PPT-parallel dbms vs map reduce

MapReduce and parallel DBMSs friends or foes Stonebraker Daniel Abadi David J Dewitt et al MAP REDUCE AND PARALLEL DBMS ARE COMPLEMENTARY In 2010 MapReduce MR has been hailed as a . Xtreme Compression, Inc. is a software design consultancy with special expertise in structured data compression. We apply our proprietary algorithms and source code to compress and encrypt structured data whenever performance beyond the reach of conventional methods is required. Xtreme Compression, Inc. is a software design consultancy with special expertise in structured data compression. We apply our proprietary algorithms and source code to compress and encrypt structured data whenever performance beyond the reach of conventional methods is required. Unlike sequential algorithms parallel algorithms cannot be analyzed very well in isolation One of our primary measures of goodness of a parallel system will be its scalability Scalability is the ability of a parallel system to take advantage of incr S. A. L. S. A. . HPC Group . http://. salsahpc.indiana.edu. School of Informatics and Computing. Indiana University. Judy . Qiu. . Thilina. . Gunarathne. . CAREER Award. Outline. Iterative . Parallel Computing. CIS . 410/. 510. Department of Computer and Information Science. Outline. What are Collectives?. Reduce Pattern. Scan Pattern. Sorting. 2. Introduction to Parallel Computing, University of Oregon, IPCC. Efficient and scalable architectures to perform pleasingly parallel, MapReduce and iterative data intensive computations on cloud environments. Thilina. . Gunarathne. (tgunarat@indiana.edu). Advisor : . Sam Madden. Physicists. Biologists. Basically Everyone Except My Bank. The Answer. Benefit(DBMS. ) ≠ . Suckiness(DBMS. ). Disadvantages of . DBMSs. are growing. Impoverished data manipulation language. Efficient and scalable architectures to perform pleasingly parallel, MapReduce and iterative data intensive computations on cloud environments. Thilina. . Gunarathne. (tgunarat@indiana.edu). Advisor : . Joint work with. Yucheng. Low. Aapo. Kyrola. Danny. Bickson. Carlos. Guestrin. Guy. Blelloch. Joe. Hellerstein. David. O’Hallaron. A New Parallel Framework for. Machine Learning. Alex. Smola. In ML we face . 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?. Quarter: Summer 2017. CSE 373: Data Structures and Algorithms. Lecture . 23: Parallelism: Map, Reduce, Analysis. Today. More on parallelism. Map & Reduce . Analysis of Efficiency. Reminder: . C. ome visit my office hours to pick up midterm. Contact: . Ibéria. Medeiros, Nuno . Neves. {. imedeiros. , nuno}@. di.fc.ul.pt. . FCiências.ID / LASIGE, . Faculdade. de . Ciências. , . Universidade. de . Lisboa. www.navigators.di.fc.ul.pt. Databases continue to be the most commonly used backend storage in enterprises, and are employed in several contexts in the electrical grid. They are often integrated with vulnerable applications, such as web frontends, that allow injection attacks to be performed. The effectiveness of such attacks steams from a . Cal Poly Pomona. What is a Database?. ?. 2. Files, Databases and Mini-world. File: A collection of records or documents dealing with one organization, person, area or subject. . Manual (paper) files. Very large volumes of data being collected. Driven by growth of web, social media, and more recently internet-of-things. Web logs were an early source of data. Analytics on web logs has great value for advertisements, web site structuring, what...