1 An Introduction to Database Tuning Spring 2002 Prof. Sang Ho Lee School of Computing, Soongsil Univ.

2 Database Tuning Database tuning is the activity of making a database application run more quickly. “More quickly” usually means higher throughput, though it may mean lower response time for some applications. Database tuning is difficult, because it requires a broad and deep understanding of applications, database systems, operating systems, hardware.

3 What is Different about Tuning Conventional query optimization research: Invent algorithms that would help make DBMSs run faster Entails changing DBMSs Does not assume knowledge of application context Tuning: Invent methods that will make my applications run faster on my DBMS Cannot change DBMSs Can make use of application context

4 Tools DEC’s RDB Expert AT&T Teradata Data Navigator’s Configurator And more

5 Further Reading D. Shasha, Database Tuning: A Principled Approach, Prentice Hall PTR, D. Shasha, Tuning Databases for High Performance, ACM Computing Surveys 28(1): , D. Shasha, Tuning Database Design for High Performance, The Computer Science and Engineering Handbook: , Allen B. Tucker ed., CRC Press, Special Issue on Self-Tuning Databases and Application Tuning, IEEE Bulletin of the Technical Committee on Data Engineering 22(2): 3-40, D. Shasha and P. Bonnet, Database Tuning: Principles, Experiments, and Troubleshoot Techniques, Morgan Kaufmann, 2002.

6 Chapter 1: Four Basic Principles Think globally, fix locally Bottlenecks are the enemy, Partitioning is the cure Start-up costs should be minimized Render onto server what is due onto server

7 Think Globally, Fix Locally Effective tuning requires a proper identification of the problem and minimalist intervention Example 1 Condition: Query is slow Tune it? Wait: Check accounting statistics to make sure it is important Tuning infrequent queries does not pay off system wide Example 2 Condition: Disk is saturated Buy a new disk? Wait: Does a query scan instead of using an index Is log on a disk by itself

8 Partitioning Breaks Bottlenecks Bottleneck = system resource that is fully utilized, creating an upper limit on the throughput Partitioning = dividing work to avoid saturating resource by dividing the load over more resource by spreading the load over time When you find a bottleneck, first try to speed up that component. If that doesn’t work, then partition Partitioning could entail additional communication expense

9 Partitioning Examples Bank has N branches. Most clients access their account data from their home branch — partition accounts pertaining to branch i in subsystem i (spatial partitioning) Contention between long transactions and on-line ones — perform the long transaction when there is little online transaction activity (for example, at night) (temporal partitioning) Lock contention on free lists — create more free lists (logical partitioning)

10 In Oracle, tuning parameter is FREE_LIST_PROC … … LATCHES Two free lists of length n … … LATCHES Four free lists of length n/2 … …

11 Start-up Costs are High; Running Costs are Low Nearly same time to read a track as to read part of one --- so scans and log writes should avoid seeks Parsing time is high --- so good to save complied queries Client/server interaction is expensive --- so retrieve set at a time Obtain the effect you want with the fewest possible start-ups

12 Render onto Server What Is Due onto Server An important design question is the allocation of work between the database system (server) and the application program (client) The relative computing resources of client and server Data buffer for compute-intensive applications in client workstations