SQL Server/T-SQL Tutorial/Analytical Functions/ROLLUP

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A summary query that includes a final summary row with "WITH ROLLUP"

3>
4>
5>
6> create table Billings (
7>     BankerID           INTEGER,
8>     BillingNumber      INTEGER,
9>     BillingDate        datetime,
10>     BillingTotal       INTEGER,
11>     TermsID            INTEGER,
12>     BillingDueDate     datetime ,
13>     PaymentTotal       INTEGER,
14>     CreditTotal        INTEGER
15>
16> );
17> GO
1>
2> INSERT INTO Billings VALUES (1, 1, "2005-01-22", 165, 1,"2005-04-22",123,321);
3> GO
(1 rows affected)
1> INSERT INTO Billings VALUES (2, 2, "2001-02-21", 165, 1,"2002-02-22",123,321);
2> GO
(1 rows affected)
1> INSERT INTO Billings VALUES (3, 3, "2003-05-02", 165, 1,"2005-04-12",123,321);
2> GO
(1 rows affected)
1> INSERT INTO Billings VALUES (4, 4, "1999-03-12", 165, 1,"2005-04-18",123,321);
2> GO
(1 rows affected)
1> INSERT INTO Billings VALUES (5, 5, "2000-04-23", 165, 1,"2005-04-17",123,321);
2> GO
(1 rows affected)
1> INSERT INTO Billings VALUES (6, 6, "2001-06-14", 165, 1,"2005-04-18",123,321);
2> GO
(1 rows affected)
1> INSERT INTO Billings VALUES (7, 7, "2002-07-15", 165, 1,"2005-04-19",123,321);
2> GO
(1 rows affected)
1> INSERT INTO Billings VALUES (8, 8, "2003-08-16", 165, 1,"2005-04-20",123,321);
2> GO
(1 rows affected)
1> INSERT INTO Billings VALUES (9, 9, "2004-09-17", 165, 1,"2005-04-21",123,321);
2> GO
(1 rows affected)
1> INSERT INTO Billings VALUES (0, 0, "2005-10-18", 165, 1,"2005-04-22",123,321);
2> GO
(1 rows affected)
1>
2>
3>
4> create table Bankers(
5>    BankerID             Integer,
6>    BankerName           VARCHAR(20),
7>    BankerContactLName   VARCHAR(20),
8>    BankerContactFName   VARCHAR(20),
9>    BankerCity           VARCHAR(20),
10>    BankerState          VARCHAR(20),
11>    BankerZipCode        VARCHAR(20),
12>    BankerPhone          VARCHAR(20)
13> )
14> GO
1>
2> insert into Bankers values (1, "ABC Inc.","Joe","Smith","Vancouver","BC","11111","111-111-1111");
3> GO
(1 rows affected)
1> insert into Bankers values (2, "DEF Inc.","Red","Rice", "New York", "DE","22222","222-222-2222");
2> GO
(1 rows affected)
1> insert into Bankers values (3, "HJI Inc.","Kit","Cat",  "Paris",    "CA","33333","333-333-3333");
2> GO
(1 rows affected)
1> insert into Bankers values (4, "QWE Inc.","Git","Black","Regina",   "ER","44444","444-444-4444");
2> GO
(1 rows affected)
1> insert into Bankers values (5, "RTY Inc.","Wil","Lee",  "Toronto",  "YU","55555","555-555-5555");
2> GO
(1 rows affected)
1> insert into Bankers values (6, "YUI Inc.","Ted","Larry","Calgary",  "TY","66666","666-666-6666");
2> GO
(1 rows affected)
1> insert into Bankers values (7, "OIP Inc.","Yam","Act",  "San Franc","FG","77777","777-777-7777");
2> GO
(1 rows affected)
1> insert into Bankers values (8, "SAD Inc.","Hit","Eat",  "Orland",   "PO","88888","888-888-8888");
2> GO
(1 rows affected)
1> insert into Bankers values (9, "DFG Inc.","Sad","Lee",  "Wisler",   "PL","99999","999-999-9999");
2> GO
(1 rows affected)
1> insert into Bankers values (0, "GHJ Inc.","Bit","Lee",  "Ticker",   "MN","00000","000-000-0000");
2> GO
(1 rows affected)
1>
2>
3> SELECT BankerID, COUNT(*) AS BillingCount,
4>     SUM(BillingTotal) AS BillingTotal
5> FROM Billings
6> GROUP BY BankerID WITH ROLLUP
7> GO
BankerID    BillingCount BillingTotal
----------- ------------ ------------
          0            1          165
          1            1          165
          2            1          165
          3            1          165
          4            1          165
          5            1          165
          6            1          165
          7            1          165
          8            1          165
          9            1          165
       NULL           10         1650
(11 rows affected)
1>
2>
3> drop table Billings;
4> drop table Bankers;
5> GO


A summary query that includes a summary row for each grouping level

3>
4>
5>
6>
7> create table Billings (
8>     BankerID           INTEGER,
9>     BillingNumber      INTEGER,
10>     BillingDate        datetime,
11>     BillingTotal       INTEGER,
12>     TermsID            INTEGER,
13>     BillingDueDate     datetime ,
14>     PaymentTotal       INTEGER,
15>     CreditTotal        INTEGER
16>
17> );
18> GO
1>
2> INSERT INTO Billings VALUES (1, 1, "2005-01-22", 165, 1,"2005-04-22",123,321);
3> GO
(1 rows affected)
1> INSERT INTO Billings VALUES (2, 2, "2001-02-21", 165, 1,"2002-02-22",123,321);
2> GO
(1 rows affected)
1> INSERT INTO Billings VALUES (3, 3, "2003-05-02", 165, 1,"2005-04-12",123,321);
2> GO
(1 rows affected)
1> INSERT INTO Billings VALUES (4, 4, "1999-03-12", 165, 1,"2005-04-18",123,321);
2> GO
(1 rows affected)
1> INSERT INTO Billings VALUES (5, 5, "2000-04-23", 165, 1,"2005-04-17",123,321);
2> GO
(1 rows affected)
1> INSERT INTO Billings VALUES (6, 6, "2001-06-14", 165, 1,"2005-04-18",123,321);
2> GO
(1 rows affected)
1> INSERT INTO Billings VALUES (7, 7, "2002-07-15", 165, 1,"2005-04-19",123,321);
2> GO
(1 rows affected)
1> INSERT INTO Billings VALUES (8, 8, "2003-08-16", 165, 1,"2005-04-20",123,321);
2> GO
(1 rows affected)
1> INSERT INTO Billings VALUES (9, 9, "2004-09-17", 165, 1,"2005-04-21",123,321);
2> GO
(1 rows affected)
1> INSERT INTO Billings VALUES (0, 0, "2005-10-18", 165, 1,"2005-04-22",123,321);
2> GO
(1 rows affected)
1>
2>
3>
4> create table Bankers(
5>    BankerID             Integer,
6>    BankerName           VARCHAR(20),
7>    BankerContactLName   VARCHAR(20),
8>    BankerContactFName   VARCHAR(20),
9>    BankerCity           VARCHAR(20),
10>    BankerState          VARCHAR(20),
11>    BankerZipCode        VARCHAR(20),
12>    BankerPhone          VARCHAR(20)
13> )
14> GO
1>
2> insert into Bankers values (1, "ABC Inc.","Joe","Smith","Vancouver","BC","11111","111-111-1111");
3> GO
(1 rows affected)
1> insert into Bankers values (2, "DEF Inc.","Red","Rice", "New York", "DE","22222","222-222-2222");
2> GO
(1 rows affected)
1> insert into Bankers values (3, "HJI Inc.","Kit","Cat",  "Paris",    "CA","33333","333-333-3333");
2> GO
(1 rows affected)
1> insert into Bankers values (4, "QWE Inc.","Git","Black","Regina",   "ER","44444","444-444-4444");
2> GO
(1 rows affected)
1> insert into Bankers values (5, "RTY Inc.","Wil","Lee",  "Toronto",  "YU","55555","555-555-5555");
2> GO
(1 rows affected)
1> insert into Bankers values (6, "YUI Inc.","Ted","Larry","Calgary",  "TY","66666","666-666-6666");
2> GO
(1 rows affected)
1> insert into Bankers values (7, "OIP Inc.","Yam","Act",  "San Franc","FG","77777","777-777-7777");
2> GO
(1 rows affected)
1> insert into Bankers values (8, "SAD Inc.","Hit","Eat",  "Orland",   "PO","88888","888-888-8888");
2> GO
(1 rows affected)
1> insert into Bankers values (9, "DFG Inc.","Sad","Lee",  "Wisler",   "PL","99999","999-999-9999");
2> GO
(1 rows affected)
1> insert into Bankers values (0, "GHJ Inc.","Bit","Lee",  "Ticker",   "MN","00000","000-000-0000");
2> GO
(1 rows affected)
1>
2>
3> SELECT BankerState, BankerCity, COUNT(*) AS QtyBankers
4> FROM Bankers
5> WHERE BankerState IN ("IA", "NJ")
6> GROUP BY BankerState, BankerCity WITH ROLLUP
7> ORDER BY BankerState DESC, BankerCity DESC
8> GO
BankerState          BankerCity           QtyBankers
-------------------- -------------------- -----------
(0 rows affected)
1>
2> drop table Billings;
3> drop table Bankers;
4> GO


Group hierarchy using the ROLLUP operator is determined by the order in which the grouping columns are specified.

5>
6>
7> create table department(
8>    dept_name     char(20)     not null,
9>    emp_cnt       int          not null,
10>    budget        float,
11>    date_month    datetime);
12> GO
1>
2> insert into department values("Research", 5, 50000, "01.01.2002");
3> insert into department values("Research", 10, 70000, "01.02.2002");
4> insert into department values("Research", 5, 65000, "01.07.2002");
5> insert into department values("Accounting", 5, 10000, "01.07.2002");
6> insert into department values("Accounting", 10, 40000, "01.02.2002");
7> insert into department values("Accounting", 6, 30000, "01.01.2002");
8> insert into department values("Accounting", 6, 40000, "01.02.2003");
9> insert into department values("Marketing", 6, 10000, "01.01.2003");
10> insert into department values("Marketing", 10, 40000, "01.02.2003");
11> insert into department values("Marketing", 3, 30000, "01.07.2003");
12> insert into department values("Marketing", 5, 40000, "01.01.2003");
13> GO
(1 rows affected)
(1 rows affected)
(1 rows affected)
(1 rows affected)
(1 rows affected)
(1 rows affected)
(1 rows affected)
(1 rows affected)
(1 rows affected)
(1 rows affected)
(1 rows affected)
1>
2> SELECT dept_name, emp_cnt, SUM(budget) sum_of_budgets
3> FROM department
4> GROUP BY dept_name, emp_cnt
5> WITH ROLLUP;
6> GO
dept_name            emp_cnt     sum_of_budgets
-------------------- ----------- ------------------------
Accounting                     5                    10000
Accounting                     6                    70000
Accounting                    10                    40000
Accounting                  NULL                   120000
Marketing                      3                    30000
Marketing                      5                    40000
Marketing                      6                    10000
Marketing                     10                    40000
Marketing                   NULL                   120000
Research                       5                   115000
Research                      10                    70000
Research                    NULL                   185000
NULL                        NULL                   425000
(13 rows affected)
1>
2> drop table department;
3> GO
1>
2>


ROLLUP Returns Super Aggregation Only in One Direction

3>
4> CREATE TABLE employee(
5>    id          INTEGER NOT NULL PRIMARY KEY,
6>    first_name  VARCHAR(10),
7>    last_name   VARCHAR(10),
8>    salary      DECIMAL(10,2),
9>    start_Date  DATETIME,
10>    region      VARCHAR(10),
11>    city        VARCHAR(20),
12>    managerid   INTEGER
13> );
14> GO
1> INSERT INTO employee VALUES (1, "Jason" ,  "Martin", 5890,"2005-03-22","North","Vancouver",3);
2> GO
(1 rows affected)
1> INSERT INTO employee VALUES (2, "Alison",  "Mathews",4789,"2003-07-21","South","Utown",4);
2> GO
(1 rows affected)
1> INSERT INTO employee VALUES (3, "James" ,  "Smith",  6678,"2001-12-01","North","Paris",5);
2> GO
(1 rows affected)
1> INSERT INTO employee VALUES (4, "Celia" ,  "Rice",   5567,"2006-03-03","South","London",6);
2> GO
(1 rows affected)
1> INSERT INTO employee VALUES (5, "Robert",  "Black",  4467,"2004-07-02","East","Newton",7);
2> GO
(1 rows affected)
1> INSERT INTO employee VALUES (6, "Linda" ,  "Green" , 6456,"2002-05-19","East","Calgary",8);
2> GO
(1 rows affected)
1> INSERT INTO employee VALUES (7, "David" ,  "Larry",  5345,"2008-03-18","West","New York",9);
2> GO
(1 rows affected)
1> INSERT INTO employee VALUES (8, "James" ,  "Cat",    4234,"2007-07-17","West","Regina",9);
2> GO
(1 rows affected)
1> INSERT INTO employee VALUES (9, "Joan"  ,  "Act",    6123,"2001-04-16","North","Toronto",10);
2> GO
(1 rows affected)
1>
2> select * from employee;
3> GO
id          first_name last_name  salary       start_Date              region     city                 managerid
----------- ---------- ---------- ------------ ----------------------- ---------- -------------------- -----------
          1 Jason      Martin          5890.00 2005-03-22 00:00:00.000 North      Vancouver                      3
          2 Alison     Mathews         4789.00 2003-07-21 00:00:00.000 South      Utown                          4
          3 James      Smith           6678.00 2001-12-01 00:00:00.000 North      Paris                          5
          4 Celia      Rice            5567.00 2006-03-03 00:00:00.000 South      London                         6
          5 Robert     Black           4467.00 2004-07-02 00:00:00.000 East       Newton                         7
          6 Linda      Green           6456.00 2002-05-19 00:00:00.000 East       Calgary                        8
          7 David      Larry           5345.00 2008-03-18 00:00:00.000 West       New York                       9
          8 James      Cat             4234.00 2007-07-17 00:00:00.000 West       Regina                         9
          9 Joan       Act             6123.00 2001-04-16 00:00:00.000 North      Toronto                       10
(9 rows affected)
1>
2>
3>
4> SELECT
5>   ID,
6>   ManagerID,
7>   YEAR(Start_Date) AS Order_Year,
8>   COUNT(*)        AS Order_Count
9> FROM
10>   Employee
11> GROUP BY
12>   ID,
13>   ManagerID,
14>   YEAR(Start_Date)
15> WITH ROLLUP
16>
17>
18>
19> drop table employee;
20> GO
ID          ManagerID   Order_Year  Order_Count
----------- ----------- ----------- -----------
          1           3        2005           1
          1           3        NULL           1
          1        NULL        NULL           1
          2           4        2003           1
          2           4        NULL           1
          2        NULL        NULL           1
          3           5        2001           1
          3           5        NULL           1
          3        NULL        NULL           1
          4           6        2006           1
          4           6        NULL           1
          4        NULL        NULL           1
          5           7        2004           1
          5           7        NULL           1
          5        NULL        NULL           1
          6           8        2002           1
          6           8        NULL           1
          6        NULL        NULL           1
          7           9        2008           1
          7           9        NULL           1
          7        NULL        NULL           1
          8           9        2007           1
          8           9        NULL           1
          8        NULL        NULL           1
          9          10        2001           1
          9          10        NULL           1
          9        NULL        NULL           1
       NULL        NULL        NULL           9
(28 rows affected)


Summarizing Data with ROLLUP

Use WITH ROLLUP with GROUP BY to add hierarchical data summaries based on the ordering of columns in the GROUP BY clause.
6>
7> CREATE TABLE employee(
8>    id          INTEGER NOT NULL PRIMARY KEY,
9>    first_name  VARCHAR(10),
10>    last_name   VARCHAR(10),
11>    salary      DECIMAL(10,2),
12>    start_Date  DATETIME,
13>    region      VARCHAR(10),
14>    city        VARCHAR(20)
15> );
16> GO
1> INSERT INTO employee VALUES (1, "Jason" ,  "Martin", 5890,"2005-03-22","North","Vancouver");
2> INSERT INTO employee VALUES (2, "Alison",  "Mathews",4789,"2003-07-21","South","Utown");
3> INSERT INTO employee VALUES (3, "James" ,  "Smith",  6678,"2001-12-01","North","Paris");
4> INSERT INTO employee VALUES (4, "Celia" ,  "Rice",   5567,"2006-03-03","South","London");
5> INSERT INTO employee VALUES (5, "Robert",  "Black",  4467,"2004-07-02","East","Newton");
6> INSERT INTO employee VALUES (6, "Linda" ,  "Green" , 6456,"2002-05-19","East","Calgary");
7> INSERT INTO employee VALUES (7, "David" ,  "Larry",  5345,"2008-03-18","West","New York");
8> INSERT INTO employee VALUES (8, "James" ,  "Cat",    4234,"2007-07-17","West","Regina");
9> INSERT INTO employee VALUES (9, "Joan"  ,  "Act",    6123,"2001-04-16","North","Toronto");
10> GO
(1 rows affected)
(1 rows affected)
(1 rows affected)
(1 rows affected)
(1 rows affected)
(1 rows affected)
(1 rows affected)
(1 rows affected)
(1 rows affected)
1> select * from employee;
2> GO
id          first_name last_name  salary       start_Date              region     city
----------- ---------- ---------- ------------ ----------------------- ---------- --------------------
          1 Jason      Martin          5890.00 2005-03-22 00:00:00.000 North      Vancouver
          2 Alison     Mathews         4789.00 2003-07-21 00:00:00.000 South      Utown
          3 James      Smith           6678.00 2001-12-01 00:00:00.000 North      Paris
          4 Celia      Rice            5567.00 2006-03-03 00:00:00.000 South      London
          5 Robert     Black           4467.00 2004-07-02 00:00:00.000 East       Newton
          6 Linda      Green           6456.00 2002-05-19 00:00:00.000 East       Calgary
          7 David      Larry           5345.00 2008-03-18 00:00:00.000 West       New York
          8 James      Cat             4234.00 2007-07-17 00:00:00.000 West       Regina
          9 Joan       Act             6123.00 2001-04-16 00:00:00.000 North      Toronto
(9 rows affected)
1>
2> CREATE TABLE title(
3>    id  INTEGER,
4>    job_title VARCHAR(20)
5> );
6> GO
1> INSERT INTO title VALUES (1, "developer");
2> INSERT INTO title VALUES (1, "manager");
3> INSERT INTO title VALUES (2, "tester");
4> INSERT INTO title VALUES (2, "programmer");
5> INSERT INTO title VALUES (3, "boss");
6> INSERT INTO title VALUES (4, "sales");
7> INSERT INTO title VALUES (5, "market");
8> INSERT INTO title VALUES (6, "coder");
9> INSERT INTO title VALUES (7, "tester");
10> INSERT INTO title VALUES (8, "developer");
11> INSERT INTO title VALUES (9, "manager");
12> GO
(1 rows affected)
(1 rows affected)
(1 rows affected)
(1 rows affected)
(1 rows affected)
(1 rows affected)
(1 rows affected)
(1 rows affected)
(1 rows affected)
(1 rows affected)
(1 rows affected)
1>
2>
3> SELECT i.region,
4> SUM(i.salary) Total
5> FROM employee i
6> INNER JOIN title p ON
7> i.ID = p.ID
8> GROUP BY i.region
9> WITH ROLLUP
10>
11>
12> drop table employee;
13> drop table title;
14> GO
region     Total
---------- ----------------------------------------
East                                       10923.00
North                                      24581.00
South                                      15145.00
West                                        9579.00
NULL                                       60228.00
(5 rows affected)
1>
2>


Using ROLLUP to Get the Order Count by Year and Month

3>
4> CREATE TABLE employee(
5>    id          INTEGER NOT NULL PRIMARY KEY,
6>    first_name  VARCHAR(10),
7>    last_name   VARCHAR(10),
8>    salary      DECIMAL(10,2),
9>    start_Date  DATETIME,
10>    region      VARCHAR(10),
11>    city        VARCHAR(20),
12>    managerid   INTEGER
13> );
14> GO
1> INSERT INTO employee VALUES (1, "Jason" ,  "Martin", 5890,"2005-03-22","North","Vancouver",3);
2> GO
(1 rows affected)
1> INSERT INTO employee VALUES (2, "Alison",  "Mathews",4789,"2003-07-21","South","Utown",4);
2> GO
(1 rows affected)
1> INSERT INTO employee VALUES (3, "James" ,  "Smith",  6678,"2001-12-01","North","Paris",5);
2> GO
(1 rows affected)
1> INSERT INTO employee VALUES (4, "Celia" ,  "Rice",   5567,"2006-03-03","South","London",6);
2> GO
(1 rows affected)
1> INSERT INTO employee VALUES (5, "Robert",  "Black",  4467,"2004-07-02","East","Newton",7);
2> GO
(1 rows affected)
1> INSERT INTO employee VALUES (6, "Linda" ,  "Green" , 6456,"2002-05-19","East","Calgary",8);
2> GO
(1 rows affected)
1> INSERT INTO employee VALUES (7, "David" ,  "Larry",  5345,"2008-03-18","West","New York",9);
2> GO
(1 rows affected)
1> INSERT INTO employee VALUES (8, "James" ,  "Cat",    4234,"2007-07-17","West","Regina",9);
2> GO
(1 rows affected)
1> INSERT INTO employee VALUES (9, "Joan"  ,  "Act",    6123,"2001-04-16","North","Toronto",10);
2> GO
(1 rows affected)
1>
2> select * from employee;
3> GO
id          first_name last_name  salary       start_Date              region     city                 managerid
----------- ---------- ---------- ------------ ----------------------- ---------- -------------------- -----------
          1 Jason      Martin          5890.00 2005-03-22 00:00:00.000 North      Vancouver                      3
          2 Alison     Mathews         4789.00 2003-07-21 00:00:00.000 South      Utown                          4
          3 James      Smith           6678.00 2001-12-01 00:00:00.000 North      Paris                          5
          4 Celia      Rice            5567.00 2006-03-03 00:00:00.000 South      London                         6
          5 Robert     Black           4467.00 2004-07-02 00:00:00.000 East       Newton                         7
          6 Linda      Green           6456.00 2002-05-19 00:00:00.000 East       Calgary                        8
          7 David      Larry           5345.00 2008-03-18 00:00:00.000 West       New York                       9
          8 James      Cat             4234.00 2007-07-17 00:00:00.000 West       Regina                         9
          9 Joan       Act             6123.00 2001-04-16 00:00:00.000 North      Toronto                       10
(9 rows affected)
1>
2>
3> SELECT
4>   YEAR(Start_Date)  AS Oyear,
5>   MONTH(Start_Date) AS Omonth,
6>   COUNT(*)         AS Order_Count
7> FROM
8>   Employee
9> GROUP BY
10>   YEAR(Start_Date),
11>   MONTH(Start_Date)
12> WITH ROLLUP
13>
14>
15>
16>
17> drop table employee;
18> GO
Oyear       Omonth      Order_Count
----------- ----------- -----------
       2001           4           1
       2001          12           1
       2001        NULL           2
       2002           5           1
       2002        NULL           1
       2003           7           1
       2003        NULL           1
       2004           7           1
       2004        NULL           1
       2005           3           1
       2005        NULL           1
       2006           3           1
       2006        NULL           1
       2007           7           1
       2007        NULL           1
       2008           3           1
       2008        NULL           1
       NULL        NULL           9
(18 rows affected)


Using the ROLLUP Operator

ROLLUP with GROUP BY calculates all possible subtotals and totals in the GROUP BY clause from left to right.
5>
6> CREATE TABLE Classification (
7>      Classif_ID         integer  NOT NULL PRIMARY KEY,
8>      Classification    varchar(25))
9> GO
1>
2> INSERT into Classification VALUES( 1,"Pop")
3> INSERT into Classification VALUES( 2,"Country")
4> INSERT into Classification VALUES( 3,"Alternative")
5> INSERT into Classification VALUES( 4,"Metal")
6> GO
(1 rows affected)
(1 rows affected)
(1 rows affected)
(1 rows affected)
1>
2>
3> CREATE TABLE CD (
4>      CD_ID              integer  NOT NULL PRIMARY KEY,
5>      CD_Title           varchar(40),
6>      Composer_ID        integer  NOT NULL,
7>      Classif_ID         integer  NOT NULL,
8>      SalesPrice        money,
9>      AverageCost       money)
10> GO
1> INSERT into CD VALUES(2000,"John",100,1,16.99,6.99)
2> INSERT into CD VALUES(2001,"Chicago 16",107,1,14.99,5.99)
3> INSERT into CD VALUES(2002,"Chicago 17",107,1,14.99,5.99)
4> INSERT into CD VALUES(2003,"Chicago 18",107,1,14.99,5.99)
5> INSERT into CD VALUES(2004,"Greatest Hits",107,1,16.99,7.99)
6> INSERT into CD VALUES(2005,"Midnight",101,3,14.99,5.99)
7> INSERT into CD VALUES(2006,"Mode",115,3,14.99,5.99)
8> INSERT into CD VALUES(2007,"Ultra",115,3,15.99,5.99)
9> INSERT into CD VALUES(2008,"Mindcrime",102,4,14.99,5.99)
10> INSERT into CD VALUES(2009,"Empire",102,4,14.99,5.99)
11> INSERT into CD VALUES(2010,"Land",102,4,12.99,4.99)
12> INSERT into CD VALUES(2011,"Night",103,4,11.99,3.99)
13> INSERT into CD VALUES(2012,"Pyromania",103,4,14.99,5.99)
14> INSERT into CD VALUES(2013,"Hysteria",103,4,14.99,5.99)
15> INSERT into CD VALUES(2014,"Hits",103,4,13.99,4.99)
16> INSERT into CD VALUES(2015,"Hits 2",104,2,15.99,6.99)
17> INSERT into CD VALUES(2016,"Greatest",105,2,14.99,5.99)
18> INSERT into CD VALUES(2017,"Hits 3",106,1,13.99,5.99)
19> INSERT into CD VALUES(2018,"Deep",108,1,12.99,2.99)
20> INSERT into CD VALUES(2019,"Turning",109,1,14.99,5.99)
21> INSERT into CD VALUES(2020,"TheHits",109,1,16.99,7.99)
22> INSERT into CD VALUES(2021,"Cars",110,1,9.99,3.99)
23> INSERT into CD VALUES(2022,"Anthology",110,1,25.99,11.99)
24> INSERT into CD VALUES(2023,"City",110,1,14.99,5.99)
25> INSERT into CD VALUES(2024,"Rick",111,1,11.99,2.99)
26> INSERT into CD VALUES(2025,"Live",112,1,19.99,8.99)
27> INSERT into CD VALUES(2026,"Pat",113,1,16.99,6.99)
28> INSERT into CD VALUES(2027,"Big",114,1,14.99,5.99)
29> INSERT into CD VALUES(2028,"Hurting",114,1,11.99,3.99)
30> INSERT into CD VALUES(2029,"Vol 1",116,1,9.99,2.99)
31> INSERT into CD VALUES(2030,"Vol 2",116,1,9.99,2.99)
32> GO
(1 rows affected)
(1 rows affected)
(1 rows affected)
(1 rows affected)
(1 rows affected)
(1 rows affected)
(1 rows affected)
(1 rows affected)
(1 rows affected)
(1 rows affected)
(1 rows affected)
(1 rows affected)
(1 rows affected)
(1 rows affected)
(1 rows affected)
(1 rows affected)
(1 rows affected)
(1 rows affected)
(1 rows affected)
(1 rows affected)
(1 rows affected)
(1 rows affected)
(1 rows affected)
(1 rows affected)
(1 rows affected)
(1 rows affected)
(1 rows affected)
(1 rows affected)
(1 rows affected)
(1 rows affected)
(1 rows affected)
1>
2>
3>
4> SELECT CD.Classif_ID,Classification.Classification,
5>        Count(CD.CD_ID) "Total Offerings"
6> FROM CD,Classification
7> WHERE CD.Classif_ID = Classification.Classif_ID
8> GROUP BY Classification.Classification, CD.Classif_ID with ROLLUP
9> GO
Classif_ID   Classification            Total Offerings
----------- ------------------------- ---------------
          3 Alternative                             3
       NULL Alternative                             3
          2 Country                                 2
       NULL Country                                 2
          4 Metal                                   7
       NULL Metal                                   7
          1 Pop                                    19
       NULL Pop                                    19
       NULL NULL                                   31
(9 rows affected)
1>
2> drop table Classification;
3> drop table CD;
4> GO


WITH ROLLUP for calculating subtotals and totals on the first column in the GROUP BY column list

6> CREATE TABLE employee(
7>    id          INTEGER NOT NULL PRIMARY KEY,
8>    first_name  VARCHAR(10),
9>    last_name   VARCHAR(10),
10>    salary      DECIMAL(10,2),
11>    start_Date  DATETIME,
12>    region      VARCHAR(10),
13>    city        VARCHAR(20),
14>    managerid   INTEGER
15> );
16> GO
1> INSERT INTO employee VALUES (1, "Jason" ,  "Martin", 5890,"2005-03-22","North","Vancouver",3);
2> GO
(1 rows affected)
1> INSERT INTO employee VALUES (2, "Alison",  "Mathews",4789,"2003-07-21","South","Utown",4);
2> GO
(1 rows affected)
1> INSERT INTO employee VALUES (3, "James" ,  "Smith",  6678,"2001-12-01","North","Paris",5);
2> GO
(1 rows affected)
1> INSERT INTO employee VALUES (4, "Celia" ,  "Rice",   5567,"2006-03-03","South","London",6);
2> GO
(1 rows affected)
1> INSERT INTO employee VALUES (5, "Robert",  "Black",  4467,"2004-07-02","East","Newton",7);
2> GO
(1 rows affected)
1> INSERT INTO employee VALUES (6, "Linda" ,  "Green" , 6456,"2002-05-19","East","Calgary",8);
2> GO
(1 rows affected)
1> INSERT INTO employee VALUES (7, "David" ,  "Larry",  5345,"2008-03-18","West","New York",9);
2> GO
(1 rows affected)
1> INSERT INTO employee VALUES (8, "James" ,  "Cat",    4234,"2007-07-17","West","Regina",9);
2> GO
(1 rows affected)
1> INSERT INTO employee VALUES (9, "Joan"  ,  "Act",    6123,"2001-04-16","North","Toronto",10);
2> GO
(1 rows affected)
1>
2> select * from employee;
3> GO
id          first_name last_name  salary       start_Date              region     city                 managerid
----------- ---------- ---------- ------------ ----------------------- ---------- -------------------- -----------
          1 Jason      Martin          5890.00 2005-03-22 00:00:00.000 North      Vancouver                      3
          2 Alison     Mathews         4789.00 2003-07-21 00:00:00.000 South      Utown                          4
          3 James      Smith           6678.00 2001-12-01 00:00:00.000 North      Paris                          5
          4 Celia      Rice            5567.00 2006-03-03 00:00:00.000 South      London                         6
          5 Robert     Black           4467.00 2004-07-02 00:00:00.000 East       Newton                         7
          6 Linda      Green           6456.00 2002-05-19 00:00:00.000 East       Calgary                        8
          7 David      Larry           5345.00 2008-03-18 00:00:00.000 West       New York                       9
          8 James      Cat             4234.00 2007-07-17 00:00:00.000 West       Regina                         9
          9 Joan       Act             6123.00 2001-04-16 00:00:00.000 North      Toronto                       10
(9 rows affected)
1>
2>
3>
4> SELECT region, city, SUM(salary)
5> FROM Employee
6> GROUP BY region, city
7> WITH ROLLUP
8> GO
region     city
---------- -------------------- ----------------------------------------
East       Calgary                                               6456.00
East       Newton                                                4467.00
East       NULL                                                 10923.00
North      Paris                                                 6678.00
North      Toronto                                               6123.00
North      Vancouver                                             5890.00
North      NULL                                                 18691.00
South      London                                                5567.00
South      Utown                                                 4789.00
South      NULL                                                 10356.00
West       New York                                              5345.00
West       Regina                                                4234.00
West       NULL                                                  9579.00
NULL       NULL                                                 49549.00
(14 rows affected)
1>
2>
3> drop table employee;
4> GO