MySQL learning record (7)

1. function

1.1 classification

• Arithmetic functions （ A function used for numerical calculation ）
• String function （ A function used to perform string operations ）
• Date function （ Functions for date operations ）
• Conversion function （ Functions used to convert data types and values ）
• Aggregate functions （ Functions for data aggregation ）

1.1.1 Arithmetic functions

-- First create a table to demonstrate 
-- DDL ： Create table 
USE shop;
DROP TABLE IF EXISTS samplemath;
CREATE TABLE samplemath
(m float(10,3),
n INT,
p INT);

-- DML ： insert data 
START TRANSACTION; --  Start business 
INSERT INTO samplemath(m, n, p) VALUES (500, 0, NULL);
INSERT INTO samplemath(m, n, p) VALUES (-180, 0, NULL);
INSERT INTO samplemath(m, n, p) VALUES (NULL, NULL, NULL);
INSERT INTO samplemath(m, n, p) VALUES (NULL, 7, 3);
INSERT INTO samplemath(m, n, p) VALUES (NULL, 5, 2);
INSERT INTO samplemath(m, n, p) VALUES (NULL, 4, NULL);
INSERT INTO samplemath(m, n, p) VALUES (8, NULL, 3);
INSERT INTO samplemath(m, n, p) VALUES (2.27, 1, NULL);
INSERT INTO samplemath(m, n, p) VALUES (5.555,2, NULL);
INSERT INTO samplemath(m, n, p) VALUES (NULL, 1, NULL);
INSERT INTO samplemath(m, n, p) VALUES (8.76, NULL, NULL);
COMMIT; --  Commit transaction 
--  Query table content 
SELECT * FROM samplemath;
+----------+------+------+
| m        | n    | p    |
+----------+------+------+
|  500.000 |    0 | NULL |
| -180.000 |    0 | NULL |
|     NULL | NULL | NULL |
|     NULL |    7 |    3 |
|     NULL |    5 |    2 |
|     NULL |    4 | NULL |
|    8.000 | NULL |    3 |
|    2.270 |    1 | NULL |
|    5.555 |    2 | NULL |
|     NULL |    1 | NULL |
|    8.760 | NULL | NULL |
+----------+------+------+
11 rows in set (0.00 sec)

 

• ABS – The absolute value （absolute value）

grammar ：ABS( The number )

ABS The function is used to calculate the absolute value of a number , Represents the distance from a number to the origin .

When ABS The argument to the function is NULL when , The return value is also NULL.

• MOD – Mod

grammar ：MOD( Divisor , Divisor )

MOD Is to calculate the remainder of division （ Seeking remainder ） Function of , yes modulo Abbreviation . The concept that decimals have no remainder , You can only remainder integer Columns .

Be careful ： Mainstream DBMS All support MOD function , Only SQL Server The function is not supported , Its use % Sign to calculate the remainder .

• ROUND – rounding

grammar ：ROUND( Object value , Keep the number of decimal places )

ROUND The function is used for rounding .

Be careful ： When parameters   Keep the number of decimal places   When is a variable , There may be mistakes , Use variables with caution

select * from samplemath;
 SELECT m, ABS(m) AS abs_col,
 n,p, MOD(n,p) AS mod_col,
 ROUND(m,1) AS round_col
 FROM samplemath;

 

1.1.2  String function  

• CONCAT – Splicing

grammar ：CONCAT(str1, str2, str3)

MySQL Use in CONCAT Function .

• LENGTH – String length

grammar ：LENGTH( character string )

• LOWER – Lowercase conversion

LOWER Function can only be used for English letters , It converts all strings in the parameter to lowercase . This function is not applicable to situations other than English letters , Does not affect the original lowercase characters .

Allied , UPPER The function is used to convert to uppercase .

• REPLACE – String replacement

grammar ：REPLACE( Object string , String before replacement , Replaced string )

• SUBSTRING – String truncation

grammar ：SUBSTRING （ Object string FROM Intercept start position FOR Number of characters intercepted ）

Use SUBSTRING function You can truncate part of the string . The starting position of the interception is calculated from the leftmost side of the string , The index value starts with 1.

• SUBSTRING_INDEX – The string is truncated by index

grammar ：SUBSTRING_INDEX ( Original string , Separator ,n)

This function is used to obtain the original string, which is divided according to the separator , The first n Before a separator （ Or after ） Substring of , Supports forward and reverse indexing , The initial values caused by the cable are 1 and -1.

-- DDL ： Create table 
USE  shop;
DROP TABLE IF EXISTS samplestr;
CREATE TABLE samplestr
(str1 VARCHAR (40),
str2 VARCHAR (40),
str3 VARCHAR (40)
);
-- DML： insert data 
START TRANSACTION;
INSERT INTO samplestr (str1, str2, str3) VALUES ('opx',	'rt', NULL);
INSERT INTO samplestr (str1, str2, str3) VALUES ('abc', 'def', NULL);
INSERT INTO samplestr (str1, str2, str3) VALUES (' The sun ',	' The moon ', ' Mars ');
INSERT INTO samplestr (str1, str2, str3) VALUES ('aaa',	NULL, NULL);
INSERT INTO samplestr (str1, str2, str3) VALUES (NULL, 'xyz', NULL);
INSERT INTO samplestr (str1, str2, str3) VALUES ('@!#$%', NULL, NULL);
INSERT INTO samplestr (str1, str2, str3) VALUES ('ABC', NULL, NULL);
INSERT INTO samplestr (str1, str2, str3) VALUES ('aBC', NULL, NULL);
INSERT INTO samplestr (str1, str2, str3) VALUES ('abc ha-ha ',  'abc', 'ABC');
INSERT INTO samplestr (str1, str2, str3) VALUES ('abcdefabc', 'abc', 'ABC');
INSERT INTO samplestr (str1, str2, str3) VALUES ('micmic', 'i', 'I');
COMMIT;
--  Confirm the contents in the table 
SELECT * FROM samplestr;

select *,CONCAT(str1,str2,str3) AS str_concat, length(str1) as str_len,lower(str1)as str_low,
replace(str1,str2,str3)as rep_str,substring(str1 from 3 for 2)as sub_str
from samplestr;

 ps:replace In is the object string （ Parameters 1） And the string before replacement （ Parameters 2） Replace the same part with the replaced string （ Parameters 3） The corresponding content in .

1.1.3  Date function

• CURRENT_DATE – Get current date
• CURRENT_TIME – current time
• CURRENT_TIMESTAMP – Current date and time
• EXTRACT – Intercept date element

grammar ：EXTRACT( Date element FROM date )

Use EXTRACT The function can truncate part of the date data , for example “ year ”

“ month ”, perhaps “ Hours ”“ second ” etc. . The return value of this function is not a date type, but a numeric type

SELECT CURRENY_DATE;
SELECT CURRENT_TIME;
SELECT CURRENT_TIMESTAMP;
SELECT CURRENT_TIMESTAMP as now,
EXTRACT(YEAR   FROM CURRENT_TIMESTAMP) AS year,
EXTRACT(MONTH  FROM CURRENT_TIMESTAMP) AS month,
EXTRACT(DAY    FROM CURRENT_TIMESTAMP) AS day,
EXTRACT(HOUR   FROM CURRENT_TIMESTAMP) AS hour,
EXTRACT(MINUTE FROM CURRENT_TIMESTAMP) AS MINute,
EXTRACT(SECOND FROM CURRENT_TIMESTAMP) AS second;
-- There should be no space between the function and the following parentheses , Otherwise, it will report a mistake 

 --EXTRACT There should be no space between the function and the following parentheses , Otherwise, it will report a mistake .

1.1.4  Conversion function

• CAST – Type conversion

grammar ：CAST（ The value before conversion AS The data type you want to convert ）

--  Convert string type to numeric type 
SELECT CAST('0001' AS SIGNED INTEGER) AS int_col;
--  Convert string type to date type 
SELECT CAST('2009-12-14' AS DATE) AS date_col;

• COALESCE – take NULL Convert to other values

grammar ：COALESCE( data 1, data 2, data 3……)

COALESCE yes SQL Special functions . This function will return variable parameters A Starting from the middle left 1 Not one NULL Value . The number of parameters is variable , Therefore, it can be increased infinitely as needed .

stay SQL In the sentence NULL The conversion function is used when converting to other values .

SELECT COALESCE(NULL, 11) AS col_1,
COALESCE(NULL, 'hello world', NULL) AS col_2,
COALESCE(NULL, NULL, '2020-11-01') AS col_3;

2. The predicate

The predicate ： A function that returns a true value . Include TRUE / FALSE / UNKNOWN.

Predicates mainly include the following ：

• LIKE
• BETWEEN
• IS NULL、IS NOT NULL
• IN
• EXISTS

2.1 LIKE The predicate – Partial consistent query for Strings  

  Partial consistency can be roughly divided into front consistency 、 There are three types of middle consistency and rear consistency .

     % The function of is similar to wildcard

• _ Underscores match any 1 Characters

Use _（ Underline ） Instead of %, And % The difference is , It represents the “ arbitrarily 1 Characters ”.

-- DDL ： Create table 
CREATE TABLE samplelike
( strcol VARCHAR(6) NOT NULL,
PRIMARY KEY (strcol)
samplelike);
-- DML ： insert data 
START TRANSACTION; --  Start business 
INSERT INTO samplelike (strcol) VALUES ('abcddd');
INSERT INTO samplelike (strcol) VALUES ('dddabc');
INSERT INTO samplelike (strcol) VALUES ('abdddc');
INSERT INTO samplelike (strcol) VALUES ('abcdd');
INSERT INTO samplelike (strcol) VALUES ('ddabc');
INSERT INTO samplelike (strcol) VALUES ('abddc');
COMMIT; --  Commit transaction 
SELECT * FROM samplelike;
--  The front is consistent 
SELECT * 
FROM samplelike
WHERE strcol like 'ddd%';
--  The middle is consistent  
SELECT *
FROM samplelike
WHERE strcol like '%ddd%';
--  The rear is consistent   
SELECT *
FROM samplelike
WHERE strcol like "%ddd";
SELECT *
FROM samplelike
WHERE strcol like 'abc_';

2.2 BETWEEN The predicate – For range queries

Use BETWEEN You can query the range ,BETWEEN Used 3 Parameters .

--  Select the sales unit price as 100～ 1000 Yuan goods 
SELECT product_name, sale_price
FROM product
WHERE sale_price BETWEEN 100 AND 1000;

BETWEEN The characteristic of is that the results will include 100 and 1000 These two critical values , That is to say Closed interval . If you don't want the results to include critical values , Then you have to use < and >.

2.3 IS NULL、 IS NOT NULL – Used to determine whether it is NULL

In order to select some values as NULL Data of columns , Out of commission =, You can only use specific predicates IS NULL.

On the contrary , Want to choose NULL Data other than , Need to use IS NOT NULL.

SELECT product_name, purchase_price
FROM product
WHERE purchase_price IS NULL;
SELECT product_name, purchase_price
FROM product
WHERE purchase_price IS NOT NULL;

2.4 IN The predicate – OR Easy to use

The union of multiple query conditions You can choose to use or sentence .

--  adopt OR Specify multiple purchase unit prices to query 
SELECT product_name, purchase_price
FROM product
WHERE purchase_price = 320
OR purchase_price = 500
OR purchase_price = 5000;
-- Instead of using IN
SELECT product_name, purchase_price
FROM product
WHERE purchase_price IN (320, 500, 5000);

It should be noted that , In the use of IN and NOT IN You can't pick out NULL Data .

2.5 Use subqueries as IN Arguments to predicates

• IN /NOT IN And subquery

IN The predicate （NOT IN The predicate ） Has a usage that other predicates do not have , You can use a subquery as its parameter , Views can also be used as IN Parameters of .

-- DDL ： Create table 
DROP TABLE IF EXISTS shopproduct;
CREATE TABLE shopproduct
(  shop_id CHAR(4)     NOT NULL,
 shop_name VARCHAR(200) NOT NULL,
product_id CHAR(4)      NOT NULL,
  quantity INTEGER      NOT NULL,
PRIMARY KEY (shop_id, product_id) --  Specify primary key 
);
-- DML ： insert data 
START TRANSACTION; --  Start business 
INSERT INTO shopproduct (shop_id, shop_name, product_id, quantity) VALUES ('000A', ' Tokyo ', '0001', 30);
INSERT INTO shopproduct (shop_id, shop_name, product_id, quantity) VALUES ('000A', ' Tokyo ', '0002', 50);
INSERT INTO shopproduct (shop_id, shop_name, product_id, quantity) VALUES ('000A', ' Tokyo ', '0003', 15);
INSERT INTO shopproduct (shop_id, shop_name, product_id, quantity) VALUES ('000B', ' Nagoya ', '0002', 30);
INSERT INTO shopproduct (shop_id, shop_name, product_id, quantity) VALUES ('000B', ' Nagoya ', '0003', 120);
INSERT INTO shopproduct (shop_id, shop_name, product_id, quantity) VALUES ('000B', ' Nagoya ', '0004', 20);
INSERT INTO shopproduct (shop_id, shop_name, product_id, quantity) VALUES ('000B', ' Nagoya ', '0006', 10);
INSERT INTO shopproduct (shop_id, shop_name, product_id, quantity) VALUES ('000B', ' Nagoya ', '0007', 40);
INSERT INTO shopproduct (shop_id, shop_name, product_id, quantity) VALUES ('000C', ' Osaka ', '0003', 20);
INSERT INTO shopproduct (shop_id, shop_name, product_id, quantity) VALUES ('000C', ' Osaka ', '0004', 50);
INSERT INTO shopproduct (shop_id, shop_name, product_id, quantity) VALUES ('000C', ' Osaka ', '0006', 90);
INSERT INTO shopproduct (shop_id, shop_name, product_id, quantity) VALUES ('000C', ' Osaka ', '0007', 70);
INSERT INTO shopproduct (shop_id, shop_name, product_id, quantity) VALUES ('000D', ' Fukuoka, ', '0001', 100);
COMMIT; --  Commit transaction 


SELECT product_name, sale_price
FROM product
WHERE product_id IN (SELECT product_id
  FROM shopproduct
                       WHERE shop_id = '000C');

--  The expanded result of subquery 
SELECT product_name, sale_price
FROM product
WHERE product_id IN ('0003', '0004', '0006', '0007');

-- NOT IN  Use subqueries as parameters , Take out the sales unit price of goods not sold in Osaka stores 
SELECT product_name, sale_price
  FROM product
 WHERE product_id NOT IN (SELECT product_id
                            FROM shopproduct
                           WHERE shop_id = '000A');

2.6 EXISTS/ NOT EXISTS The predicate

• EXISTS How to use predicates

The function of predicate is  “ Determine whether there are records that meet certain conditions ”.

If such a record exists, it returns true （TRUE）, If it does not exist, return false （FALSE）.

EXISTS（ There is ） The subject of the predicate is “ Record ”.

EXISTS There is only one , Write casually .

SELECT product_name, sale_price
  FROM product AS p
 WHERE EXISTS (SELECT *
                 FROM shopproduct AS sp
                WHERE sp.shop_id = '000C'
                  AND sp.product_id = p.product_id);

3. CASE expression

CASE Expressions are used to distinguish situations , This distinction is commonly referred to in programming as （ Conditions ） Branch .

CASE WHEN < Evaluation expression > THEN < expression >
     WHEN < Evaluation expression > THEN < expression >
     WHEN < Evaluation expression > THEN < expression >
     .
     .
     .
ELSE < expression >
END 

When the above statement is executed , Judge in turn when Whether the expression is true , Yes, it is THEN The following sentence , If all when All expressions are false , execute ELSE The following sentence .
No matter how huge CASE expression , Finally, only one value will be returned .

-- Application scenarios 1： Get different column values according to different branches 
SELECT  product_name,
        CASE WHEN product_type = ' clothes ' THEN CONCAT('A ： ',product_type)
             WHEN product_type = ' Office Supplies '  THEN CONCAT('B ： ',product_type)
             WHEN product_type = ' Kitchenware '  THEN CONCAT('C ： ',product_type)
             ELSE NULL
        END AS abc_product_type
  FROM  product;
--
-- Application scenarios 2： Achieve aggregation in the column direction 
--  Perform line to line conversion on the total sales unit price calculated by commodity type 
SELECT SUM(CASE WHEN product_type = ' clothes ' THEN sale_price ELSE 0 END) AS sum_price_clothes,
       SUM(CASE WHEN product_type = ' Kitchenware ' THEN sale_price ELSE 0 END) AS sum_price_kitchen,
       SUM(CASE WHEN product_type = ' Office Supplies ' THEN sale_price ELSE 0 END) AS sum_price_office
  FROM product;

-- Application scenarios 3： Realize row to column conversion 
-- CASE WHEN  Implement a digital column  score  Transfer line column 
SELECT name,
       SUM(CASE WHEN subject = ' Chinese language and literature ' THEN score ELSE null END) as chinese,
       SUM(CASE WHEN subject = ' mathematics ' THEN score ELSE null END) as math,
       SUM(CASE WHEN subject = ' Foreign Languages ' THEN score ELSE null END) as english
  FROM score
 GROUP BY name;

-- CASE WHEN  Implement text column  subject  Transfer line column 
SELECT name,
       MAX(CASE WHEN subject = ' Chinese language and literature ' THEN subject ELSE null END) as chinese,
       MAX(CASE WHEN subject = ' mathematics ' THEN subject ELSE null END) as math,
       MIN(CASE WHEN subject = ' Foreign Languages ' THEN subject ELSE null END) as english
  FROM score
 GROUP BY name;

• When the column to be converted is a number , have access to SUM AVG MAX MIN Wait for the aggregate function ;
• When the column to be converted is text , have access to MAX MIN Wait for the aggregate function

Exercises ：

According to the sales unit price （ sale_price） Yes, practice 6.1 Medium product（ goods ） The goods in the table are classified as follows .

• Low end goods ： The sales unit price is in 1000 Below yen （T shirt 、 Office Supplies 、 Fork 、 Clean the board 、 Ball pen ）
• Mid range goods ： The sales unit price is in 1001 Above JPY 3000 Below yen （ kitchen knife ）
• High end goods ： The sales unit price is in 3001 Above JPY （ motion T T-shirt 、 pressure cooker ）

Please write down the statistics of the number of goods included in the above categories SELECT sentence , The results are shown below .

 SELECT COUNT(CASE WHEN sale_price <=1000 THEN product_name ELSE null END) AS low_price,
 COUNT(CASE WHEN  sale_price >1000 AND sale_price <=3000 THEN product_name  ELSE null END) AS mid_price,
 COUNT(CASE WHEN sale_price >3000 THEN product_name ELSE null END) AS high_price
 from product;

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