PPT-Joins on Encoded and Partitioned

Data JaeGil Lee 2 Gopi Attaluri 3 Ronald Barber 1 Naresh Chainani 3 Oliver Draese 3 Frederick Ho 5 Stratos Idreos 4 MinSoo Kim 6 Sam Lightstone 3 Guy Lohman. HRP223 – 2012. October 29, 2012 . Copyright © . 1999-2012 . Leland Stanford Junior University. All rights reserved.. Warning: This presentation is protected by copyright law and international treaties. Unauthorized reproduction of this presentation, or any portion of it, may result in severe civil and criminal penalties and will be prosecuted to maximum extent possible under the law.. Data. Jae-Gil Lee. 2*. . Gopi. Attaluri. 3. Ronald Barber. 1. . Naresh. Chainani. 3. Oliver Draese. 3. Frederick Ho. 5. . Stratos. Idreos. 4*. Min-Soo Kim. 6*. Sam Lightstone. 3. Guy Lohman. LPAR 2008 . –. Doha, Qatar. Nikolaj . Bjørner. , . Leonardo de Moura. Microsoft Research. Bruno . Dutertre. SRI International. Satisfiability Modulo Theories (SMT). Accelerating lemma learning using joins. Ashwin Rao . Karavadi, Rakesh . Parida. Microsoft IT. Data Partitioning. Why?. Split a table into manageable partitions. Improve data access performance. Simplify maintenance. Partitioned Views. Available since SQL Server 7.0. DBMS for Semantic Web data Management. . . Surabhi Mithal. Nipun Garg. Daniel J. Abadi, Adam Marcus, Samuel R. Madden, and Kate Hollenbach. 2009. The VLDB Journal.. DBMS for Semantic Web data Management. . . Surabhi Mithal. Nipun Garg. Introduction to semantic web : An example. ISBN. Author. Title. Publisher. Year. 0006511409X. Agenda. Opening tables. The interface. Working with columns. Working with records. Making selections. Advanced table tools. Add fields. Relates (links). Joins. Editing table content. Editing table structure. HRP223 – . 2011. October . 31, . 2011 . Copyright © . 1999-2011 . Leland Stanford Junior University. All rights reserved.. Warning: This presentation is protected by copyright law and international treaties. Unauthorized reproduction of this presentation, or any portion of it, may result in severe civil and criminal penalties and will be prosecuted to maximum extent possible under the law.. Merging Data (with SQL). HRP223 – 2009. October 19, 2009 . Copyright © . 1999-2009 . Leland Stanford Junior University. All rights reserved.. Warning: This presentation is protected by copyright law and international treaties. Unauthorized reproduction of this presentation, or any portion of it, may result in severe civil and criminal penalties and will be prosecuted to maximum extent possible under the law.. 1. Recap. Map-reduce ✔️. Algorithms with multiple map-reduce steps. Naïve . bayes. test routine for large datasets and large models. Cleanly describing these algorithms. workflow (or dataflow) languages . 1. Sim. Joins on Product Descriptions. Surface s. imilarity . can be . high. for descriptions of . distinct. items:. AERO TGX-Series Work Table -42'' x 96'' Model 1TGX-4296 All tables shipped KD AEROSPEC- 1TGX Tables are . Caching 50.5* COS 518: Advanced Computer Systems Lecture 9 Michael Freedman * Half of 101 Tradeoff Fast: Costly, small, close Slow: Cheap, large, far Based on two assumptions Temporal location: Will be accessed again soon  — A quantitative understanding of neuronal computations can be a c hieved by monitori ng membrane potential reported by genetically - encoded voltage indicators (GEVIs) . T he fluorescent F. k. m. 1. F. k. m. 2. . F. k. m. l. t. . …. CBC-MAC vs. CBC-mode. CBC-MAC is . deterministic. (no IV). MACs do not need to be randomized to be secure. Verification is done by re-computing the result.