{"id":2898,"date":"2023-01-30T07:00:00","date_gmt":"2023-01-30T04:00:00","guid":{"rendered":"https:\/\/www.dataplatform.gr\/?p=2898"},"modified":"2023-12-04T00:10:23","modified_gmt":"2023-12-03T21:10:23","slug":"pos-veltionoyme-ena-query-poy-eiche-trexei-s","status":"publish","type":"post","link":"https:\/\/www.dataplatform.gr\/en\/pos-veltionoyme-ena-query-poy-eiche-trexei-s\/","title":{"rendered":"How to improve a previously run query on an Oracle database (SQL Tuning Advisor with AWR Snapshots)"},"content":{"rendered":"<p>In <a href=\"https:\/\/www.dataplatform.gr\/en\/pos-tha-veltiosoyme-ena-query-poy-trechei-se-v\/\" target=\"_blank\" rel=\"noreferrer noopener\">previous article<\/a> we had analyzed how to improve a query in <strong>Oracle <\/strong>with its use <strong>SQL Tuning Advisor<\/strong>. But in order to run the SQL Tuning Advisor, the query should still be in the<strong> Shared Pool <\/strong><em>that is, in memory<\/em> (RAM). However, if the query was executed before, it will no longer exist in memory. In this article we will see how we can run the SQL Tuning Advisor again by drawing information from the <a href=\"https:\/\/docs.oracle.com\/database\/121\/RACAD\/GUID-C3CD2DCE-38BD-46BA-BC32-7A28CAC9A7FD.htm#RACAD951\" target=\"_blank\" rel=\"noreferrer noopener\">AWR Snapshots<\/a>.<\/p>\n\n\n\n<p>We should remember that the <strong>SQL Tuning Advisor<\/strong> during its execution it collects information from various sources (as we will see in the image below) and at the end makes suggestions to improve the performance of the query.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"572\" height=\"434\" src=\"https:\/\/www.dataplatform.gr\/wp-content\/uploads\/2021\/02\/ota-01.png\" alt=\"\" class=\"wp-image-2908\" srcset=\"https:\/\/www.dataplatform.gr\/wp-content\/uploads\/2021\/02\/ota-01.png 572w, https:\/\/www.dataplatform.gr\/wp-content\/uploads\/2021\/02\/ota-01-300x228.png 300w\" sizes=\"auto, (max-width: 572px) 100vw, 572px\" \/><figcaption class=\"wp-element-caption\">docs.oracle.com<br><\/figcaption><\/figure>\n\n\n\n<p>The recommendations he suggests we make might be:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>To get statistics on specific tables as they are stale<\/li>\n\n\n\n<li>Let&#039;s create new indexes<\/li>\n\n\n\n<li>Let&#039;s change the way the query is written<\/li>\n\n\n\n<li>Use a SQL profile to force a different plan for the query<\/li>\n<\/ul>\n\n\n\n<p><\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"338\" height=\"422\" src=\"https:\/\/www.dataplatform.gr\/wp-content\/uploads\/2021\/02\/ota-02.png\" alt=\"\" class=\"wp-image-2909\" srcset=\"https:\/\/www.dataplatform.gr\/wp-content\/uploads\/2021\/02\/ota-02.png 338w, https:\/\/www.dataplatform.gr\/wp-content\/uploads\/2021\/02\/ota-02-240x300.png 240w\" sizes=\"auto, (max-width: 338px) 100vw, 338px\" \/><figcaption class=\"wp-element-caption\">docs.oracle.com<\/figcaption><\/figure>\n\n\n\n<p>To use the SQL Tuning Advisor we must have&nbsp;<strong>Enterprise<\/strong>&nbsp;version of Oracle or have purchased it&nbsp;<a href=\"https:\/\/docs.oracle.com\/cd\/B28359_01\/license.111\/b28287\/options.htm#DBLIC169\" target=\"_blank\" rel=\"noreferrer noopener\">Tuning Pack<\/a><\/p>\n\n\n\n<h2 class=\"wp-block-heading\">The example<\/h2>\n\n\n\n<p>First we have to find it&nbsp;<strong>SQL_ID&nbsp;<\/strong>from the query we want to see. If we don&#039;t have it&nbsp;<strong>SQL_ID<\/strong>&nbsp;<a href=\"https:\/\/www.dataplatform.gr\/en\/pos-vriskoyme-grigora-ti-trechei-se-mia\/\" target=\"_blank\" rel=\"noreferrer noopener\">in this article<\/a>&nbsp;you can see how to find it easily through the dynamic view <strong>GV$AACTIVE_SESSION_HISTORY<\/strong>.<\/p>\n\n\n\n<p>After we found it <strong>SQL_ID <\/strong>with the following query we will see the various plans that may have changed over time.<\/p>\n\n\n\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"sql\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\" data-no-translation=\"\" data-no-auto-translation=\"\">SELECT SQL_ID, PLAN_HASH_VALUE, TIMESTAMP FROM DBA_HIST_SQL_PLAN WHERE SQL_ID='93uy7ndb6uf2z';\n <\/pre>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"415\" height=\"228\" src=\"https:\/\/www.dataplatform.gr\/wp-content\/uploads\/2021\/02\/hta-01.png\" alt=\"\" class=\"wp-image-2899\" srcset=\"https:\/\/www.dataplatform.gr\/wp-content\/uploads\/2021\/02\/hta-01.png 415w, https:\/\/www.dataplatform.gr\/wp-content\/uploads\/2021\/02\/hta-01-300x165.png 300w\" sizes=\"auto, (max-width: 415px) 100vw, 415px\" \/><figcaption class=\"wp-element-caption\">01<\/figcaption><\/figure>\n\n\n\n<p>What we care about now is keeping them <strong>snap_id <\/strong>from the snapshots we want to study the query.<\/p>\n\n\n\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"sql\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\" data-no-translation=\"\" data-no-auto-translation=\"\">select snap_id,sql_id,plan_hash_value from dba_hist_sqlstat \nwhere sql_id='93uy7ndb6uf2z' \n--and plan_hash_value='3448248699' \norder by snap_id desc;\n<\/pre>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"361\" height=\"82\" src=\"https:\/\/www.dataplatform.gr\/wp-content\/uploads\/2021\/02\/hta-02.png\" alt=\"\" class=\"wp-image-2900\" srcset=\"https:\/\/www.dataplatform.gr\/wp-content\/uploads\/2021\/02\/hta-02.png 361w, https:\/\/www.dataplatform.gr\/wp-content\/uploads\/2021\/02\/hta-02-300x68.png 300w\" sizes=\"auto, (max-width: 361px) 100vw, 361px\" \/><figcaption class=\"wp-element-caption\">02<\/figcaption><\/figure>\n\n\n\n<p>As a next step we should create the <em>tuning task<\/em> completing it <strong>begin_snap<\/strong>\/<strong>end_snap <\/strong>(time limits he had run), the <strong>sql_id <\/strong>and give the task a name to <strong>task_name<\/strong>.<\/p>\n\n\n\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"sql\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\" data-no-translation=\"\" data-no-auto-translation=\"\">DECLARE\n   l_sql_tune_task_id  VARCHAR2(100);\nBEGIN\n   l_sql_tune_task_id := DBMS_SQLTUNE.create_tuning_task (\n                           begin_snap  => 71200,\n                           end_snap    => 71201,\n                           sql_id      => '93uy7ndb6uf2z',\n                           scope       => DBMS_SQLTUNE.scope_comprehensive,\n                           time_limit  => 60,\n                           task_name   => '93uy7ndb6uf2z_AWR_tuning_task',\n                           description => 'Tuning task for statement 93uy7ndb6uf2z  in AWR');\n   DBMS_OUTPUT.put_line('l_sql_tune_task_id: ' || l_sql_tune_task_id);\nEND;\n\/<\/pre>\n\n\n\n<p>Then we run the tuning task we created before:<\/p>\n\n\n\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"sql\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\" data-no-translation=\"\" data-no-auto-translation=\"\"> \nexec dbms_sqltune.execute_tuning_task (TASK_NAME => '93uy7ndb6uf2z_AWR_tuning_task');<\/pre>\n\n\n\n<p>After it is completed, we see the results from the analysis with the following select query:<\/p>\n\n\n\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"sql\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\" data-no-translation=\"\" data-no-auto-translation=\"\"> \nSET LONG 10000;\nSET PAGESIZE 1000;\nSET LINESIZE 200;\nSELECT DBMS_SQLTUNE.report_tuning_task('93uy7ndb6uf2z_AWR_tuning_task') AS recommendations FROM dual;\nSET PAGESIZE 24;\n<\/pre>\n\n\n\n<p>In the results we will see in three different sections.<\/p>\n\n\n\n<p>The&nbsp;<strong>General Section&nbsp;<\/strong>which contains the&nbsp;<strong>SQL text<\/strong>.<\/p>\n\n\n\n<p>The&nbsp;<strong>Finding Sections&nbsp;<\/strong>which contains the sentences he found such as:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Statistics Finding<\/strong>: Creating statistics in one&nbsp;<em>stale&nbsp;<\/em>table that the query reads<\/li>\n\n\n\n<li><strong>Index Finding<\/strong>: Which suggests the creation&nbsp;<em>index&nbsp;<\/em>in the field that was in the where clause<\/li>\n\n\n\n<li><strong>SQL Profile Finding<\/strong>: Suggests to enable it&nbsp;<em>SQL Profile<\/em>&nbsp;that he created that makes use of a better plan<\/li>\n<\/ul>\n\n\n\n<p>End of&nbsp;<strong>Explain Plan Section&nbsp;<\/strong>it analyzes the 2 different plans, one that has run the query and the other that it recommends.<\/p>\n\n\n\n<pre class=\"wp-block-code\" data-no-translation=\"\" data-no-auto-translation=\"\"><code>        | OTHER_AFM                   |   12\nRECOMMENDATIONS\n--------------------------------------------------------------------------------\nGENERAL INFORMATION SECTION\n-------------------------------------------------------------------------------\nTuning Task Name   : 93uy7ndb6uf2z_AWR_tuning_task\nTuning Task Owner  : SYS\nWorkload Type      : Single SQL Statement\nScope              : COMPREHENSIVE\nTime Limit(seconds): 60\nCompletion Status  : COMPLETED\nStarted at         : 01\/01\/2021 17:22:25\nCompleted at       : 01\/01\/2021 17:22:54\n\n-------------------------------------------------------------------------------\nSchema Name: USERS\nSQL ID     : 5t5mxfm0ph3n0\nSQL Text   : SELECT   TR.NAME,\n                                                                  TR.AGE,\n                                                                  TR.CITY,\n                                                                  TR.SIGN_DATE\n                                                            FROM    USERS.CUSTOMERS TR\n                                                            WHERE   \n                                                                  TR.SIGN_DATE  = TO_DATE('30\/12\/2020','DD\/MM\/YYYY')\n\n-------------------------------------------------------------------------------\nFINDINGS SECTION (3 findings)\n-------------------------------------------------------------------------------\n\n1- Statistics Finding\n---------------------\n  Optimizer statistics for table \"USERS\".\"CUSTOMERS\" are stale.\n\n  Recommendation\n  --------------\n  - Consider collecting optimizer statistics for this table and its indices.\n    execute dbms_stats.gather_table_stats(ownname =&gt; 'USERS', tabname =&gt;\n            'CUSTOMERS', estimate_percent =&gt;\n            DBMS_STATS.AUTO_SAMPLE_SIZE, method_opt =&gt; 'FOR ALL COLUMNS SIZE\n            AUTO', cascade =&gt; TRUE);\n\n  Rationale\n  ---------\n    The optimizer requires up-to-date statistics for the table and its indices\n    in order to select a good execution plan.\n\n\n2- Index Finding (see explain plans section below)\n--------------------------------------------------\n  The execution plan of this statement can be improved by creating one or more\n  indices.\n \n  Recommendation (estimated benefit: 99.99%)\n  ------------------------------------------\n  - Consider running the Access Advisor to improve the physical schema design\n    or creating the recommended index.\n    create index USERS.IDX$$_17C0B0001 on\n    USERS.CUSTOMERS(\"SIGN_DATE\");\n\t\n3- SQL Profile Finding (see explain plans section below)\n--------------------------------------------------------\n  A potentially better execution plan was found for this statement.\n\n  Recommendation (estimated benefit: 68.27%)\n  ------------------------------------------\n  - Consider accepting the recommended SQL profile.\n    execute dbms_sqltune.accept_sql_profile(task_name =&gt;\n            'SQL_TUNNING_TASK_5t5mxfm0ph3n0', task_owner =&gt; 'SYS', replace =&gt;\n            TRUE);\n\n-------------------------------------------------------------------------------\nEXPLAIN PLANS SECTION\n-------------------------------------------------------------------------------\n\n1- Original With Adjusted Cost\n------------------------------\nPlan hash value: 321555184\n\n--------------------------------------------------------------------------------\n| Id  | Operation            | Name             | Rows  | Bytes | Cost (%CPU)| T\n--------------------------------------------------------------------------------\n|   0 | SELECT STATEMENT     |                  |     6 |   330 |    19   (0)| 0\n|   1 |  PX COORDINATOR      |                  |       |       |            |\n|   2 |   PX SEND QC (RANDOM)| :TQ10000         |     6 |   330 |    19   (0)| 0\n|   3 |    PX BLOCK ITERATOR |                  |     6 |   330 |    19   (0)| 0\n|*  4 |     TABLE ACCESS FULL| CUSTOMERS |     6 |   330 |    19   (0)| 0\n--------------------------------------------------------------------------------\n\nPredicate Information (identified by operation id):\n---------------------------------------------------\n\n   4 - filter(\"TR\".\"SIGN_DATE\"=TO_DATE(' 2020-12-30 00:00:00', 'syyyy-mm-dd')\n\n2- Using SQL Profile\n--------------------\nPlan hash value: 3378393080\n\n--------------------------------------------------------------------------------\n| Id  | Operation                           | Name               | Rows  | Bytes\n--------------------------------------------------------------------------------\n|   0 | SELECT STATEMENT                    |                    |     6 |   330\n|   1 |  PARTITION RANGE SINGLE             |                    |     6 |   330\n|   2 |   INLIST ITERATOR                   |                    |       |\n|   3 |    TABLE ACCESS BY LOCAL INDEX ROWID| CUSTOMERS   |     6 |   330\n|*  4 |     INDEX RANGE SCAN                | INX_CUSTOMERS_1 |     1 |\n--------------------------------------------------------------------------------\n\nPredicate Information (identified by operation id):\n---------------------------------------------------\n\n   4 - access(\"TR\".\"SIGN_DATE\"=TO_DATE(' 2020-12-30 00:00:00', 'syyyy-mm-dd')\n        \n\n-------------------------------------------------------------------------------\n\nPL\/SQL procedure successfully completed<\/code><\/pre>\n\n\n\n<p>Finally, to delete the task or see what state it is in, execute the following:<\/p>\n\n\n\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"sql\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\" data-no-translation=\"\" data-no-auto-translation=\"\">--SELECT task_name, status FROM dba_advisor_log WHERE task_name = '93uy7ndb6uf2z_AWR_tuning_task';\nexecute dbms_sqltune.drop_tuning_task('93uy7ndb6uf2z_AWR_tuning_task');<\/pre>\n\n\n\n<h2 class=\"wp-block-heading\">Sources:<\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li><a href=\"https:\/\/docs.oracle.com\/database\/121\/TGSQL\/tgsql_sqltune.htm#TGSQL540\" target=\"_blank\" rel=\"noreferrer noopener\">Analyzing SQL with SQL Tuning Advisor<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/docs.oracle.com\/database\/121\/RACAD\/GUID-C3CD2DCE-38BD-46BA-BC32-7A28CAC9A7FD.htm#RACAD951GV$ACTIVE_SESSION_HISTORY\" target=\"_blank\" rel=\"noreferrer noopener\">Automatic Workload Repository<\/a><\/li>\n<\/ul>","protected":false},"excerpt":{"rendered":"<p>In a previous article we analyzed how to improve a query in Oracle using the SQL Tuning Advisor. However, in order to run the SQL Tuning Advisor, the query must still be in the Shared Pool, i.e. in memory (RAM). However, if the query was executed before, it will no longer exist in memory. In this [\u2026]<\/p>","protected":false},"author":1,"featured_media":704,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[11,16],"tags":[5,48,30,39],"class_list":["post-2898","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-databases","category-oracle-db","tag-oracle-database","tag-performance_tuning","tag-rdbms","tag-sql"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.4 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>\u03a0\u03ce\u03c2 \u03b2\u03b5\u03bb\u03c4\u03b9\u03ce\u03bd\u03bf\u03c5\u03bc\u03b5 \u03ad\u03bd\u03b1 query \u03c0\u03bf\u03c5 \u03b5\u03af\u03c7\u03b5 \u03c4\u03c1\u03ad\u03be\u03b5\u03b9 \u03c3\u03c4\u03bf \u03c0\u03b1\u03c1\u03b5\u03bb\u03b8\u03cc\u03bd \u03c3\u03b5 \u03b2\u03ac\u03c3\u03b7 \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03c9\u03bd \u03c4\u03b7\u03c2 Oracle (SQL Tuning Advisor with 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