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Introduction to SQL Tuning

Brown Bag. Introduction to SQL Tuning. Three essential concepts. Introduction to SQL Tuning. How to speed up a slow query? Find a better way to run the query Cause the database to run the query your way. Introduction to SQL Tuning. How does a database run a SQL query? Join order

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Introduction to SQL Tuning

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  1. Brown Bag Introduction to SQL Tuning Three essential concepts

  2. Introduction to SQL Tuning • How to speed up a slow query? • Find a better way to run the query • Cause the database to run the query your way

  3. Introduction to SQL Tuning How does a database run a SQL query? Join order Join method Access method

  4. Example Query SQL> select 2 sale_date, product_name, customer_name, amount 3 from sales, products, customers 4 where 5 sales.product_number=products.product_number and 6 sales.customer_number=customers.customer_number and 7 sale_date between 8 to_date('01/01/2012','MM/DD/YYYY') and 9 to_date('01/31/2012','MM/DD/YYYY') and 10 product_type = 'Cheese' and 11 customer_state = 'FL'; SALE_DATE PRODUCT_NAME CUSTOMER_NAME AMOUNT --------- ------------ ----------------- ---------- 04-JAN-12 Feta Sunshine State Co 300 02-JAN-12 Chedder Sunshine State Co 100 05-JAN-12 Feta Green Valley Inc 400 03-JAN-12 Chedder Green Valley Inc 200

  5. Join Order Join Order = order in which tables in from clause are joined Two row sources at a time Row source: Table Result of join View as tree – execution tree or plan

  6. Join Order – sales, products, customers join 2 join 1 customers sales products

  7. Join Order as Plan Execution Plan ---------------------------------------------------------- 0 SELECT STATEMENT 1 0 HASH JOIN 2 1 HASH JOIN 3 2 TABLE ACCESS (FULL) OF 'SALES' (TABLE) 4 2 TABLE ACCESS (FULL) OF 'PRODUCTS' (TABLE 5 1 TABLE ACCESS (FULL) OF 'CUSTOMERS' (TABLE)

  8. Bad Join Order – customers, products, sales join 2 join 1 sales customers products

  9. Cartesian Join – all products to all customers SQL> -- joining products and customers SQL> -- cartesian join SQL> SQL> select 2 product_name,customer_name 3 from products, customers 4 where 5 product_type = 'Cheese' and 6 customer_state = 'FL'; PRODUCT_NAME CUSTOMER_NAME ------------ ----------------- Chedder Sunshine State Co Chedder Green Valley Inc Feta Sunshine State Co Feta Green Valley Inc

  10. Plan with Cartesian Join Execution Plan ---------------------------------------------------------- 0 SELECT STATEMENT Optimizer=ALL_ROWS 1 0 MERGE JOIN (CARTESIAN) 2 1 TABLE ACCESS (FULL) OF 'PRODUCTS' (TABLE) 3 1 BUFFER (SORT) 4 3 TABLE ACCESS (FULL) OF 'CUSTOMERS' (TABLE)

  11. Selectivity Selectivity = percentage of rows accessed versus total rows Use non-joining where clause predicates sale_date, product_type, customer_state Compare count of rows with and without non-joining predicates

  12. Count(*) to get selectivity -- # selected rows select count(*) from sales where sale_date between to_date('01/01/2012','MM/DD/YYYY') and to_date('01/31/2012','MM/DD/YYYY'); -- total #rows select count(*) from sales;

  13. Selectivity of sub-tree SQL> select count(*) from sales, products 3 where 4 sales.product_number=products.product_number and 5 sale_date between 6 to_date('01/01/2012','MM/DD/YYYY') and 7 to_date('01/31/2012','MM/DD/YYYY') and 8 product_type = 'Cheese'; COUNT(*) ---------- 4 SQL> select count(*) 2 from sales, products 3 where 4 sales.product_number=products.product_number; COUNT(*) ---------- 4

  14. Modifying the Join Order Tables with selective predicates first Gather Optimizer Statistics Estimate Percent Histogram on Column Cardinality Hint Leading Hint Break Query into Pieces

  15. Gather Optimizer Statistics -- 1 - set preferences begin DBMS_STATS.SET_TABLE_PREFS(NULL,'SALES','ESTIMATE_PERCENT','10'); DBMS_STATS.SET_TABLE_PREFS(NULL,'SALES','METHOD_OPT', 'FOR COLUMNS SALE_DATE SIZE 254 PRODUCT_NUMBER SIZE 1 '|| 'CUSTOMER_NUMBER SIZE 1 AMOUNT SIZE 1'); end; / -- 2 - regather table stats with new preferences execute DBMS_STATS.GATHER_TABLE_STATS (NULL,'SALES');

  16. Cardinality Hint SQL> select /*+cardinality(sales 1) */ 2 sale_date, product_name, customer_name, amount 3 from sales, products, customers 4 where 5 sales.product_number=products.product_number and 6 sales.customer_number=customers.customer_number and 7 sale_date between 8 to_date('01/01/2012','MM/DD/YYYY') and 9 to_date('01/31/2012','MM/DD/YYYY') and 10 product_type = 'Cheese' and 11 customer_state = 'FL'; SALE_DATE PRODUCT_NAME CUSTOMER_NAME AMOUNT --------- ------------ ----------------- ---------- 04-JAN-12 Feta Sunshine State Co 300 02-JAN-12 Chedder Sunshine State Co 100 05-JAN-12 Feta Green Valley Inc 400 03-JAN-12 Chedder Green Valley Inc 200

  17. Plan with Cardinality hint Execution Plan ---------------------------------------------------------- 0 SELECT STATEMENT Optimizer=ALL_ROWS 1 0 HASH JOIN 2 1 HASH JOIN 3 2 TABLE ACCESS (FULL) OF 'SALES' (TABLE) 4 2 TABLE ACCESS (FULL) OF 'PRODUCTS' (TABLE 5 1 TABLE ACCESS (FULL) OF 'CUSTOMERS' (TABLE)

  18. Leading Hint SQL> select /*+leading(sales) */ 2 sale_date, product_name, customer_name, amount 3 from sales, products, customers 4 where 5 sales.product_number=products.product_number and 6 sales.customer_number=customers.customer_number and 7 sale_date between 8 to_date('01/01/2012','MM/DD/YYYY') and 9 to_date('01/31/2012','MM/DD/YYYY') and 10 product_type = 'Cheese' and 11 customer_state = 'FL'; SALE_DATE PRODUCT_NAME CUSTOMER_NAME AMOUNT --------- ------------ ----------------- ---------- 04-JAN-12 Feta Sunshine State Co 300 02-JAN-12 Chedder Sunshine State Co 100 05-JAN-12 Feta Green Valley Inc 400 03-JAN-12 Chedder Green Valley Inc 200

  19. Break Query Into Pieces SQL> create global temporary table sales_product_results 2 ( 3 sale_date date, 4 customer_number number, 5 amount number, 6 product_type varchar2(12), 7 product_name varchar2(12) 8 ) on commit preserve rows; Table created.

  20. Break Query Into Pieces SQL> insert /*+append */ 2 into sales_product_results 3 select 4 sale_date, 5 customer_number, 6 amount, 7 product_type, 8 product_name 9 from sales, products 10 where 11 sales.product_number=products.product_number and 12 sale_date between 13 to_date('01/01/2012','MM/DD/YYYY') and 14 to_date('01/31/2012','MM/DD/YYYY') and 15 product_type = 'Cheese'; 4 rows created.

  21. Break Query Into Pieces SQL> select 2 sale_date, product_name, customer_name, amount 3 from sales_product_results spr, customers c 4 where 5 spr.customer_number=c.customer_number and 6 c.customer_state = 'FL'; SALE_DATE PRODUCT_NAME CUSTOMER_NAME AMOUNT --------- ------------ ----------------- ---------- 02-JAN-12 Chedder Sunshine State Co 100 03-JAN-12 Chedder Green Valley Inc 200 04-JAN-12 Feta Sunshine State Co 300 05-JAN-12 Feta Green Valley Inc 400

  22. Join Methods Join Method = way that data from two sources is joined Nested Loops Small number of rows in first table Unique index on second large table Hash Join Smaller or equal number of rows in first table No index required

  23. Join Method – Nested Loops Execution Plan ------------------------------------------------------------------ 0 SELECT STATEMENT Optimizer=ALL_ROWS 1 0 TABLE ACCESS (BY INDEX ROWID) OF 'CUSTOMERS' (TABLE) 2 1 NESTED LOOPS 3 2 NESTED LOOPS 4 3 TABLE ACCESS (FULL) OF 'SALES' (TABLE) 5 3 TABLE ACCESS (BY INDEX ROWID) OF 'PRODUCTS' 6 5 INDEX (RANGE SCAN) OF 'PRODUCTS_INDEX' (INDEX) 7 2 INDEX (RANGE SCAN) OF 'CUSTOMERS_INDEX' (INDEX)

  24. Join Method – Hash Join Execution Plan ---------------------------------------------------------- 0 SELECT STATEMENT Optimizer=ALL_ROWS 1 0 HASH JOIN 2 1 HASH JOIN 3 2 TABLE ACCESS (FULL) OF 'SALES' (TABLE) 4 2 TABLE ACCESS (FULL) OF 'PRODUCTS' 5 1 TABLE ACCESS (FULL) OF 'CUSTOMERS' (TABLE)

  25. Modifying the Join Method Hints use_hash use_nl Add Index Hash_area_size parameter

  26. Join Methods Hints /*+ use_hash(products) use_nl(customers) */

  27. Join Methods Indexes create index products_index on products(product_number); create index customers_index on customers(customer_number);

  28. Join Methods Hash_Area_Size NAME TYPE VALUE ------------------------------------ ----------- --------- hash_area_size integer 100000000 sort_area_size integer 100000000 workarea_size_policy string MANUAL

  29. Access Methods Access method = way that data is retrieved from table Index scan – small number of rows accessed Full scan – larger number of rows accessed

  30. Modifying the Access Method Set Initialization Parameter optimizer_index_caching optimizer_index_cost_adj db_file_multiblock_read_count Set Parallel Degree > 1 Hints Full Index

  31. Set Initialization Parameter alter system set optimizer_index_cost_adj=1000 scope=both sid='*';

  32. Set Parallel Degree alter table sales parallel 8;

  33. Full Scan and Index Hints /*+ full(sales) index(customers) index(products) */

  34. Conclusion Use count queries to determine selective parts of where clause Modify the join order, join methods, and access methods using Optimizer statistics Hints Initialization parameters Breaking the query into pieces Parallel degree Indexes Compare elapsed time of query with new plan to original

  35. Check For Improved Elapsed Time SQL> set timing on SQL> SQL> select … … removed for clarity … SALE_DATE PRODUCT_NAME CUSTOMER_NAME AMOUNT --------- ------------ ----------------- ---------- 02-JAN-12 Chedder Sunshine State Co 100 03-JAN-12 Chedder Green Valley Inc 200 04-JAN-12 Feta Sunshine State Co 300 05-JAN-12 Feta Green Valley Inc 400 Elapsed: 00:00:00.00

  36. Further Reading Oracle Database Concepts Chapter 7 SQL Oracle Database Performance Tuning Guide Chapter 11 The Query Optimizer Chapter 19 Using Optimizer Hints Oracle Database Reference Chapter 1 Initialization Parameters Oracle Database PL/SQL Packages and Types Reference Chapter 141 DBMS_STATS Cost-Based Oracle Fundamentals - Jonathan Lewis http://www.bobbydurrettdba.com/resources/

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