COP5725 Advanced Database Systems

1. COP5725Advanced Database Systems Final Review Spring 2014

2. Final Exam • Time: Tuesday 04/29/2013 10am --- 12pm • Venue: LOV 103, in-class exam • Closed book/note, but you can bring a piece of cheat sheet (A4, double side) • Plan your strategy well • No calculators or other electronic devices • Laptops, IPADs, smart phones, etc. are prohibited • Any form of cheating on the examination will result in zero grade, and will be reported to the university

3. Final Exam • Bring you FSU ID to attend the final exam • 30% of your final score • Coverage • All materials taught in the class and on the textbook, starting from data storage and representation, to LSH • Seven required reading papers

4. Format • One set of true/false questions with brief answers • e.g., MapReducemodel is a better model for large-scale data than parallel databases • Answer: False. Because …… • Short-answer questions • e.g, What is the nested-loop join? What is the complexity of this join algorithm? • Several more questions • e.g., Dynamic programming for optimal join order selection • 100 points • I believe you have enough time (120 minutes)

5. Suggested Method for Study • Go over the lecture slides and study the textbook • Reread the required reading papers • Work independently on problems in HW/lectures/exercises in the textbook • Any practice– work it out before looking at solutions • Questions? • Office hours (me and TA) • Discuss with people in the class

6. Final Exam

7. User/Web Forms/Applications/DBA query transaction DDL commands Query Parser Transaction Manager DDL Processor Query Rewriter Concurrency Control Logging & Recovery Query Optimizer Query Executor Records Indexes Lock Tables Buffer: data, indexes, log, etc Buffer Manager Main Memory Storage Manager Storage data, metadata, indexes, log, etc Advanced DB Systems

8. Results are Impressive

9. Why Such Great Achievements?

10. And Many More Behind the Scene • The next one is You!

11. Data Storage and Representation • Memory Hierarchy • Speed vs. Size vs. Cost • Disk • Latency = seek + rotation + transfer • I/O cost • Random I/O vs. Sequential I/O • Data Representation in RDB Systems • Database Addresses • Pointer swizzling • Record Modification • Row Store vs. Column Store

12. Indexing • What is indexing and different types of indices • B/B+ Trees • Inverted Index and Boolean Queries • Query optimization • Multidimensional Indices and Queries • kd-tree • quad-tree • R tree • Bitmap Index

13. Query Processing • Logical vs. Physical Operators • Iterator model • Materialization vs. pipelining • One-pass algorithms • Nested-loop join • …… • Two-pass algorithms • Sort based • Hash based • Index based algorithms

14. Query Optimization • Algebraic Laws • Rule Based Optimization • Heuristic rules for selection • Cost Based Optimization • Dynamic programming • Size Estimation

15. MapReduce • What is MapReduce • General ideas • Map • Reduce • Combiner: local aggregation for optimization • Distributed File Systems • RDB vs. MapReduce • Relational Algebra in MapReduce

16. Data Mining • Data Mining and Knowledge Discovery from Data • Frequent Pattern Mining • Association rules • Closed patterns and maximal patterns • Apriori algorithms • Finding Similar Patterns • Shingles • Jaccard similarity and Minhashing • Locality sensitive hashing

17. Break a Leg!