PPT-1 Chapter 5 : Query Processing and Optimization

Group 4 Nipun Garg Surabhi Mithal httpwwwuserscsumnedusmithal Chapter Organization 2 OLD Organization 51 Evaluation of Spatial Operations 52 Query Optimization 53 . 16 5th Chapter 1316 6th Chapter 1216 Things to Learn Join algorithms Motivation Studentsid name addr age GPA Enrollsid dept cnum sec Btree index on sid age of Student table Q How do we process SELECT FROM Student WHERE sid 30 Q How do we process SE 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 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. 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. John . Sirmon. Senior Escalation Engineer – Microsoft Corporation. Microsoft CSS at PASS 2009. Session Objectives And Takeaways. Processing issues . When good cubes go bad. Troubleshooting processing simplified . 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 . 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. 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). Data Management for Big Data. 2018-2019 (. s. pring semester). Dario Della Monica. These slides are a modified version of the slides provided with the book. Özsu. and . Valduriez. , . Principles of . 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.