数据库知识点①

WHY SQL?
1.SQL is a very-high-level language, in which the programmer is able to avoid specifying a lot of data-manipulation details that would be necessary in languages like C++.
2.What makes SQL viable is that its queries are “optimized” quite well, yielding efficient query executions.
Queries :

1. Single-relation queries
2. Multi-relation queries
3. Subqueries
4. Grouping and Aggregation

（1）SELECT - FROM - WHERE statements

　　SELECT ... (desired attributes)

　　From ... （one or more tables）

　　WHERE ...（ condition about tuples of the tables）

EX: Using Beers(name, manf), what beers are made by Busch?

SELECT name,

FROM Beers,

WHERE manf = 'Busch'

（2）When there is one relation in the FROM clause, SELECT * clause stands for “all attributes of this relation.”

（3）If you want the result to have different attribute names, use “AS <new name>” to rename an attribute.

EX:Example based on Beers(name, manf):

SELECT name AS beername, manf
FROM  Beers
WHERE manf = ‘Busch’

（4）SQL allows duplicates in relations as well as in query results.

To force the elimination of duplicates, insert the keyword distinct after select.

Find the names of all branches in the loan relations, and remove duplicates

select distinct branch_name
from loan

The keyword all specifies that duplicates not be removed.

select all branch_name
from loan

　(5)Any expression that makes sense can appear as an element of a SELECT clause.

　　EX: from Sells(bar, beer, price):　

SELECT bar, beer,  price * 6 AS priceInYuan

FROM Sells;

（6）function 查询全体学生的姓名、出生年份和所有系，要求用小写字母表示所有系名。

SELECT Sname，2006-Sage AS 'Year of Birth: ' ，

LOWER(Sdept)

FROM Student；

(7)What we can use in select clause :

expressions

constants

functions

Attribute alias

（8）What you can use in WHERE:

attribute names of the relation(s) used in the FROM.

comparison operators: =, <>, <, >, <=, >=, between, in

apply arithmetic operations: stockprice*2

operations on strings (e.g., “||” for concatenation).

Lexicographic order on strings.

Pattern matching: s LIKE p

Special stuff for comparing dates and times.

（9）Range comparison: between

谓词： BETWEEN … AND … NOT BETWEEN … AND …
查询年龄在20~23岁（包括20岁和23岁）之间的学生的姓名、系别和年龄。

SELECT Sname，Sdept，Sage

FROM   Student

WHERE Sage BETWEEN 20 AND 23；

（10）Set operator: in

使用谓词： IN <值表>, NOT IN <值表>

<值表>： 用逗号分隔的一组取值

[例]查询信息系（IS）、数学系（MA）和计算机科学系（CS）学生的姓名和性别。

SELECT Sname，Ssex

FROM  Student

WHERE Sdept IN ( 'IS'，'MA'，'CS' );

（11）Patterns

WHERE clauses can have conditions in which a string is compared with a pattern, to see if it matches.

General form: <Attribute> LIKE <pattern> or <Attribute> NOT LIKE <pattern>

Pattern is a quoted string with [b]%[/b] = “any string”; [b]_[/b] = “any character.”
（12）The LIKE operator

s LIKE p: pattern matching on strings
p may contain two special symbols:
% = any sequence of characters
_ = any single character
（13）ESCAPE character

When the string contains ‘%’ or ‘_’, you need to use ESCAPE character
（14）Ordering the Display of Tuples

Use ‘Order by’ clause to specify the alphabetic order of the query result

select distinct customer_name
from    borrower
order by customer_name

We may specify desc for descending order or asc for ascending order, for each attribute; ascending order is the default.

Example: order by customer_name desc
Note: Order by can only be used as the last part of select statement
（15）Order by

[例] 查询全体学生情况，查询结果按所在系的系号升序排列，同一系中的学生按年龄降序排列。

SELECT  *
FROM  Student
ORDER BY Sdept ASC，Sage DESC；

（16）Null Values

Three-Valued Logic

To understand how AND, OR, and NOT work in 3-valued logic, think of TRUE = 1, FALSE = 0, and UNKNOWN = ½.
AND = MIN; OR = MAX, NOT(x) = 1-x.
Example:
TRUE AND (FALSE OR NOT(UNKNOWN)) = MIN(1, MAX(0, (1 - ½ ))) = MIN(1, MAX(0, ½ ) = MIN(1, ½ ) = ½.

（17）If x=Null then 4*(3-x)/7 is still NULL

If x=Null then x=“Joe” is UNKNOWN
Three boolean values:
FALSE = 0
UNKNOWN = 0.5
TRUE = 1
（18）Unexpected behavior:

SELECT *

FROM   Person

WHERE  age < 25  OR  age >= 2

Some Persons are not included !

（19）Testing for Null

Can test for NULL explicitly:

x IS NULL
x IS NOT NULL

SELECT *
FROM     Person
WHERE  age < 25  OR  age >= 25 OR age IS NULL

Now it includes all Persons

（20）Aggregations

SUM, AVG, COUNT, MIN, and MAX can be applied to a column in a SELECT clause to produce that aggregation on the column.
Also, COUNT(*) counts the number of tuples.

计数 COUNT（[DISTINCT|ALL] *） COUNT（[DISTINCT|ALL] <列名>）
计算总和 SUM（[DISTINCT|ALL] <列名>）
计算平均值 AVG（[DISTINCT|ALL] <列名>）
求最大值 MAX（[DISTINCT|ALL] <列名>）

求最小值 MIN（[DISTINCT|ALL] <列名>）

–DISTINCT短语：在计算时要取消指定列中的重复值
–ALL短语：不取消重复值
–ALL为缺省值

EX:From Sells(bar, beer, price), find the average price of Bud:

SELECT AVG(price)

FROM Sells

WHERE beer = ‘Bud’;

（21）Eliminating Duplicates in an Aggregation

DISTINCT inside an aggregation causes duplicates to be eliminated before the aggregation.
Example: find the number of different prices charged for Bud:

SELECT COUNT(DISTINCT price)
FROM Sells
WHERE beer = ‘Bud’;

（22）NULL’s Ignored in Aggregation

NULL never contributes to a sum, average, or count, and can never be the minimum or maximum of a column.
But if there are no non-NULL values in a column, then the result of the aggregation is NULL.
（23）Grouping

We may follow a SELECT-FROM-WHERE expression by GROUP BY and a list of attributes.
The relation that results from the SELECT-FROM-WHERE is grouped according to the values of all those attributes, and any aggregation is applied only within each group.
EX： From Sells(bar, beer, price), find the average price for each beer:

SELECT beer, AVG(price)
FROM Sells
GROUP BY beer;

（24）Restriction on SELECT Lists With Aggregation

If any aggregation is used, then each element of the SELECT list must be either:
1.Aggregated, or
2.An attribute on the GROUP BY list.
（25）Illegal Query Example

You might think you could find the bar that sells Bud the cheapest by:

SELECT bar, MIN(price)

FROM Sells

WHERE beer = ‘Bud’;

But this query is illegal in SQL.
Why? Note bar is neither aggregated nor on the GROUP BY list.
（26）HAVING Clauses

HAVING <condition> may follow a GROUP BY clause.
If so, the condition applies to each group, and groups not satisfying the condition are eliminated.

The next article：http://www.cnblogs.com/zpfbuaa/p/5479733.html