The Underestimated Subquery Factoring Clause

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1 The Underestimated Subquery Factoring Clause Philipp Salvisberg Senior Consultant DOAG Konferenz Mannheim, 16. November 2006 Basel Baden Bern Lausanne Zürich Düsseldorf Frankfurt/M. Freiburg i. Br. Hamburg München Stuttgart Wien

2 Zu meiner Person Senior Consultant bei der Trivadis AG, Zürich Betriebsökonom HWV Schwerpunkt Oracle Application Development Application Performance Management Business Intelligence 18 Jahre Erfahrung mit Oracle The Underestimated Subquery Factoring Clause

3 Agenda Einführung Sales History Tuning Fall Komplexe Abfragen Daten sind immer im Spiel. Tipps & Tricks Zusammenfassung The Underestimated Subquery Factoring Clause

4 Subquery Factoring Klausel (With Klausel) Syntax (seit 9i Release 1 gemäss ANSI SQL99 Standard) WITH query_name AS (subquery) [, query_name AS (subquery) ] SELECT... Features Bezeichnung einer Subquery als query_name Mehrfache Verwendung einer query_name, sogar in anderen, nachfolgend definierten Subqueries CBO behandelt eine Subquery als Inline View oder Temporary Table Einschränkungen Jede query_name ist mindestens einmal zu verwenden Maximal eine Subquery Factoring Klausel per SQL Statement Keine Unterstützung der RECURSIVE Klausel (ANSI Pendant zu CONNECT BY START WITH) The Underestimated Subquery Factoring Clause

5 NF9i Beispiel WITH emp_sal AS ( SELECT e.deptno, d.dname, SUM(e.sal) AS sal FROM emp e INNER JOIN dept d ON e.deptno = d.deptno GROUP BY e.deptno, d.dname ), avg_sal AS ( SELECT AVG(sal) AS avgsal FROM emp_sal ) -- main SELECT * FROM emp_sal CROSS JOIN avg_sal WHERE emp_sal.sal < avg_sal.avgsal ORDER BY emp_sal.dname; Mehrfache Verwendung DEPTNO DNAME SAL AVGSAL ACCOUNTING SALES The Underestimated Subquery Factoring Clause

6 NF9i Beispiel Execution Plan Id Operation Name Rows Bytes Cost SELECT STATEMENT 10 1 TEMP TABLE TRANSFORMATION emp_sal 2 LOAD AS SELECT 3 HASH GROUP BY NESTED LOOPS TABLE ACCESS FULL EMP TABLE ACCESS BY INDEX ROWID DEPT * 7 INDEX UNIQUE SCAN PK_DEPT SORT ORDER BY NESTED LOOPS avg_sal VIEW SORT AGGREGATE VIEW TABLE ACCESS FULL SYS_TEMP_ * 14 VIEW TABLE ACCESS FULL SYS_TEMP_ Predicate Information (identified by operation id): access("e"."deptno"="d"."deptno") 14 - filter("emp_sal"."sal"<"avg_sal"."avgsal") The Underestimated Subquery Factoring Clause

7 Subquery als Inline View betrachten WITH emp_sal AS ( SELECT /*+inline */ e.deptno, d.dname, SUM(e.sal) AS sal FROM emp e INNER JOIN dept d ON e.deptno = d.deptno GROUP BY e.deptno, d.dname ), avg_sal AS ( SELECT AVG(sal) AS avgsal FROM emp_sal ) -- main SELECT * FROM emp_sal CROSS JOIN avg_sal WHERE emp_sal.sal < avg_sal.avgsal ORDER BY emp_sal.dname; DEPTNO DNAME SAL AVGSAL ACCOUNTING SALES The Underestimated Subquery Factoring Clause

8 Execution Plan mit Inline Hint Id Operation Name Rows Bytes Cost SELECT STATEMENT SORT ORDER BY NESTED LOOPS avg_sal VIEW SORT AGGREGATE VIEW emp_sal HASH GROUP BY NESTED LOOPS TABLE ACCESS FULL EMP TABLE ACCESS BY INDEX ROWID DEPT * 10 INDEX UNIQUE SCAN PK_DEPT 1 0 * 11 VIEW SORT GROUP BY emp_sal NESTED LOOPS TABLE ACCESS FULL EMP TABLE ACCESS BY INDEX ROWID DEPT * 16 INDEX UNIQUE SCAN PK_DEPT Predicate Information (identified by operation id): access("e"."deptno"="d"."deptno") 11 - filter("emp_sal"."sal"<"avg_sal"."avgsal") 16 - access("e"."deptno"="d"."deptno") The Underestimated Subquery Factoring Clause

9 NF9i Beispiel Refactored WITH emp_sal AS ( SELECT e.deptno, d.dname, SUM(e.sal) AS sal, AVG(SUM(e.sal)) over() AS avgsal FROM emp e INNER JOIN dept d ON e.deptno = d.deptno GROUP BY e.deptno, d.dname ) -- main SELECT * FROM emp_sal WHERE sal < avgsal ORDER BY dname; DEPTNO DNAME SAL AVGSAL ACCOUNTING SALES The Underestimated Subquery Factoring Clause

10 NF9i Beispiel Refactored Execution Plan Id Operation Name Rows Bytes Cost SELECT STATEMENT * 1 VIEW WINDOW BUFFER SORT GROUP BY NESTED LOOPS TABLE ACCESS FULL EMP TABLE ACCESS BY INDEX ROWID DEPT * 7 INDEX UNIQUE SCAN PK_DEPT Predicate Information (identified by operation id): filter("sal"<"avgsal") 7 - access("e"."deptno"="d"."deptno") The Underestimated Subquery Factoring Clause

11 Temp Table Transformation erzwingen WITH emp_sal AS ( SELECT /*+ materialize */ e.deptno, d.dname, SUM(e.sal) AS sal, AVG(SUM(e.sal)) over() AS avgsal FROM emp e INNER JOIN dept d ON e.deptno = d.deptno GROUP BY e.deptno, d.dname ) -- main SELECT * FROM emp_sal WHERE sal < avgsal ORDER BY dname; DEPTNO DNAME SAL AVGSAL ACCOUNTING SALES The Underestimated Subquery Factoring Clause

12 Execution Plan mit Materialize Hint Id Operation Name Rows Bytes Cost SELECT STATEMENT TEMP TABLE TRANSFORMATION 2 LOAD AS SELECT 3 WINDOW BUFFER SORT GROUP BY NESTED LOOPS TABLE ACCESS FULL EMP TABLE ACCESS BY INDEX ROWID DEPT * 8 INDEX UNIQUE SCAN PK_DEPT SORT ORDER BY * 10 VIEW TABLE ACCESS FULL SYS_TEMP_ Predicate Information (identified by operation id): access("e"."deptno"="d"."deptno") 10 - filter("sal"<"avgsal") The Underestimated Subquery Factoring Clause

13 Materialize Hint auch in Inline View anwendbar? SELECT * FROM (SELECT /*+ materialize */ e.deptno, d.dname, SUM(e.sal) AS sal, AVG(SUM(e.sal)) over() AS avg_sal FROM emp e INNER JOIN dept d ON e.deptno = d.deptno GROUP BY e.deptno, d.dname) WHERE sal < avg_sal ORDER BY dname; Id Operation Name Rows Bytes Cost Nein! 0 SELECT STATEMENT * 1 VIEW WINDOW BUFFER SORT GROUP BY NESTED LOOPS TABLE ACCESS FULL EMP TABLE ACCESS BY INDEX ROWID DEPT * 7 INDEX UNIQUE SCAN PK_DEPT The Underestimated Subquery Factoring Clause

14 Einführung: Fazit Die Subqueries der Subquery Factoring Klausel sind mächtiger als Inline Views Das Mass unserer Dinge ist die Höhe Ihrer Ansprüche. Der CBO erhält mehr Informationen über eine Query und hat darum bessere Optimierungsmöglichkeiten Nur Subqueries der Subquery Factoring Klausel unterstützen die undokumentierten Hints materialize inline The Underestimated Subquery Factoring Clause

15 Agenda Einführung Sales History Tuning Fall Komplexe Abfragen Daten sind immer im Spiel. Tipps & Tricks Zusammenfassung The Underestimated Subquery Factoring Clause

16 Sales History Datenmodell und Beispiel COUNTRIES * CUSTOMERS TIMES 0..* SALES PRODUCTS * * 1 72 The Underestimated Subquery Factoring Clause

17 Ausgangslage SELECT co.country_region, t.fiscal_year, COUNT(*) AS number_of_sales, COUNT(DISTINCT p.prod_id) AS distinct_products, COUNT(DISTINCT c.cust_id) AS distinct_customers FROM sales s INNER JOIN customers c ON c.cust_id = s.cust_id INNER JOIN countries co ON co.country_id = c.country_id INNER JOIN products p ON p.prod_id = s.prod_id INNER JOIN times t ON t.time_id = s.time_id WHERE co.country_region IN ('Oceania', 'Asia') AND p.prod_category_desc = 'Photo' GROUP BY co.country_region, t.fiscal_year ORDER BY co.country_region, t.fiscal_year COUNTRY_REGION FISCAL_YEAR NUMBER_OF_SALES DISTINCT_PRODUCTS DISTINCT_CUSTOMERS Asia Asia Oceania Oceania Oceania Oceania The Underestimated Subquery Factoring Clause

18 Execution Plan Id Operation Name Rows Bytes TempSpc Cost (%CPU) SELECT STATEMENT (9) 1 SORT GROUP BY (9) * 2 HASH JOIN 130K 9337K 4257 (8) 3 TABLE ACCESS FULL TIMES (4) * 4 HASH JOIN 130K 7802K 4224 (8) * 5 TABLE ACCESS FULL COUNTRIES (0) * 6 HASH JOIN 382K 17M 1200K 4208 (8) 7 TABLE ACCESS FULL CUSTOMERS K 363 (3) * 8 HASH JOIN 382K 13M 2708 (11) * 9 TABLE ACCESS FULL PRODUCTS (0) 10 PARTITION RANGE ALL 2756K 44M 2616 (8) 11 TABLE ACCESS FULL SALES 2756K 44M 2616 (8) Predicate Information (identified by operation id): access("t"."time_id"="s"."time_id") 4 - access("co"."country_id"="c"."country_id") 5 - filter("co"."country_region"='asia' OR "CO"."COUNTRY_REGION"='Oceania') 6 - access("c"."cust_id"="s"."cust_id") 8 - access("p"."prod_id"="s"."prod_id") 9 - filter("p"."prod_category_desc"='photo') The Underestimated Subquery Factoring Clause

19 Analyse 1/2 Sales Intermediate Result Set 1 Intermediate Result Set 2 Products Intermediate Result Set 3 Customers 15% Execution Plan als Left-Deep Tree Result Set 30% Countries Times Problem schlechte Antwortzeit Ursache Execution Plan als Left-Deep Tree ist ineffizient Products, Sales, Customers, Countries werden zu spät gefiltert Join von irrelevanten Customers zu grosses Zwischenresultat Grösserer Bedarf an Memory und allenfalls Temp. Space Join benötigt mehr CPU Oracle kennt keine tabellenübergreifende Statistiken 30% Countries 30% Customers 15% Products15% Sales The Underestimated Subquery Factoring Clause

20 Analyse 2/2 Sales Intermediate Result Set 1 Products Intermediate Result Set 3 15% Execution Plan als Bushy Tree Result Set Customers Times Intermediate Result Set 2 30% Countries Lösungsansatz Join zwischen Customers und Countries früher ausführen Execution Plan als Bushy Tree Varianten um Join Reihenfolge anzupassen Strukturen erstellen, löschen Statistiken erstellen, fälschen Oracle Parameter ändern Stored Outlines erstellen, ändern SQL Profiles anwenden Hints anwenden Refactoring der Query (umformulieren) The Underestimated Subquery Factoring Clause

21 Hinting V1 SELECT /*+leading(co c) */ co.country_region, t.fiscal_year, COUNT(*) AS number_of_sales, COUNT(DISTINCT p.prod_id) AS distinct_products, COUNT(DISTINCT c.cust_id) AS distinct_customers FROM sales s INNER JOIN customers c ON c.cust_id = s.cust_id INNER JOIN countries co ON co.country_id = c.country_id INNER JOIN products p ON p.prod_id = s.prod_id INNER JOIN times t ON t.time_id = s.time_id WHERE co.country_region IN ('Oceania', 'Asia') AND p.prod_category_desc = 'Photo' GROUP BY co.country_region, t.fiscal_year ORDER BY co.country_region, t.fiscal_year COUNTRY_REGION FISCAL_YEAR NUMBER_OF_SALES DISTINCT_PRODUCTS DISTINCT_CUSTOMERS Asia Asia Oceania Oceania Oceania Oceania The Underestimated Subquery Factoring Clause

22 Hinting V1 Execution Plan Id Operation Name Rows Bytes Cost (%CPU) SELECT STATEMENT (12) 1 SORT GROUP BY (12) * 2 HASH JOIN 130K 9337K 3141 (11) 3 TABLE ACCESS FULL TIMES (4) * 4 HASH JOIN 130K 7802K 3108 (11) * 5 TABLE ACCESS FULL PRODUCTS (0) * 6 HASH JOIN 943K 35M 3074 (10) * 7 HASH JOIN K 369 (4) * 8 TABLE ACCESS FULL COUNTRIES (0) 9 TABLE ACCESS FULL CUSTOMERS K 363 (3) 10 PARTITION RANGE ALL 2756K 105M 2616 (8) 11 TABLE ACCESS FULL SALES 2756K 105M 2616 (8) Predicate Information (identified by operation id): access("t"."time_id"="s"."time_id") 4 - access("p"."prod_id"="s"."prod_id") 5 - filter("p"."prod_category_desc"='photo') 6 - access("c"."cust_id"="s"."cust_id") 7 - access("co"."country_id"="c"."country_id") 8 - filter("co"."country_region"='asia' OR "CO"."COUNTRY_REGION"='Oceania')!"# $%$ Gleicher Execution Plan mit pga_aggregate_target >= 12M statt leading Hint (Alternative Ausgangslage) The Underestimated Subquery Factoring Clause

23 Hinting V2 SELECT /*+leading(co c p s) */ co.country_region, t.fiscal_year, COUNT(*) AS number_of_sales, COUNT(DISTINCT p.prod_id) AS distinct_products, COUNT(DISTINCT c.cust_id) AS distinct_customers FROM sales s INNER JOIN customers c ON c.cust_id = s.cust_id INNER JOIN countries co ON co.country_id = c.country_id INNER JOIN products p ON p.prod_id = s.prod_id INNER JOIN times t ON t.time_id = s.time_id WHERE co.country_region IN ('Oceania', 'Asia') AND p.prod_category_desc = 'Photo' GROUP BY co.country_region, t.fiscal_year ORDER BY co.country_region, t.fiscal_year COUNTRY_REGION FISCAL_YEAR NUMBER_OF_SALES DISTINCT_PRODUCTS DISTINCT_CUSTOMERS Asia Asia Asia Asia Oceania Oceania Oceania Oceania The Underestimated Subquery Factoring Clause

24 Hinting V2 Execution Plan Id Operation Name Rows Cost (%CPU) SELECT STATEMENT (1) 1 TEMP TABLE TRANSFORMATION 2 LOAD AS SELECT SYS_TEMP_0FD9D * 3 HASH JOIN (4) * 4 TABLE ACCESS FULL COUNTRIES 6 3 (0) 5 TABLE ACCESS FULL CUSTOMERS (3) 6 SORT GROUP BY (1) * 7 HASH JOIN (1) 8 TABLE ACCESS FULL SYS_TEMP_0FD9D (8) * 9 HASH JOIN (1) 10 TABLE ACCESS FULL TIMES (4) * 11 HASH JOIN (1) * 12 TABLE ACCESS FULL PRODUCTS 10 3 (0) 13 PARTITION RANGE ALL 130K (1) 14 TABLE ACCESS BY LOCAL INDEX ROWID SALES 130K (1) 15 BITMAP CONVERSION TO ROWIDS 16 BITMAP AND &$" '( ) 17 BITMAP MERGE 18 BITMAP KEY ITERATION 19 BUFFER SORT * 20 TABLE ACCESS FULL PRODUCTS 10 3 (0) * 21 BITMAP INDEX RANGE SCAN SALES_PROD_BIX 22 BITMAP MERGE 23 BITMAP KEY ITERATION 24 BUFFER SORT 25 TABLE ACCESS FULL SYS_TEMP_0FD9D 1 2 (0) * 26 BITMAP INDEX RANGE SCAN SALES_CUST_BIX The Underestimated Subquery Factoring Clause

25 Hinting V3 SELECT /*+leading(co c p s) no_star_transformation */ co.country_region, t.fiscal_year, COUNT(*) AS number_of_sales, COUNT(DISTINCT p.prod_id) AS distinct_products, COUNT(DISTINCT c.cust_id) AS distinct_customers FROM sales s INNER JOIN customers c ON c.cust_id = s.cust_id INNER JOIN countries co ON co.country_id = c.country_id INNER JOIN products p ON p.prod_id = s.prod_id INNER JOIN times t ON t.time_id = s.time_id WHERE co.country_region IN ('Oceania', 'Asia') AND p.prod_category_desc = 'Photo' GROUP BY co.country_region, t.fiscal_year * ORDER BY co.country_region, t.fiscal_year COUNTRY_REGION FISCAL_YEAR NUMBER_OF_SALES DISTINCT_PRODUCTS DISTINCT_CUSTOMERS Asia Asia Asia Oceania Oceania Oceania The Underestimated Subquery Factoring Clause

26 Hinting V3 Execution Plan Id Operation Name Rows Bytes TempSpc Cost (%CPU) SELECT STATEMENT (3) 1 SORT GROUP BY (3) * 2 HASH JOIN 130K 9337K (3) 3 TABLE ACCESS FULL TIMES (4) * 4 HASH JOIN 130K 7802K 10M (3) 5 MERGE JOIN CARTESIAN 189K 8158K (2) * 6 HASH JOIN K 369 (4) * 7 TABLE ACCESS FULL COUNTRIES (0) 8 TABLE ACCESS FULL CUSTOMERS K 363 (3) $ (1 9 BUFFER SORT (2) * 10 TABLE ACCESS FULL PRODUCTS (0) 11 PARTITION RANGE ALL 2756K 44M 2616 (8) 12 TABLE ACCESS FULL SALES 2756K 44M 2616 (8) Predicate Information (identified by operation id): access("t"."time_id"="s"."time_id") 4 - access("p"."prod_id"="s"."prod_id" AND "C"."CUST_ID"="S"."CUST_ID") 6 - access("co"."country_id"="c"."country_id") 7 - filter("co"."country_region"='asia' OR "CO"."COUNTRY_REGION"='Oceania') 10 - filter("p"."prod_category_desc"='photo') + #$,-. /%! 0$ The Underestimated Subquery Factoring Clause

27 Refactoring & Hinting WITH cc AS ( SELECT /*+no_merge cardinality(3000) */ c.cust_id, co.country_region FROM countries co INNER JOIN customers c ON c.country_id = co.country_id WHERE co.country_region IN ('Oceania', 'Asia') ) SELECT /*+index(s) */ cc.country_region, t.fiscal_year, COUNT(*) AS number_of_sales, COUNT(DISTINCT p.prod_id) AS distinct_products, COUNT(DISTINCT cc.cust_id) AS distinct_customers FROM sales s INNER JOIN cc ON cc.cust_id = s.cust_id INNER JOIN products p ON p.prod_id = s.prod_id INNER JOIN times t ON t.time_id = s.time_id WHERE p.prod_category_desc = 'Photo' GROUP BY cc.country_region, t.fiscal_year ORDER BY cc.country_region, t.fiscal_year * COUNTRY_REGION FISCAL_YEAR NUMBER_OF_SALES DISTINCT_PRODUCTS DISTINCT_CUSTOMERS Asia Oceania The Underestimated Subquery Factoring Clause

28 Refactoring & Hinting Execution Plan Id Operation Name Rows Cost (%CPU) SELECT STATEMENT (1) 1 SORT GROUP BY (1) * 2 HASH JOIN 162K (1) 3 TABLE ACCESS FULL TIMES (4) * 4 HASH JOIN 162K (1) 5 VIEW (4) * 6 HASH JOIN (4) * 7 TABLE ACCESS FULL COUNTRIES 6 3 (0) 8 TABLE ACCESS FULL CUSTOMERS (3) 9 TABLE ACCESS BY LOCAL INDEX ROWID SALES (1) 10 NESTED LOOPS 382K (1) * 11 TABLE ACCESS FULL PRODUCTS 10 3 (0) 12 PARTITION RANGE ALL 13 BITMAP CONVERSION TO ROWIDS * 14 BITMAP INDEX SINGLE VALUE SALES_PROD_BIX Predicate Information (identified by operation id): access("t"."time_id"="s"."time_id") 4 - access("cc"."cust_id"="s"."cust_id") 6 - access("c"."country_id"="co"."country_id") 7 - filter("co"."country_region"='asia' OR "CO"."COUNTRY_REGION"='Oceania') 11 - filter("p"."prod_category_desc"='photo') 14 - access("p"."prod_id"="s"."prod_id") +$%234$$" ( 56" (3 7 (5 8(+8 9: " ( - The Underestimated Subquery Factoring Clause

29 Übersicht der Resultate Fall Hints Laufzeit in Sek. Bemerkungen Ausgangslage - ~ 5.5 Countries Join erfolgt zu spät Hinting V1 leading(co c) ~ 4.1 Products Join erfolgt zu spät Hinting V2 leading(co c p s) ~ 1.0 Hint forciert Star Transformation Hinting V3 leading(co c p s) no_star_transformation ~ 3.8 Hint forciert Cartesian Join Refactoring & Hinting no_merge cardinality(3000) Index(s) ~ 0.8 Gewünschter Execution Plan The Underestimated Subquery Factoring Clause

30 Sales History Tuning Fall: Fazit Verwende die Subquery Factoring Clause in Kombination mit Hints um einen Execution Plan als Bushy Tree zu forcieren Das Mass unserer Dinge ist die Höhe Ihrer Ansprüche. Hints sind in einer Subquery Factory Clause gezielt und dosiert einsetzbar z.b. no_merge Hint um einen Join in einer Subquery Factoring Clause zu erzwingen, aber dem CBO die Wahl zu lassen wann und wie oft dieser Join auszuführen ist The Underestimated Subquery Factoring Clause

31 Agenda Einführung Sales History Tuning Fall Komplexe Abfragen Daten sind immer im Spiel. Tipps & Tricks Zusammenfassung The Underestimated Subquery Factoring Clause

32 McGyver Taschenlampe The Underestimated Subquery Factoring Clause

33 Die Anforderungen Alle Berechtigungen eines Benutzers anzeigen Direkte System Privilegien Direct Grant Identifikator System Privilegien aufgrund Privileg direkt an Benutzer vergeben rekursiv aufgelöster Rollen Blatt Identifikator Berechtigte Rollen/Privilegien Rollen ohne Sub-Rollen System Privilegien USERNAME PRIV GRANTED_PRIV DIRECT_GRANT IS_LEAF OLAPSYS SELECT ANY TABLE OLAP_DBA N Y OLAPSYS SELECT ANY TABLE SELECT ANY TABLE Y Y SCOTT SELECT ANY TABLE DBA N Y SYS SELECT ANY TABLE DBA N Y SYS SELECT ANY TABLE EXP_FULL_DATABASE N Y SYS SELECT ANY TABLE IMP_FULL_DATABASE N Y SYS SELECT ANY TABLE OLAP_DBA N Y SYS SELECT ANY TABLE SELECT ANY TABLE Y Y SYSMAN SELECT ANY TABLE DBA N Y SYSTEM SELECT ANY TABLE DBA N Y SYSTEM SELECT ANY TABLE SELECT ANY TABLE Y Y The Underestimated Subquery Factoring Clause

34 Query Teil 1 von 4 WITH -- roles-privileges as recursive structure priv AS ( -- roles without parent (=roots) SELECT ROLE AS priv, NULL AS parent_priv FROM dba_roles WHERE ROLE NOT IN (SELECT granted_role FROM role_role_privs) UNION ALL -- roles granted to roles SELECT granted_role AS priv, ROLE AS parent_priv FROM role_role_privs UNION ALL -- system privileges granted to roles SELECT PRIVILEGE AS priv, grantee AS parent_priv FROM dba_sys_privs WHERE grantee IN (SELECT ROLE FROM dba_roles) ) The Underestimated Subquery Factoring Clause

35 Query Teil 2 von 4 -- complete hierarchy as tree view, tree AS ( SELECT priv, parent_priv, sys_connect_by_path(priv, '/') '/' AS priv_path, CASE WHEN connect_by_isleaf = '0' THEN 'N' ELSE 'Y' END AS is_leaf -- 10g Style FROM priv CONNECT BY PRIOR priv = parent_priv ) -- complete hierarchy as graph view, graph AS ( SELECT priv, substr(priv_path, 2, instr(priv_path, '/', 2) - 2) AS parent_priv, is_leaf FROM tree ) The Underestimated Subquery Factoring Clause

36 Query Part 3 von 4 -- user privileges (user system privileges and user roles), upriv AS ( -- system privileges granted to users SELECT u.username, p.privilege AS priv FROM dba_sys_privs p INNER JOIN dba_users u ON u.username = p.grantee UNION ALL -- roles granted to users SELECT u.username, p.granted_role AS priv FROM dba_role_privs p INNER JOIN dba_users u ON u.username = p.grantee ) The Underestimated Subquery Factoring Clause

37 Query Teil 4 von 4 -- user privileges as graph view, ugraph AS ( SELECT DISTINCT upriv.username, graph.priv, CAST(graph.parent_priv AS VARCHAR2(30)) AS granted_priv, CASE WHEN graph.priv = graph.parent_priv THEN 'Y' ELSE 'N' END AS direct_grant, graph.is_leaf FROM upriv INNER JOIN graph ON upriv.priv = graph.parent_priv ) -- main SELECT username, priv, granted_priv, direct_grant, is_leaf FROM ugraph WHERE priv = 'SELECT ANY TABLE' ORDER BY username, PRIV, granted_priv; The Underestimated Subquery Factoring Clause

38 Inline Views versus Subquery Factoring Clause SELECT username, priv, granted_priv, direct_grant, is_leaf FROM (SELECT FROM (SELECT ) upriv, (SELECT FROM (SELECT FROM (SELECT ) priv ) tree ) graph ) ugraph WHERE priv = 'SELECT ANY TABLE' ORDER BY username, PRIV, granted_priv; WITH priv AS (SELECT ), tree AS (SELECT FROM priv ), graph AS (SELECT FROM tree ), upriv AS (SELECT ), ugraph AS (SELECT FROM upriv, graph ) SELECT username, priv, granted_priv, direct_grant, is_leaf FROM ugraph WHERE priv = 'SELECT ANY TABLE' ORDER BY username, PRIV, granted_priv; The Underestimated Subquery Factoring Clause

39 Komplexe Abfragen: Fazit Komplexe Queries als Folge von einfachen Subqueries schreiben Ähnliches Konzept wie Pipes Das Mass unserer Dinge ist die Höhe Ihrer Ansprüche. Die Subquery Factoring Clause ist immer durch mehrere, geschachtelte Inline Views ersetzbar, aber die Konsequenzen sind: Sich wiederholende Subqueries Schlechtere Lesbarkeit und Wartbarkeit The Underestimated Subquery Factoring Clause

40 Agenda Einführung Sales History Tuning Fall Komplexe Abfragen Daten sind immer im Spiel. Tipps & Tricks Zusammenfassung The Underestimated Subquery Factoring Clause

41 Tipps & Tricks (1) Falls das eingesetzte Werkzeug die Subquery Factoring Clause nicht unterstützt: SELECT * FROM ( WITH query_name AS (subquery) [, query_name AS (subquery) ] SELECT... ) Dieser Inline View Workaround hilft auch Fehlermeldungen der Formatierungs-Werkzeuge zu vermeiden Toad unterstützt WITH Klausel SQL Navigator unterstützt WITH Klausel SQL Developer unterstützt WITH Klausel PL/SQL Developer unterstützt WITH Klausel in PL/SQL benötigt Workaround für SQL Die Limitierung auf eine WITH Klausel per SQL Statement kann in einigen Fällen mit Hilfe des Inline View Workarounds umgangen werden. Jede WITH Klausel definiert aber ihren eigenen Namensraum! The Underestimated Subquery Factoring Clause

42 Tipps & Tricks (2) Bug verhindert allenfalls die Nutzung der Subquery Factoring Clause in Views, weil die in Subqueries verwendeten Objekte ebenfalls berechtigt werden müssen (gelöst in 10.2) Falls predicate pushing in geschachtelten Strukturen nicht funktioniert: Context Variablen Bind Variablen Dynamisches SQL Table Function Um das Debugging eines Query Subsets zu vereinfachen: Subqueries aufgrund ihrer Zusammengehörigkeit ordnen -- für Kommentare verwenden --+ für Hints verwenden /* */ Syntax reservieren, um ganze Query Blöcke auszukommentieren The Underestimated Subquery Factoring Clause

43 Zusammenfassung Die Subquery Factoring Clause ist eine gute Alternative für jede Inline View, um die Lesbarkeit und Wartbarkeit zu erhöhen Das Mass unserer Dinge ist die Höhe Ihrer Ansprüche. Die Subquery Factoring Clause unterstützt den CBO gezielt bei seiner Arbeit; typische Hints in Subqueries sind no_merge, merge materialize, inline oder dynamic_sampling cardinality opt_estimate table_stats, column_stats, index_stats Die Subquery Factoring Clause erhöht die Kontrolle der Query Verarbeitung The Underestimated Subquery Factoring Clause

44 Vielen Dank!? Basel Baden Bern Lausanne Zürich Düsseldorf Frankfurt/M. Freiburg i. Br. Hamburg München Stuttgart Wien