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A quick and easy way to check if statistics are accurate is to compare the NUM_ROWS column in USER_TABLES with the actual row count of a table. The following script will prompt you for a table name: select a.num_rows/b.actual_rows from user_tables a ,(select count(*) actual_rows from &&table_name) b where a.table_name=upper('&&table_name'); The next script uses SQL to generate the prior SQL for all tables for a user. The script uses SQL*Plus formatting commands to turn off headings and page breaks: set head off pages 0 lines 132 trimspool on spo show_stale.sql select 'select ' || '''' || table_name || ': ' || '''' || '||' || chr(10) || ' round(decode(b.actual_rows,0,0,a.num_rows/b.actual_rows),2) ' || chr(10) || 'from user_tables a ' || ',(select count(*) actual_rows from ' || table_name || ') b' || chr(10) || 'where a.table_name=(' || '''' || table_name || '''' || ');' from user_tables; spo off; This script produces a file named show_stale.sql that you can execute to display the staleness of table statistics.

Figure 2-23. Managing saved filters This screen shows you all of the custom filters that you ve created. For each filter, you can perform these actions: Share the filter with the entire team by checking the Shared checkbox. The filter will now appear on everyone s list of filters. This checkbox is only available to FogBugz administrators. Edit the conditions for the filter by clicking the icon in the Edit column. Delete the filter by clicking the icon in the Delete column. There s no confirmation for this action, so be sure you really want to delete the filter before you click!

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make is an extremely useful part of the build process. By creating a file called Makefile, you describe to make exactly how to build your application. make can then intelligently determine how to build your application without necessarily rebuilding the entire application. If you build Gaim and then change a single source file, only that source file needs to be recompiled. The other object files are up-to-date. All that needs to be done is to compile that one source file and link the resulting object file with the other, older object files. By creating a proper makefile, you can specify this behavior by specifying separate rules for each sub-task in building your application.

The scripts in the solution section use the NUM_ROWS column that is populated when statistics are gathered. If the percentage of NUM_ROWS to actual rows is more than 10% different from the actual rows, the statistics are probably stale. There are a few other techniques for determining if statistics have been recently generated. For example, you can check the LAST_ANALYZED column of the USER_TABLES and USER_INDEXES views to determine the last time your tables and indexes were analyzed. This following query displays the last time tables were analyzed for the current schema: select table_name ,last_analyzed ,monitoring from user_tables order by last_analyzed; This next query reports the last time indexes were analyzed for the current schema: select index_name ,last_analyzed from user_indexes order by last_analyzed; Viewing the last time statistics were generated for tables and indexes in a vacuum can be somewhat misleading. The LAST_ANALYZED column does tell you if statistics have ever been generated, but that s about it. The LAST_ANALYZED time doesn t provide enough information to determine whether the statistics might need to be re-generated. For more detailed information about table statistics use the USER_TAB_STATISTICS view. This view contains information about the many optimizer statistics that are generated for tables. For example, this view has a STALE_STATS column that is an indicator of whether or not Oracle thinks the statistics are stale. The following query displays statistics such as SAMPLE_SIZE and STALE_STATS: select table_name ,partition_name ,last_analyzed ,num_rows ,sample_size ,stale_stats from user_tab_statistics order by last_analyzed; Similar to the table statistics, you can also view index statistics by querying the USER_IND_STATISTICS view: select index_name ,partition_name

,last_analyzed ,num_rows ,sample_size ,stale_stats from user_ind_statistics order by last_analyzed; If you want to determine how much INSERT, UPDATE, DELETE, and TRUNCATE activity has occurred since the last time statistics were generated, query the USER_TAB_MODIFICATIONS view. For example, you may have a situation in which a table is truncated before a large load of new records are inserted. You can run a query like the following to verify that that type of activity has occurred since the last time statistics were generated: select table_name ,partition_name ,inserts ,updates ,deletes ,truncated ,timestamp from user_tab_modifications order by table_name; If you detect that there have been significant changes to the data in a table, you should consider generating the statistics manually (see recipe 19-14 for details).

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