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. 1 Parallel Processing A parallel processing system is able to perform concurrent data processing to achieve faster execution time The system may have two or more ALUs and be able to execute two or more instructions at the same time Also the system m Some of the slides have been borrowed from courses taught at Stanford, Berkeley, Washington, and earlier version of CS 223 at UCI . ICS214B. Notes 11. 2. .. Distributed . Transaction. Action:. a. Liew. . Woei. Song. Muhammad Hofiz Achoson. Introduction. Transaction Processing System. What is a TPS?. an information system designed to process routine business transactions . seeks time- and cost-efficiency by automating repetitive operations in large volumes. -. Bhavya. . Kilari. Dr. . Yanqing. Zhang, . CSc. 8320. PREVIEW. P. ART. I. : . I. NTRODUCTION. Transaction Processing System. [. R. Chow & T. Johnson, 1997. 884 891 890 887 889 892 886 885 888 881 882 883 GLocks :Ef Hadoop. Spring 2012. Aviram. . Rehana. Lior. Zeno. Supervisor : Edward . Bortnikov. Agenda. The problem and . motivation. Background on databases’ access. What is done so far. Project goals. Effort assessment and roadmap . 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.. 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. Introduction. Papadakis Harris. Dept. of Engineering Informatics. ΤΕΙ . of Crete. Distributed Systems. - . Contents. Definition. Parallel. . Processing. Distributed . Computin. Clusters. Examples.