 Distributed deadlocks. COMP3017 Advanced Databases. Dr. Nicholas Gibbins – . nmg@ecs.soton.ac.uk. 2012-2013. Overview. 2. Fragmentation. Horizontal (primary and derived), vertical, hybrid. Query processing. L. ocalisation. Dr Susan Cartwright. Dept of Physics and Astronomy. University of Sheffield. Parallel Universes. Are you unique?. Could there be another “you” differing only in what you had for breakfast this morning?. S. Sudarshan. IIT Bombay. Derived from an earlier talk by S. . Sudarshan, presented . at the. MSRI Summer School on Distributed Systems, May/June 2012. Why Distributed Data Storage a.k.a. Cloud Storage. Mohammadhossein . Behgam. Agenda. Need for parallelism. Challenges. Image processing algorithms. Data handling & Load Balancing. Communication cost & performance. What is the problem?. Image Processing applications can be very computationally demanding due to:. © . 2013 . Pearson Education, Inc.  Publishing as Prentice Hall. 1. Modern Database Management. 11. th. Edition. Jeffrey A. Hoffer, V. Ramesh, . Heikki Topi. . Objectives. Define terms. Explain business conditions driving distributed databases. Early Adopter: ASU - Intel Collaboration in Parallel and Distributed Computing Yinong Chen , Eric Kostelich , Yann -Hang Lee, Alex Mahalov , Gil Speyer, and Violet R. Syrotiuk 1 st NSF /TCPP Workshop on Parallel and Distributed Computing Education ( -. Bhavya. . Kilari. Dr. . Yanqing. Zhang, . CSc. 8320. PREVIEW. P. ART. I. : . I. NTRODUCTION. Transaction Processing System [. R. Chow & T. Johnson, 1997.