One of the difficulty when writing a SQL query (static SQL) is to have in the same Where Clause different conditions handling Null Values and Not Null Values for a predica.<\/p>\n
Let’s me explain you by an example :<\/p>\n
Users can entered different values for a user field from an OBI report:
\n – If no value entered then all rows must be returned.
\n – If 1 value entered then only row(s) related to the filter must be returned.
\n – If List Of Values entered then only row(s) related to the filter must be returned.<\/p>\n
The SQL we want to write must take into account all the conditions possible (the 3 listed above).<\/p>\n
Here is the first version of the SQL query written by the customer :<\/p>\n
\nselect * \nfrom my_table a\nWHERE a.pt_name LIKE decode(:PT_PARAM, NULL, '%', '')\nOR a.pt_name IN (:PT_PARAM);\n<\/pre>\n:PT_PARAM is the user variable.<\/p>\n
The problem with this query is that the both conditions :
\n – a.pt_name LIKE decode(:PT_PARAM, NULL, ‘%’, ”)
\n – a.pt_name IN (:PT_PARAM)
\nare always TRUE, so unnecessary work will be done by oracle optimizer.<\/p>\nWe can prove that by checking the execution plan :<\/p>\n
If :PT_PARAM is equal to ‘Value1’ :<\/p>\n
\nEXPLAIN PLAN FOR\nselect * \nfrom my_table a \nWHERE a.pt_name LIKE decode('Value1', NULL, '%', '')\nOR a.pt_name IN ('Value1');\n\nSELECT * FROM TABLE(DBMS_XPLAN.DISPLAY);\n\nPlan hash value: 1606647163\n \n--------------------------------------------------------------------------------------------------------\n| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |\n--------------------------------------------------------------------------------------------------------\n| 0 | SELECT STATEMENT | | 5 | 1140 | 3 (0)| 00:00:01 |\n| 1 | TABLE ACCESS BY INDEX ROWID BATCHED| MY_TABLE | 5 | 1140 | 3 (0)| 00:00:01 |\n| 2 | BITMAP CONVERSION TO ROWIDS | | | | | |\n| 3 | BITMAP OR | | | | | |\n|* 4 | BITMAP INDEX SINGLE VALUE | BIX_DMED_TERM_01 | | | | |\n| 5 | BITMAP MERGE | | | | | |\n|* 6 | BITMAP INDEX RANGE SCAN | BIX_DMED_TERM_01 | | | | |\n--------------------------------------------------------------------------------------------------------\n \nPredicate Information (identified by operation id):\n---------------------------------------------------\n \n 4 - access(\"A\".\"PT_NAME\"='Value1')\n 6 - access(\"A\".\"PT_NAME\" LIKE NULL)\n filter(\"A\".\"PT_NAME\" LIKE NULL AND \"A\".\"PT_NAME\" LIKE NULL)\n<\/pre>\nOracle Optimizer does 2 access :
\n – 1 access for NULL value
\n – 1 access for ‘Value1’ value<\/p>\nThe first access is not necessary since the user has selected a Not Null Value (‘Value1’). Indeed if the user select one Not Null value (‘Value1’), we don’t want oracle execute condition for NULL value.<\/p>\n
To avoid this couple of access, it’s necessary to re-write the SQL statement like that :<\/p>\n
\nselect * \nfrom my_table a\nwhere (:PT_PARAM is null AND a.pt_name like '%')\nOR (:PT_PARAM IS NOT NULL AND a.pt_name in (:PT_PARAM));\n<\/pre>\nWe just add a SQL clause indicating that if the first condition is TRUE, the second condition is FALSE and vice versa:
\nif (:PT_PARAM is null AND a.pt_name like ‘%’) is TRUE then (:PT_PARAM IS NOT NULL AND a.pt_name in (:PT_PARAM)) is FALSE
\nif (:PT_PARAM IS NOT NULL AND a.pt_name in (:PT_PARAM)) is TRUE then (:PT_PARAM is null AND a.pt_name like ‘%’) is FALSE<\/p>\nChecking the execution plan related to the new SQL statement :<\/p>\n
\nEXPLAIN PLAN FOR\nselect * \nfrom my_table a\nwhere ('Value1' is null AND a.pt_name like '%')\nOR ( 'Value1' IS NOT NULL AND a.pt_name in ('Value1'));\n\nPlan hash value: 2444798625\n \n--------------------------------------------------------------------------------------------------------\n| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |\n--------------------------------------------------------------------------------------------------------\n| 0 | SELECT STATEMENT | | 5 | 1140 | 2 (0)| 00:00:01 |\n| 1 | TABLE ACCESS BY INDEX ROWID BATCHED| MY_TABLE | 5 | 1140 | 2 (0)| 00:00:01 |\n| 2 | BITMAP CONVERSION TO ROWIDS | | | | | |\n|* 3 | BITMAP INDEX SINGLE VALUE | BIX_DMED_TERM_01 | | | | |\n--------------------------------------------------------------------------------------------------------\n \nPredicate Information (identified by operation id):\n---------------------------------------------------\n \n 3 - access(\"A\".\"PT_NAME\"='Value1')\n<\/pre>\nNow only one access is done, the one related to the value ‘Value1’ selected by the user.<\/p>\n
Conclusion:<\/h3>\n
Tuning a SQL query can be made within different way : modify the physical design for a table (indexes, partitioning), influence the optimizer (Hints) to force an execution plan, modify oracle optimizer database parameters.<\/p>\n
But very often, SQL tuning can be made “simply” by re-written the SQL query. Most of the time, performance problem is due to bad written SQL statement.<\/p>\n
The first advice before to write a SQL query is:
\n – always understand the business needs in order to avoid bad interpretations.
\n – avoid unnecessary step for oracle optimizer by checking oracle execution plan in details to control the path oracle choose to access the data.
\n – avoid writing complex SQL – SQL is a very simple language, don’t forget it.<\/p>\n","protected":false},"excerpt":{"rendered":"One of the difficulty when writing a SQL query (static SQL) is to have in the same Where Clause different conditions handling Null Values and Not Null Values for a predica. Let’s me explain you by an example : Users can entered different values for a user field from an OBI report: – If no […]<\/p>\n","protected":false},"author":27,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[368,59],"tags":[98],"type_dbi":[],"class_list":["post-12307","post","type-post","status-publish","format-standard","hentry","category-development-performance","category-oracle","tag-sql"],"acf":[],"yoast_head":"\n
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