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

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

3>
4>
5> create table Billings (
6>     BankerID           INTEGER,
7>     BillingNumber      INTEGER,
8>     BillingDate        datetime,
9>     BillingTotal       INTEGER,
10>     TermsID            INTEGER,
11>     BillingDueDate     datetime ,
12>     PaymentTotal       INTEGER,
13>     CreditTotal        INTEGER
14>
15> );
16> 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 CUBE
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> drop table Billings;
3> drop table Bankers;
4> GO
1>


A summary query that includes a summary row for each set of groups

4>
5>
6>
7>
8> create table Billings (
9>     BankerID           INTEGER,
10>     BillingNumber      INTEGER,
11>     BillingDate        datetime,
12>     BillingTotal       INTEGER,
13>     TermsID            INTEGER,
14>     BillingDueDate     datetime ,
15>     PaymentTotal       INTEGER,
16>     CreditTotal        INTEGER
17>
18> );
19> 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> SELECT BankerState, BankerCity, COUNT(*) AS QtyBankers
2>
3>
4> FROM Bankers
5> WHERE BankerState IN ("IA", "NJ")
6> GROUP BY BankerState, BankerCity WITH CUBE
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


Creating the Vbase_cube View to Hide the CUBE Query Complexity

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> CREATE VIEW Vbase_cube
5> AS
6> SELECT
7>   ID,
8>   GROUPING(ID)      AS Grp_Cust,
9>   YEAR(Start_Date)           AS Order_Year,
10>   GROUPING(YEAR(Start_Date)) AS Grp_Year,
11>   COUNT(*) as Order_Count
12> FROM
13>   Employee
14> GROUP BY
15>   ID,
16>   YEAR(Start_Date)
17> WITH CUBE
18> GO
1> --Selecting All Rows from the Vbase_cube View
2> SELECT
3>   *
4> FROM
5>   Vbase_cube
6> GO
ID          Grp_Cust Order_Year  Grp_Year Order_Count
----------- -------- ----------- -------- -----------
          1        0        2005        0           1
          1        0        NULL        1           1
          2        0        2003        0           1
          2        0        NULL        1           1
          3        0        2001        0           1
          3        0        NULL        1           1
          4        0        2006        0           1
          4        0        NULL        1           1
          5        0        2004        0           1
          5        0        NULL        1           1
          6        0        2002        0           1
          6        0        NULL        1           1
          7        0        2008        0           1
          7        0        NULL        1           1
          8        0        2007        0           1
          8        0        NULL        1           1
          9        0        2001        0           1
          9        0        NULL        1           1
       NULL        1        NULL        1           9
       NULL        1        2001        0           2
       NULL        1        2002        0           1
       NULL        1        2003        0           1
       NULL        1        2004        0           1
       NULL        1        2005        0           1
       NULL        1        2006        0           1
       NULL        1        2007        0           1
       NULL        1        2008        0           1
(27 rows affected)
1>
2> drop view Vbase_cube
3> GO
1>
2>
3> drop table employee;
4> GO


CUBE performs this rollup for every combination of grouped column values.

The CUBE operator is an expanded version of the ROLLUP operator.

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>    managerid   INTEGER
16> );
17> 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 CUBE
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
NULL       Calgary                                               6456.00
NULL       London                                                5567.00
NULL       New York                                              5345.00
NULL       Newton                                                4467.00
NULL       Paris                                                 6678.00
NULL       Regina                                                4234.00
NULL       Toronto                                               6123.00
NULL       Utown                                                 4789.00
NULL       Vancouver                                             5890.00
(23 rows affected)
1>
2>
3> drop table employee;
4> GO
1>
2>
3>


Summarizing Data with CUBE

WITH CUBE summarizes total values based on the columns in the GROUP BY clause.
Extra NULL values were included in the result set for those rows that contained the WITH CUBE aggregate totals.
15> CREATE TABLE employee(
16>    id          INTEGER NOT NULL PRIMARY KEY,
17>    first_name  VARCHAR(10),
18>    last_name   VARCHAR(10),
19>    salary      DECIMAL(10,2),
20>    start_Date  DATETIME,
21>    region      VARCHAR(10),
22>    city        VARCHAR(20),
23>    managerid   INTEGER
24> );
25> 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 i.region,SUM(i.salary) Total
4> FROM employee i
5> GROUP BY i.region
6> WITH CUBE;
7> GO
region     Total
---------- ----------------------------------------
East                                       10923.00
North                                      18691.00
South                                      10356.00
West                                        9579.00
NULL                                       49549.00
(5 rows affected)
1>
2>
3>
4>
5> drop table employee;
6> GO
1>


Using GROUPING with CUBE

5> CREATE TABLE employee(
6>    id          INTEGER NOT NULL PRIMARY KEY,
7>    first_name  VARCHAR(10),
8>    last_name   VARCHAR(10),
9>    salary      DECIMAL(10,2),
10>    start_Date  DATETIME,
11>    region      VARCHAR(10),
12>    city        VARCHAR(20),
13>    managerid   INTEGER
14> );
15> 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 i.region, GROUPING(i.region) Source,
4> SUM(i.salary) Total
5> FROM employee i
6> GROUP BY i.region
7> WITH CUBE;
8> GO
region     Source Total
---------- ------ ----------------------------------------
East            0                                 10923.00
North           0                                 18691.00
South           0                                 10356.00
West            0                                  9579.00
NULL            1                                 49549.00
(5 rows affected)
1>
2>
3>
4> drop table employee;
5> GO
1>


Using the CUBE Operator

CUBE with GROUP BY calculates aggregate function on all records and appends this to the last row

10> CREATE TABLE Classification (
11>      Classif_ID         integer  NOT NULL PRIMARY KEY,
12>      Classification    varchar(25))
13> 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 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 with CUBE
9> GO
Classification            Total Offerings
------------------------- ---------------
Alternative                             3
Country                                 2
Metal                                   7
Pop                                    19
NULL                                   31
(5 rows affected)
1>
2> drop table Classification;
3> drop table CD;
4> GO