1. Self-Managing Cost Models Shivnath Babu Stanford University

2. 2 Cost Models in Database Systems Conventional query optimization: –Enumerate query plans –Estimate physical cost of each plan (e.g., execution time, total resources--CPU & I/O--required) –Choose plan with minimum cost Estimation of physical cost is based on (operator) cost models Very important to have fairly accurate cost models

3. 3 Current Approach to Deriving Cost Models Trial and error Classic: Linear combination of CPU cost & the number of disk blocks accessed Sequential Vs. Random accesses –Data layout, data access pattern Buffer pool hit ratio –Buffer pool size, data access pattern, number of concurrent queries L1, L2, L3 cache hit ratio

4. 4 Problems with the Current Approaches Growing importance of: –Autonomic Computing –Diverse data management needs in many new apps –Non-monolithic uses of database software –Better user experience (Ex: SLAs, progress bars) Current manual approach to cost model management is a hindrance in this new world: –Hard to port across system configurations (Ex: Local disk Vs. RAID Vs. NAS Vs. Remote database) or workloads –Complex, many lines of code, hard to maintain –Assumptions (Ex: ignores interference across queries) –Severely restricts auto-configuration and plug & play

5. 5 Solution #1: Get Rid of Cost Models Use Eddies: no plan, no optimizer  no cost models Jury is still out

6. 6 #2: Automated Cost-Model Management 1.Bootstrapping--Start with: An overall objective (Ex: minimize execution time) A common-case model (Ex: CPU + Seq. I/O + Rand. I/O) A list of other factors that could affect cost (Ex: cache misses, #concurrent processes) 2.Detect deviations from model during execution Ignore deviations resulting from stats. estimation errors 3.Troubleshoot online (challenging) Does the deviation matter? What is the cause? Use extra “probe queries” 4.Update model and test: Online what-if analysis

7. 7 Epilogue Related work: –In data integration (e.g., CORDS-MDBS, Garlic) –In main-memory databases (e.g., Monet) –Not comprehensive or fully automated Self-managing cost models: –A big step toward Autonomic Database Systems –Will improve re-usability of DB software –Should improve overall performance and user- experience