SQL Server/T-SQL Tutorial/Analytical Functions/CUBE
Содержание
- 1 A summary query that includes a final summary row with "WITH CUBE"
- 2 A summary query that includes a summary row for each set of groups
- 3 Creating the Vbase_cube View to Hide the CUBE Query Complexity
- 4 CUBE performs this rollup for every combination of grouped column values.
- 5 Summarizing Data with CUBE
- 6 Using GROUPING with CUBE
- 7 Using the CUBE Operator
A summary query that includes a final summary row with "WITH CUBE"
<source lang="sql">
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></source>
A summary query that includes a summary row for each set of groups
<source lang="sql">
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</source>
Creating the Vbase_cube View to Hide the CUBE Query Complexity
<source lang="sql">
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</source>
CUBE performs this rollup for every combination of grouped column values.
<source lang="sql">
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></source>
Summarizing Data with CUBE
<source lang="sql">
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></source>
Using GROUPING with CUBE
<source lang="sql">
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></source>
Using the CUBE Operator
<source lang="sql">
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</source>
