1. 8 Copyright © 2005, Oracle. All rights reserved. Gathering Statistics

2. 8-2 Copyright © 2005, Oracle. All rights reserved. Objectives After completing this lesson, you should be able to do the following: Use the DBMS_STATS package Identify table, index, and column statistics Identify predicate selectivity calculations Create histograms for columns with skewed data

3. 8-3 Copyright © 2005, Oracle. All rights reserved. What Are Statistics? Information used by cost-based optimization: To estimate the selectivity of predicates To estimate the cost of each execution plan To estimate the number of table rows To estimate CPU and I/O costs

4. 8-4 Copyright © 2005, Oracle. All rights reserved. Types of Statistics Object statistics –Table statistics –Column statistics –Index statistics System statistics –I/O performance and utilization –CPU performance and utilization

5. 8-5 Copyright © 2005, Oracle. All rights reserved. Gathering Statistics Estimation based on random data sampling Exact computation User-defined statistics collection methods

6. 8-6 Copyright © 2005, Oracle. All rights reserved. DBMS_STATS Package You can use the DBMS_STATS package to: Generate and manage statistics for cost-based optimization Gather, modify, view, export, import, and delete statistics Identify or name the statistics gathered Gather statistics on: –Indexes, tables, columns, and partitions –All schema objects in a schema or database Gather statistics either serially or in parallel Gather statistics needed for cost-based optimization

7. 8-7 Copyright © 2005, Oracle. All rights reserved. Methods for Gathering Statistics Procedure Description GATHER_INDEX_STATS Collects index statistics GATHER_TABLE_STATS Collects table, column, and index statistics GATHER_SCHEMA_STATS Collects statistics for all objects in a schema GATHER_SYSTEM_STATS Collects CPU and I/O statistics for the system GATHER_DATABASE_STATS Collects statistics for all objects in a database

8. 8-8 Copyright © 2005, Oracle. All rights reserved. Gathering Automated Statistics You can automatically gather statistics or create lists of tables that have stale or no statistics. To automatically gather statistics, run either of the following: – DBMS_STATS.GATHER_SCHEMA_STATS – DBMS_STATS.GATHER_DATABASE_STATS

9. 8-9 Copyright © 2005, Oracle. All rights reserved. Monitoring Automated Statistics Gathering Bring tables of a specific schema or database into monitoring mode: – DBMS_STATS.ALTER_SCHEMA_TAB_MONITORING – DBMS_STATS.ALTER_DATABASE_TAB_MONITORING Use the MONITORING keyword in the CREATE and ALTER TABLE statement syntax. Monitoring tracks the approximate number of DML since statistics were last gathered. This data is used to identify stale statistics. Automated statistics gathering is enabled using DBMS_STATS.GATHER_TABLE_STATS with the GATHER STALE option.

10. 8-10 Copyright © 2005, Oracle. All rights reserved. Full Notes Page

11. 8-11 Copyright © 2005, Oracle. All rights reserved. Generating Table Statistics dbms_stats.gather_table_stats ('sh' -- schema,'customers' -- table, null -- partition, 20 -- sample size(%), false -- block sample?,'for all columns' -- column spec, 4 -- degree of //,'default' -- granularity, true -- cascade to indexes );

12. 8-12 Copyright © 2005, Oracle. All rights reserved. Full Notes Page

13. 8-13 Copyright © 2005, Oracle. All rights reserved. BEGIN dbms_stats.create_stat_table ('SH', 'STATS'); dbms_stats.gather_table_stats ('SH', 'CUSTOMERS',stattab => 'STATS'); END; Gathering Statistics: Example BEGIN dbms_stats.delete_table_stats ('SH', 'CUSTOMERS'); END;

14. 8-14 Copyright © 2005, Oracle. All rights reserved. Generating System Statistics Applications can gather statistics during the day. Statistic gathering ends after 720 minutes and is stored in the MYSTATS table: BEGIN dbms_stats.gather_system_stats( gathering_mode => 'interval', interval => 720, stattab => 'mystats', statid => 'oltp'); END; /

15. 8-15 Copyright © 2005, Oracle. All rights reserved. Full Notes Page

16. 8-16 Copyright © 2005, Oracle. All rights reserved. Index Statistics Index statistics can be collected with the following commands: DBMS_STATS CREATE INDEX ALTER INDEX…REBUILD

17. 8-17 Copyright © 2005, Oracle. All rights reserved. Verifying Table Statistics SQL> SELECT table_name, num_rows, blocks, 2 avg_row_len, 3 to_char(last_analyzed, 'mm/dd/yyyy 4 hh24:mi:ss') analyzed 5 FROM user_tables 6 WHERE table_name ='EMPLOYEES';

18. 8-18 Copyright © 2005, Oracle. All rights reserved. Verifying Index Statistics SQL> SELECT index_name "name", num_rows, 2 distinct_keys "distinct", 3 leaf_blocks, clustering_factor 4 "cf", blevel "level", 5 avg_leaf_blocks_per_key "avg_leaf" 6 FROM user_indexes 7 WHERE table_owner = 'SH' 8 ORDER BY index_name;

19. 8-19 Copyright © 2005, Oracle. All rights reserved. Full Notes Page

20. 8-20 Copyright © 2005, Oracle. All rights reserved. Verifying Column Statistics SQL> SELECT column_name, num_distinct, 2 num_nulls, num_buckets, density 3 FROM user_tab_col_statistics 4 WHERE table_name ='SALES' 5 ORDER BY column_name;

21. 8-21 Copyright © 2005, Oracle. All rights reserved. Full Notes Page

22. 8-22 Copyright © 2005, Oracle. All rights reserved. Maintaining Statistics DECLARE num_rows number; num_blocks number; avg_row_len number; BEGIN dbms_stats.get_table_stats('oe','orders',null, 'savestats','test1', num_rows,num_blocks,avg_row_len); -- print the values dbms_output.put_line('num_rows='||num_rows||',num_blocks='||num_blocks|| ',avg_row_len='||avg_row_len); END; /

23. 8-23 Copyright © 2005, Oracle. All rights reserved. Dynamic Sampling Dynamic sampling should be used when: A better plan could be found The cost of collecting the statistics is minimal compared to the execution time The query is executed many times

24. 8-24 Copyright © 2005, Oracle. All rights reserved. Enabling Dynamic Sampling Dynamic sampling is not performed when OPTIMIZER_DYNAMIC_SAMPLING = 0 Dynamic sampling is performed when: – OPTIMIZER_DYNAMIC_SAMPLING = 1 –The query accesses more than one table. –There are no table statistics and no index –A full table scan is selected by optimizer More aggressive dynamic sampling is performed when: –Value is set higher –Upper limit is 10 – OPTIMIZER_DYNAMIC_SAMPLING > 1

25. 8-25 Copyright © 2005, Oracle. All rights reserved. Predicate Selectivity Unique or primary key = constant (This is a single-row predicate.) Nonunique index = constant Bounded or unbounded range scan – high : upper bound (or max ) – low : lower bound (or min ) – max,min : column statistics selectivity = 1/distinct_keys selectivity = (high-low+1)/(max-min+1)

26. 8-26 Copyright © 2005, Oracle. All rights reserved. Bind Variables and Predicate Selectivity Equality condition: No difference Bounded or unbounded range scan: Assumes built-in default selectivity If high performance is an issue, consider using dynamic SQL instead of bind variables: – DBMS_SQL package – EXECUTE IMMEDIATE Dynamic SQL implies less shared SQL. Optimizer performs bind peeking.

27. 8-27 Copyright © 2005, Oracle. All rights reserved. Histograms A histogram does the following: Partitions the values in the column into bands Reorders column values in a band to fall within the same range Provides improved selectivity estimates in the presence of data skew Enables optimal execution plans with nonuniform data distributions

28. 8-28 Copyright © 2005, Oracle. All rights reserved. Full Notes Page

29. 8-29 Copyright © 2005, Oracle. All rights reserved. Histograms and Selectivity Popular and nonpopular values Range scan selectivity is determined by the number of buckets spanned. Equality search selectivity is determined by: –Number of buckets (popular values) – DENSITY (nonpopular values)

30. 8-30 Copyright © 2005, Oracle. All rights reserved. Creating Histograms Use DBMS_STATS to create histograms. Generate statistics for the PRODUCTS table and the PROD_LIST_PRICE column (maximum 50 buckets). SQL> execute dbms_stats.gather_table_stats ('sh','products', method_opt => 'for columns size 50 prod_list_price' );

31. 8-31 Copyright © 2005, Oracle. All rights reserved. Histogram Tips Do not use histograms unless they substantially improve performance. Histograms allocate additional storage. Create histograms on columns that are used frequently in WHERE clauses of queries. Create histograms on columns that have a highly skewed data distribution. Histograms, like all other optimizer statistics, are static. Recompute the histogram when the data distribution of a column changes frequently.

32. 8-32 Copyright © 2005, Oracle. All rights reserved. When to Use Histograms Histograms can affect performance and should be used with caution. Use histograms for a column when the data is highly skewed.

33. 8-33 Copyright © 2005, Oracle. All rights reserved. Choosing a Sample Size If the data is uniformly distributed, 5% of the rows suffice. Choose a higher sample size if the number of distinct values is more than 10% of the number of rows. Use AUTO_SAMPLE_SIZE.

34. 8-34 Copyright © 2005, Oracle. All rights reserved. Choosing the Number of Buckets Start with the default size of 75 buckets. Experiment with different sizes to obtain optimum results. Set the number of buckets to be greater than the number of frequently occurring distinct values. Set method_opt.

35. 8-35 Copyright © 2005, Oracle. All rights reserved. Viewing Histogram Statistics Histogram information: USER/ALL_HISTOGRAMS The number of buckets in each histogram: USER/ALL_TAB_COL_STATISTICS SQL> SELECT endpoint_number, endpoint_value 2 FROM user_tab_histograms 3 WHERE table_name = 'PRODUCTS' 4 AND column_name = 'PROD_LIST_PRICE';

36. 8-36 Copyright © 2005, Oracle. All rights reserved. Full Notes Page

37. 8-37 Copyright © 2005, Oracle. All rights reserved. Summary In this lesson, you should have learned how to: Use the DBMS_STATS package Copy statistics between databases Determine selectivity for predicates with and without bind variables Use histograms –Popular values –Nonpopular values –Table, column, index, and cluster statistics collected

38. 8-38 Copyright © 2005, Oracle. All rights reserved. Practice 8: Overview This practice covers the following topics: Generating table statistics Creating a histogram Calculating selectivity Querying data dictionary information Deleting table statistics

39. 8-39 Copyright © 2005, Oracle. All rights reserved. Full Notes Page

40. 8-40 Copyright © 2005, Oracle. All rights reserved.