PPT-Query Processing and Query Optimization

Database System Implementation CSE 507 Some slides adapted from S ilberschatz Korth and Sudarshan Database System Concepts 6 th Edition And Elamsri and Navathe Fundamentals of Database Systems 6. In addition to extensibility dynamic pro gramming and memorization based on and extended from the EXODUS and Volcano prototypes this new optimizer provides i manipulation of operator arguments using rules or functions ii operators that are both logi Dr. Bjarne Berg . 3. What We’ll Cover …. . Introduction. Performance Issues & Tips. MultiProviders and Partitioning. Aggregates. Query Design & Caching. Hardware & Servers. Designing for Performance. Group 4: . Nipun . Garg, Surabhi . Mithal. http://www-users.cs.umn.edu/~smithal/. Chapter Organization. 2. OLD Organization. 5.1 . Evaluation of Spatial Operations . 5.2 . Query Optimization . 5.3 . CSE 8330. Instructor: . Dr.Margaret. H. Dunham. Presenter: . Akshaya. . Aradhya. Introduction. Query optimization in XML databases. Query optimization in Parallel databases. Comparison. Conclusion and Future work. Query Optimization Process. (simplified a bit). Parse the SQL query into a logical tree:. identify distinct blocks (corresponding to nested sub-queries or views). . Query rewrite phase:. apply . algebraic transformations. Dr. Bjarne Berg . 3. What We’ll Cover …. . Introduction. Performance Issues & Tips. MultiProviders and Partitioning. Aggregates. Query Design & Caching. Hardware & Servers. Designing for Performance. IDOL Under . the . Hood. Techniques and algorithms. #. SeizeTheData. Read the presenter notes before presenting.. Most of the content of this presentation is contained therein.. IDOL knowledge flow. Acquisition. Processing. Carsten. Binnig, Donald . Kossmann. and Eric Lo. ICDE . 2007. Presented . by . Ankit. Shah . Bikash. Chandra. Motivation. Testing database applications requires generating test . databases. of Massive Trajectory Data based on MapReduce. Qiang. Ma, Bin Yang (. Fudan. University). Weining. . Qian. , . Aoying. Zhou (ECNU). Presented By: . Xin. Cao (Aalborg University). Outline. Introduction . CSE 8330. Conventional Query Processing. Statistics generation. Query optimization. Query execution. Unreliable cardinality . e. stimates. Complex queries. Changes in the runtime environment. Query interactivity. on OpenCL-based FPGAs. Zeke Wang. , Johns Paul, Hui Yan Cheah . (. NTU,. . Singapore), . Bingsheng He (. NUS,. Singapore), . Wei Zhang (HKUST, Hong Kong). 1. Outline. Background and Problem. Challenges. Query optimization. :. The process of choosing a suitable execution strategy for processing a query.. Two internal representations of a query:. Query Tree. Query Graph. Introduction to Query Processing (2). Chapters 12.4-12.6 and 15.2-15.3 of Cow Book. Arun Kumar. CSE 132C. Database System Implementation. Slide ACKs: Jignesh Patel. Query. Query Result. Database Server. Select R.text from . Report R, Weather W. Query Processing. Document-at-a-time. Calculates complete scores for documents by processing all term lists, one document at a time. Term-at-a-time. Accumulates scores for documents by processing term lists one at a time.