Displaying Data from Multiple Tables
Types of Joins
SQL:1999 Compliant Joins:
--Cross joins
--Natural joins
--Using clause
--Full or two sided outer joins
--Arbitrary join conditions for outer joins
Syntax：
Select tableA.column,tableB.column from tableA
[CROSS JOIN tableB] |
[NATURAL JOIN tableB] |
[JOIN tableB USING (column_name)] |
[JOIN tableB ON (tableA.column_name = tableB.column_name)] |
[LEFT | RIGHT | FULL OUTER JOIN tableB ON (tableA.column_name = tableB.column_name)];
Oracle Proprietary Joins
--Equijoin
select a.columnA, b.columnB,c.columnC from tableA a,tableB b,tableC c where a.id=b.id and b.id=c.id;
--Non-euqijoins
select a.columnA,b.columnB from tableA a,tableB b where a.salary between b.lowestsalary and b.highestsalary;
--Outer join
select a.column,b.column from tableA a,tableB b where a.column(+) = b.column;
select a.column,b.column from tableA a,tableB b where a.column = b.column(+);
--Self join
select a.columnA, a.columnB from tableA a,tableA b where a.columnC=b.columnC;
Cartesian Products
select ColumnA,ColumnB,ColumnC from tableA tableB;
select columnA,columnB from tableA cross jion tableB;
Aggregating Data Using Group Functions
Types of group functions: avg,count,max,min,sum,stddev,variance
select count(distinct columnA) from dual;
select avg(nvl(columnA,0) from tale;
using the group by clause on multiple columns
select avg(salary) from tableA group by columnA,columnB;
Syntax:
SELECT column,group_function FROM table [WHERE condition]
[group by group_by_expression] [having group_condition] [order by column];
Note:you can’t use where clause to restrict groups but you can use the having clause to restrict groups.
Error: select department_id,avg(salary) from employee where avg(salary)>8000 group by department_id;
Right:select department_id,avg(salary) from employee group by department_id having avg(salary)>8000;
nesting group functions :
select max(avg(salary)) from employees group by department_id;
Subqueries
SELECT select_list FROM table WHERE expr operator
(SELECT select _list FROM table);
Operator : IN , ANY , ALL
IN: Equal to any member in the list
ANY:compare value to each value returned by the subquery
ALL:compare value to every value returned by the subquery
<ANY means less than the maximum
>ANY means more than the minimum
=ANY is equivalent to IN
<ALL means less than the minimum
>ALL means more than the maximum
The NOT operator can be used with IN,ANY and ALL operators.
If one of the values returned by the inner query is a null value, and hence the entire query returns no rows. The reason is that all conditions that compare a null value result is a null.So whenever null values are likely to be part of the results set of a subquery,do not use the NOT IN operator.The NOT IN operator is equivalent to <>ALL.
Manipulating Data
Data Manipulation Language
A DML statement is executed when you:
-Add new rows to a table
-Modify exsitng rows in a table
-Remove exsting rows from a table
A transaction consists of a collection of DML statements that form a logical unit of work.
INSERT INTO table [(column [,column …])] VALUES (value [,value…]);
INSERT INTO table( login_time) values ( TO_DATE(DATE(’FEB 3, 1999’, ’MON DD, YYYY’));
INSERT ITNO (SELECT columnA,columnB from tableA where id=50) VALUES(avariableA,avariableB);
INSERT INTO (columnA) values (default);
UPDATE table SET column=value[,column =value,…] [WHERE condition];
DELETE [FROM] table [WHERE condition];
WITH CHECK OPTION keyword
The with check option keyword prohibits you from changing rows that are not in the subquery
The MERGE statement
Provides the ability to conditionally update or insert data into a database table
performs an update if the row exists,and an insert if it is a new row;
--avoids separate updates
--Increases performance and ease of use
--Is useful in data warehousing applications
Syntax:
MERGE INTO table_name table_alias
USING (table|view|sub_query) alias
ON (join condition)
WHEN MATCHED THEN
UPDATE SET
col1 = col_vall,
col2 = col_val2
WHEN NOT MATCHED THEN
INSERT (column_list)
VALUES (column_values);