Chapter 11 Database Performance Tuning and Query Optimization Database Systems: Design, Implementation, and Management Eighth Edition Chapter 11 Database Performance Tuning and Query Optimization

Objectives In this chapter, you will learn: Basic database performance-tuning concepts How a DBMS processes SQL queries About the importance of indexes in query processing About the types of decisions the query optimizer has to make Some common practices used to write efficient SQL code How to formulate queries and tune the DBMS for optimal performance Performance tuning in SQL Server 2005 Database Systems, 8th Edition

11.1 Database Performance-Tuning Concepts Goal of database performance is to execute queries as fast as possible Database performance tuning Set of activities and procedures designed to reduce response time of database system All factors must operate at optimum level with minimal bottlenecks Good database performance starts with good database design Database Systems, 8th Edition

Database Systems, 8th Edition

Performance Tuning: Client and Server Client side Generate SQL query that returns correct answer in least amount of time Using minimum amount of resources at server SQL performance tuning Server side DBMS environment configured to respond to clients’ requests as fast as possible Optimum use of existing resources DBMS performance tuning Database Systems, 8th Edition

DBMS Architecture All data in database are stored in data files Automatically expand in predefined increments known as extends Grouped in file groups or table spaces Table space or file group: Logical grouping of several data files that store data with similar characteristics Database Systems, 8th Edition

Basic DBMS architecture Database Systems, 8th Edition

DBMS Architecture (continued) Data cache or buffer cache: shared, reserved memory area Stores most recently accessed data blocks in RAM SQL cache or procedure cache: stores most recently executed SQL statements Also PL/SQL procedures, including triggers and functions DBMS retrieves data from permanent storage and places it in RAM Database Systems, 8th Edition

DBMS Architecture (continued) Input/output request: low-level data access operation to/from computer devices, such as memory, hard disks, videos, and printers Data cache is faster than data in data files DBMS does not wait for hard disk to retrieve data Majority of performance-tuning activities focus on minimizing I/O operations Typical DBMS processes: Listener, User, Scheduler, Lock manager, Optimizer Database Systems, 8th Edition

Database Statistics Measurements about database objects and available resources Tables, Indexes, Number of processors used, Processor speed, Temporary space available Make critical decisions about improving query processing efficiency Can be gathered manually by DBA or automatically by DBMS UPDATE STATISTICS table_name [index_name] Auto-Update and Auto-Create Statistics option 資料庫屬性 -> 自動更新統計資料 資料庫屬性 -> 自動建立統計資料 Database Systems, 8th Edition

Database Systems, 8th Edition

Ch08: dbcc show_statistics (customer, PK__CUSTOMER__24927208 ) Ch08: dbcc show_statistics (customer, CUS_UI1) 補充 SQL Server 2005 Database Systems, 8th Edition

11.2 Query Processing DBMS processes queries in three phases Parsing DBMS parses the query and chooses the most efficient access/execution plan Execution DBMS executes the query using chosen execution plan Fetching DBMS fetches the data and sends the result back to the client Database Systems, 8th Edition

Query Processing Database Systems, 8th Edition

SQL Parsing Phase Break down query into smaller units Transform original SQL query into slightly different version of original SQL code Fully equivalent Optimized query results are always the same as original query More efficient Optimized query will almost always execute faster than original query Database Systems, 8th Edition

SQL Parsing Phase (continued) Query optimizer analyzes SQL query and finds most efficient way to access data Validated for syntax compliance Validated against data dictionary Tables, column names are correct User has proper access rights Analyzed and decomposed into more atomic components Optimized through transforming into a fully equivalent but more efficient SQL query Prepared for execution by determining the execution or access plan Database Systems, 8th Edition

SQL Parsing Phase (continued) Access plans are DBMS-specific Translate client’s SQL query into series of complex I/O operations Required to read the data from the physical data files and generate result set DBMS checks if access plan already exists for query in SQL cache DBMS reuses the access plan to save time If not, optimizer evaluates various plans Chosen plan placed in SQL cache Database Systems, 8th Edition

Database Systems, 8th Edition

SQL Execution and Fetching Phase All I/O operations indicated in access plan are executed Locks acquired Data retrieved and placed in data cache Transaction management commands processed Rows of resulting query result set are returned to client DBMS may use temporary table space to store temporary data The server may send only the first 100 rows of 9000 rows Database Systems, 8th Edition

Query Processing Bottlenecks Delay introduced in the processing of an I/O operation that slows the system CPU RAM Hard disk Network Application code Database Systems, 8th Edition

SQL 敘述輸入完成後先不要執行查詢, 請按下工具列的顯示估計執行計劃鈕 ： Database Systems, 8th Edition

11.3 Indexes and Query Optimization Crucial in speeding up data access Facilitate searching, sorting, and using aggregate functions as well as join operations Ordered set of values that contains index key and pointers More efficient to use index to access table than to scan all rows in table sequentially Database Systems, 8th Edition

Indexes and Query Optimization Data sparsity: number of different values a column could possibly have Indexes implemented using: (課本 p. 453) Hash indexes B-tree indexes: most common index type. Used in tables in which column values repeat a small number of times. The leaves contain pointers to records It is self-balanced. Bitmap indexes: 0/1 DBMSs determine best type of index to use Ex: CUST_LNAME with B-tree and REGION_CODE with Bitmap indexes Database Systems, 8th Edition

B-tree and bitmap index representation Database Systems, 8th Edition B-tree and bitmap index representation

Index Representation for the CUSTOMER table SELECT CUS_NAME FROM CUSTOMER WHERE CUS_STATE=‘FL’ Requires only 5 accesses to STATE_INDEX, 5 accesses to CUSTOMER Index Representation for the CUSTOMER table

11.4 Optimizer Choices Rule-based optimizer Cost-based optimizer Preset rules and points Rules assign a fixed cost to each operation Cost-based optimizer Algorithms based on statistics about objects being accessed Adds up processing cost, I/O costs, resource costs to derive total cost Database Systems, 8th Edition

Example With the following database statistics: SELECT P_CODE, P_DESCRIPT, P_PRICE, V_NAME, V_STATE FROM PRODUCT P, VENDOR V WHERE P.V_CODE=V.V_CODE AND V.V_STATE=‘FL’; With the following database statistics: The PRODUCT table has 7000 rows The VENDOR table has 300 rows 10 vendors come from Florida 1000 products come from vendors in Florida Database Systems, 8th Edition

Database Systems, 8th Edition

Example Assume the PRODUCT table has the index PQOH_NDX in the P_QOH attribute SELECT MIN(P_QOH) FROM PRODUCT could be resolved by reading only the first entry in the PQOH_NDX index Database Systems, 8th Edition

Using Hints to Affect Optimizer Choices Optimizer might not choose best plan Makes decisions based on existing statistics Statistics may be old Might choose less efficient decisions Optimizer hints: special instructions for the optimizer embedded in the SQL command text Database Systems, 8th Edition

Oracle 版本 Database Systems, 8th Edition

SQL Server Query Hints Example select o.customerid,companyname from orders as o inner MERGE join customers as c on o.customerid = c.customerid from orders as o inner HASH join customers as c  select o.customerid,companyname from orders as o inner LOOP join customers as c select city, count(*) from customers group by city OPTION (HASH GROUP)   MS SQL Server 的語法請參考： http://msdn.microsoft.com/en-us/library/ms187713.aspx Database Systems, 8th Edition