Pivot Tables Motivation (1)

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Shonda Newton
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1 Pivot Tables The Pivot relational operator (available in some SQL platforms/servers) allows us to write cross-tabulation queries from tuples in tabular layout. It takes data in separate rows, aggregates it and convert it into columns. 1

2 Pivot Tables Motivation (1) Considering table customers as: Cust_id Cust_name State_code Times_purchased 1 John CT 1 2 Mary NY 10 3 Alfredo NJ 2 4 Ana NY If we want to know how many customers bought someting once, twice, thrice and so on, from each state, a regular SQL to satisfy that query would be, select state_code, times_purchased, count(*) cnt from customers group by state_code, times_purchased; 2

3 Pivot Tables Motivation (2) Whose result would be: State_code Times_purchased cnt CT 0 90 CT CT NY This is the information we need but it is a little hard to read. A crosstab where we could organize the data vertically and states horizontally would be preferable: Times_purchased CT NY NJ

4 Pivot Tables: another example The following tuples: order_id customer_ref product_id SMITH SMITH ANDERSON ANDERSON JONES JONES SMITH SMITH SMITH 20 Can be shown as: customer_ref ANDERSON JONES SMITH

5 PIVOT clause syntax (1) SELECT * FROM ( SELECT column1,, columnj FROM tables WHERE conditions ) PIVOT ( aggregate_function(columnj) FOR columnj IN ( expr1, expr2,... expr_n) subquery ) ORDER BY expression [ ASC DESC ]; 5

6 PIVOT clause syntax (2) Where: aggregate_function can be a function such as SUM, COUNT, MIN, MAX or AVG IN ( expr1, expr2,... expr_n ) is a list of values for columnj to pivot into headings in the cross-tabulation query. Each distinct value will be shown as a separate column subquery can be used instead of a list of values. 6

7 PIVOT clause Application (1) select * from ( select times_purchased times, state_code from customers t ) pivot ( count(state_code) for state_code in ('NY','CT','NJ','FL','MO') ) order by times_purchased times NY CT NJ FL MO

8 Searching with PIVOT clause (1) EMP table EMPNO ENAME JOB MGR HIREDATE SAL COMM DEPTNO 7839 KING PRESIDENT 17-NOV BLAKE MANAGER MAY CLARK MANAGER JUN JONES MANAGER APR Question: For each job, display the salary totals in a separate column for each department. 8

9 Searching with PIVOT clause (2) WITH pivot_data AS (SELECT deptno, job, sal from EMP) select * from pivot_data PIVOT ( SUM(sal) for deptno in (10, 20, 30, 40) ); JOB CLERK SALESMAN 6160 PRESIDENT 5500 MANAGERT ANALYST 6600 The list of values in deptno was hard-coded in this example (10, 20, 30, 40) 9

10 Searching with PIVOT clause (2) Alternatively, an inline-view may be used to obtain the same result: select * from (SELECT deptno, job, sal from EMP) PIVOT ( SUM(sal) for deptno in (10, 20, 30, 40)); JOB CLERK SALESMAN 6160 PRESIDENT 5500 MANAGER ANALYST

11 Searching with PIVOT clause (3) Groupings will be affected if pivot queries are performed on a larger set of columns. Ex: SELECT * from EMP PIVOT ( SUM(sal) for deptno in (10, 20, 30, 40)); Here, deptno is still the pivot column but the large group of columns Including a superkey of EMP cause the effective useless of the pivot (results in the next slide). 11

12 Searching with PIVOT clause (4) EMPNO ENAME JOB MGR HIREDATE COMM MARTIN SALESMAN /09/ BLAKE MANAGER /05/ MILLER CLERK /01/ WARD SALESMAN /02/ JONES MANAGER /04/ TURNER SALESMAN /09/ JAMES CLERK /12/ KING PRESIDENT 19/04/ ADAMS CLERK /05/ FORD ANALYST /12/

13 Searching with PIVOT clause (5) Question: For ANALYST, CLERK and SALESMAN, display the salary totals in a separate column for each department. WITH pivot_data AS (SELECT deptno, job, sal from EMP) select * from pivot_data PIVOT ( SUM(sal) for deptno in (10, 20, 30, 40)) where job in ( ANALYST, CLERK, SALESMAN ); JOB CLERK SALESMAN 6160 ANALYST

14 Searching with PIVOT clause (6) Aliases can be used: WITH pivot_data AS (SELECT deptno, job, sal from EMP) select * from pivot_data PIVOT ( SUM(sal) as salaries for deptno in (10 as Dep10, 20 as Dep20, 30 as Dep30, 40 AS Dep40)) where job in ( ANALYST, CLERK, SALESMAN ); JOB Dep10_salaries Dep20_salaries Dep30_salaries Dep40_salaries CLERK SALESMAN 6160 ANALYST

15 Searching with PIVOT clause (7) Pivoting multiple columns: WITH pivot_data AS (SELECT deptno, job, sal from EMP) select * from pivot_data PIVOT ( SUM(sal) as sum, count(sal) as cnt for deptno in (10 as D10, 20 as D20, 30 as D30)); JOB D10_sum D10_cnt... D30_sum D30_cnt CLERK SALESMAN PRESIDENT MANAGER ANALYST

16 Or: Searching with PIVOT clause (8) WITH pivot_data AS (SELECT deptno, job, sal from EMP) select * from pivot_data PIVOT ( SUM(sal) as sum, count(sal) as cnt for (deptno, job) in ((30, 'SALESMAN') as d30_sls, (30, 'MANAGER') as d30_mgr, (30, 'CLERK') AS d30_clk)); D30_SLS_SUM D30_SLS_CNT D30_MGR_SUM D30_MGR_CNT

17 PIVOTing an Unknown Domain of Values (1) By default, the pivot syntax does not support a dynamic list of values in the pivot_in_clause. A subquery instead of a hardcode list of values used in the pivot_in_clause will generate an error: SELECT * FROM emp PIVOT (SUM(sal) AS salaries FOR deptno IN (SELECT deptno FROM dept)); 17

18 PIVOTing an Unknown Domain of Values (2) A possible workaround to solve this problem: (with Oracle) select * from (SELECT deptno, job, sal from EMP) PIVOT XML ( SUM(sal) for deptno in (any)); JOB DEPTNO_XML ANALYST <PivotSet><item><column name = "DEPTNO">20</column><column name = "SUM(SAL) ">6600</column></item></PivotSet> MANAGER It implies extra work to read the information from the XML format! 18

19 PIVOTing an Unknown Domain of Values (3) Another workaround to solve the problem (with Oracle SQLplus): column namelist new_value nlist noprint; /* first obtain a string with the list of distinct values of deptno select wm_concat('''' deptno '''') namelist from (select distinct deptno from emp) connect by nocycle deptno = prior deptno group by level; WITH pivot_data AS (SELECT deptno, job, sal from EMP) select * from pivot_data PIVOT ( SUM(sal) for deptno in (&nlist)); /* &nlist is a variable containing the string '10','20','30 (results in the next slide). */ 19

20 PIVOTing an Unknown Domain of Values (4) JOB CLERK SALESMAN 6160 PRESIDENT 5500 MANAGER ANALYST

21 UnPIVOT turning pivot tables into rows (1) SELECT... FROM... UNPIVOT [INCLUDE EXCLUDE NULLS] ( unpivot_clause unpivot_for_clause unpivot_in_clause ) WHERE... unpivot clause: specifies a name for a column to represent the unpivoted measure values. unpivot_for_clause: specifies the name for the column that will result from our unpivot query. unpivot_for_clause: this contains the list of pivoted columns (not values) to be unpivoted 21

22 UnPIVOT turning pivot tables into rows (2) CREATE VIEW pivoted_data as SELECT * FROM pivot_data PIVOT (SUM(sal) FOR deptno IN (10 AS d10_sal, 20 as d20_sal, 30 as d30_sal, 40 AS d40_sal)); select * from pivoted_data; JOB D10_sal D20_sal D30_sal D40_sal CLERK SALESMAN 6160 PRESIDENT 5500 MANAGERT ANALYST

23 UnPIVOT turning pivot tables into rows (3) SELECT * FROM pivoted_data UNPIVOT ( Deptsal FOR saldesc IN (d10_sal, d20_sal, d30_sal, d40_sal) ); JOB SALDESC DEPTSAL CLERK D10_SAL 1430 CLERK D20_SAL 2090 CLERK D30_SAL 1045 SALESMAN D30_SAL 6160 PRESIDENT D10_SAL 5500 MANAGER D10_SAL 2695 MANAGER D20_SAL MANAGER D30_SAL 3135 ANALYST D20_SAL

24 UnPIVOT other uses (1) Since columns in the unpivot_in_clause must all be of the same datatype, this would cause an error: SELECT empno, job, unpivot_col_name, unpivot_col_value FROM emp UNPIVOT (unpivot_col_value FOR unpivot_col_name IN (ename, deptno, hiredate)); 24

25 UnPIVOT other uses (2) A workaround (in oracle) consists on datatype conversion: WITH emp_data AS ( SELECT empno, job, ename, TO_CHAR(deptno) as deptno, TO_CHAR(hiredate) as hiredate FROM emp) SELECT empno, job, unpivot_col_name, unpivot_col_value FROM emp_data UNPIVOT (unpivot_col_value FOR unpivot_col_name IN (ename, deptno, hiredate)); (results in the next page) 25

26 UnPIVOT other uses (3) EMPNO JOB UNPIVOT_COL_NAME UNPIVOT_COL_VALUE 7369 CLERK ENAME SMITH 7369 CLERK DEPTNO CLERK HIREDATE 17/12/ SALESMAN ENAME ALLEN 7499 SALESMAN DEPTNO SALESMAN HIREDATE 20/02/

CS2 Current Technologies Lecture 2: SQL Programming Basics

T E H U N I V E R S I T Y O H F R G E D I N B U CS2 Current Technologies Lecture 2: SQL Programming Basics Dr Chris Walton (cdw@dcs.ed.ac.uk) 4 February 2002 The SQL Language 1 Structured Query Language