python-day43--單表查詢之關鍵字執行優先級（重點）
阿新 • • 發佈：2017-09-09
exp 連接字符串 四則運算 img isp 數字 group 強調 alex 
一、關鍵字的執行優先級(重點)
1.關鍵字執行優先級
from where #約束條件（在數據產生之前執行） group by #分組 沒有分組則默認一組 按照select後的字段取得一張新的虛擬表，有聚合函數則執行聚合函數 having #過濾條件 ,having 是根據內存中的虛擬表 過濾的 ；出現having的時候肯定是有group by，不然沒意義 distinct #去重 #在select 之後執行 忽略先後順序 order by #排序 #在select 之後執行 忽略先後順序limit #限制查詢的記錄數 #在select 之後執行 忽略先後順序
1.找到表:from
2.拿著where指定的約束條件，去文件/表中取出一條條記錄
3.將取出的一條條記錄進行分組group by，如果沒有group by，則整體作為一組
4.按照select後的字段得到一張新的虛擬表，如果有聚合函數，則將組內數據進行聚合
5.將4的結果過濾：having
6.查出結果：select
7.去重
8.將結果按條件排序：order by
9.限制結果的顯示條數
2.having與where不一樣的地方在於!!!!!!
#！！！執行優先級從高到低：where > group by > 聚合函數 > having#1. Where 是一個約束聲明，使用Where約束來自數據庫的數據，Where是在結果返回之前起作用的（先找到表，按照where的約束條件，從表(文件)中取出數據），Where中不能使用聚合函數。 #2. Having是一個過濾聲明，是在查詢返回結果集以後對查詢結果進行的過濾操作（先找到表，按照where的約束條件，從表(文件)中取出數據，然後group by分組，如果沒有group by則所有記錄整體為一組，然後執行聚合函數，然後使用having對聚合的結果進行過濾），在Having中可以使用聚合函數。 #3. having可以放到group by之後，而where只能放到group by之前#4. 在查詢過程中聚合語句(sum,min,max,avg,count)要比having子句優先執行。而where子句在查詢過程中執行優先級高於聚合語句。
驗證不同之處：
#驗證之前再次強調：執行優先級從高到低：where > group by > 聚合函數 > having select count(id) from employee where salary > 10000; #正確，分析：where先執行，後執行聚合count(id),然後select出結果 select count(id) from employee having salary > 10000;#錯誤，分析：先執行聚合count(id)，後執行having過濾，無法對id進行salary>10000的過濾
以上兩條sql的順序是：
1:找到表employee--->用where過濾---->沒有分組則默認一組執行聚合count(id)--->select執行查看組內id數目
2:找到表employee--->沒有分組則默認一組執行聚合count(id)---->having 基於上一步聚合的結果（此時只有count(id)字段了）進行salary>10000的過濾，很明顯，根本無法獲取到salary字段
其他需要註意的問題：
select post,group_concat(name) from employee group by post having salary > 10000;#錯誤，分組後無法直接取到salary字段 select post,group_concat(name) from employee group by post having avg(salary) > 10000; 正確
例子：
例子： select max(salary) from t1 where id > 2 group by depart_id having count(id) > 2; 執行順序： from t1 ——> where id >2 ——> group by depart_id ——> max(salary)和count(id) 然後才執行 having count(id) >2 最後打印 輔助理解：select 333333333 from t1 where id > 2 group by depart_id having 4 > 2;
練習：
#練習 select post,count(id),group_concat(name) from emp group by post having count(id) < 2; #可以運行 select count(id) from emp having id > 15; #運行錯誤
3.命名
命名： select post,avg(salary) as 平均工資 from emp group by post having avg(salary) > 10000; select post 崗位名,avg(salary) 平均工資 from emp group by post having avg(salary) > 10000; #命名時 as 可以省略
4.order by關鍵字
select * from emp order by salary; #默認就是升序 select * from emp order by salary asc; #升序 select * from emp order by salary desc; #降序 select * from emp order by age asc,salary desc; #先按照年齡從小到大排，如果年齡分不出勝負（即值相同）再按照salary從大到小排。
練習：
select * from emp order by age asc,hire_date desc; select post 崗位名,avg(salary) 平均工資 from emp group by post having avg(salary) > 10000 order by avg(salary) asc;
5.通過四則運算查詢：
select name, salary*12 AS Annual_salary FROM employee; select name, salary*12 Annual_salary FROM employee; select * from employee where id%2=1;
6.定義顯示格式：
1.CONCAT() 函數用於連接字符串 SELECT CONCAT(‘姓名: ‘,name,‘ 年薪: ‘, salary*12) AS Annual_salary FROM employee; mysql> SELECT CONCAT(‘姓名: ‘,name,‘ 年薪: ‘, salary*12) AS Annual_salary -> FROM emp; +---------------------------------------+ | Annual_salary | +---------------------------------------+ | 姓名: egon 年薪: 87603.96 | | 姓名: alex 年薪: 12000003.72 | | 姓名: wupeiqi 年薪: 99600.00 | | 姓名: yuanhao 年薪: 42000.00 | | 姓名: liwenzhou 年薪: 25200.00 | | 姓名: jingliyang 年薪: 108000.00 | | 姓名: jinxin 年薪: 360000.00 | | 姓名: 成龍 年薪: 120000.00 | | 姓名: 歪歪 年薪: 36001.56 | | 姓名: 丫丫 年薪: 24004.20 | | 姓名: 丁丁 年薪: 12004.44 | | 姓名: 星星 年薪: 36003.48 | | 姓名: 格格 年薪: 48003.96 | | 姓名: 張野 年薪: 120001.56 | | 姓名: 程咬金 年薪: 240000.00 | | 姓名: 程咬銀 年薪: 228000.00 | | 姓名: 程咬銅 年薪: 216000.00 | | 姓名: 程咬鐵 年薪: 204000.00 | +---------------------------------------+ 18 rows in set (0.00 sec) 2.CONCAT_WS() 第一個參數為分隔符 SELECT CONCAT_WS(‘:‘,name,salary*12) AS Annual_salary FROM employee; mysql> SELECT CONCAT_WS(‘:‘,name,salary*12) AS Annual_salary -> FROM emp; +----------------------+ | Annual_salary | +----------------------+ | egon:87603.96 | | alex:12000003.72 | | wupeiqi:99600.00 | | yuanhao:42000.00 | | liwenzhou:25200.00 | | jingliyang:108000.00 | | jinxin:360000.00 | | 成龍:120000.00 | | 歪歪:36001.56 | | 丫丫:24004.20 | | 丁丁:12004.44 | | 星星:36003.48 | | 格格:48003.96 | | 張野:120001.56 | | 程咬金:240000.00 | | 程咬銀:228000.00 | | 程咬銅:216000.00 | | 程咬鐵:204000.00 | +----------------------+ 18 rows in set (0.00 sec)
7. limit 限制查詢的記錄數
1. select * from emp limit 10; #第一條到第十條記錄
mysql> select * from emp limit 10; +----+------------+--------+-----+------------+-----------------------------------------+--------------+------------+--------+-----------+ | id | name | sex | age | hire_date | post | post_comment | salary | office | depart_id | +----+------------+--------+-----+------------+-----------------------------------------+--------------+------------+--------+-----------+ | 1 | egon | male | 18 | 2017-03-01 | 老男孩駐沙河辦事處外交大使 | NULL | 7300.33 | 401 | 1 | | 2 | alex | male | 78 | 2015-03-02 | teacher | NULL | 1000000.31 | 401 | 1 | | 3 | wupeiqi | male | 81 | 2013-03-05 | teacher | NULL | 8300.00 | 401 | 1 | | 4 | yuanhao | male | 73 | 2014-07-01 | teacher | NULL | 3500.00 | 401 | 1 | | 5 | liwenzhou | male | 28 | 2012-11-01 | teacher | NULL | 2100.00 | 401 | 1 | | 6 | jingliyang | female | 18 | 2011-02-11 | teacher | NULL | 9000.00 | 401 | 1 | | 7 | jinxin | male | 18 | 1900-03-01 | teacher | NULL | 30000.00 | 401 | 1 | | 8 | 成龍 | male | 48 | 2010-11-11 | teacher | NULL | 10000.00 | 401 | 1 | | 9 | 歪歪 | female | 48 | 2015-03-11 | sale | NULL | 3000.13 | 402 | 2 | | 10 | 丫丫 | female | 38 | 2010-11-01 | sale | NULL | 2000.35 | 402 | 2 | +----+------------+--------+-----+------------+-----------------------------------------+--------------+------------+--------+-----------+ 10 rows in set (0.00 sec)View Code
2.從哪開始，往後取幾條 第一個數字表示的是索引，第二個代表步距
select * from emp limit 0,3; #第一條開始往後三條
select * from emp limit 0,3; #第一條開始往後三條 +----+---------+------+-----+------------+-----------------------------------------+--------------+------------+--------+-----------+ | id | name | sex | age | hire_date | post | post_comment | salary | office | depart_id | +----+---------+------+-----+------------+-----------------------------------------+--------------+------------+--------+-----------+ | 1 | egon | male | 18 | 2017-03-01 | 老男孩駐沙河辦事處外交大使 | NULL | 7300.33 | 401 | 1 | | 2 | alex | male | 78 | 2015-03-02 | teacher | NULL | 1000000.31 | 401 | 1 | | 3 | wupeiqi | male | 81 | 2013-03-05 | teacher | NULL | 8300.00 | 401 | 1 | +----+---------+------+-----+------------+-----------------------------------------+--------------+------------+--------+-----------+ 3 rows in set (0.00 sec) select * from emp limit 3,3; +----+------------+--------+-----+------------+---------+--------------+---------+--------+-----------+ | id | name | sex | age | hire_date | post | post_comment | salary | office | depart_id | +----+------------+--------+-----+------------+---------+--------------+---------+--------+-----------+ | 4 | yuanhao | male | 73 | 2014-07-01 | teacher | NULL | 3500.00 | 401 | 1 | | 5 | liwenzhou | male | 28 | 2012-11-01 | teacher | NULL | 2100.00 | 401 | 1 | | 6 | jingliyang | female | 18 | 2011-02-11 | teacher | NULL | 9000.00 | 401 | 1 | +----+------------+--------+-----+------------+---------+--------------+---------+--------+-----------+ 3 rows in set (0.00 sec) select * from emp limit 6,3; +----+--------+--------+-----+------------+---------+--------------+----------+--------+-----------+ | id | name | sex | age | hire_date | post | post_comment | salary | office | depart_id | +----+--------+--------+-----+------------+---------+--------------+----------+--------+-----------+ | 7 | jinxin | male | 18 | 1900-03-01 | teacher | NULL | 30000.00 | 401 | 1 | | 8 | 成龍 | male | 48 | 2010-11-11 | teacher | NULL | 10000.00 | 401 | 1 | | 9 | 歪歪 | female | 48 | 2015-03-11 | sale | NULL | 3000.13 | 402 | 2 | +----+--------+--------+-----+------------+---------+--------------+----------+--------+-----------+ 3 rows in set (0.00 sec)View Code
8.distinct 去重
select distinct sex from emp; +--------+ | sex | +--------+ | male | | female | +--------+ 2 rows in set (0.00 sec)
9.where name 正則
SELECT * FROM employee WHERE name REGEXP ‘^ale‘; SELECT * FROM employee WHERE name REGEXP ‘on$‘; SELECT * FROM employee WHERE name REGEXP ‘m{2}‘; 小結：對字符串匹配的方式 WHERE name = ‘egon‘; WHERE name LIKE ‘yua%‘; WHERE name REGEXP ‘on$‘;
小練習：查看所有員工中名字是jin開頭，n或者g結果的員工信息
select * from employee where name regexp ‘^jin.*[gn]$‘;View Code
python-day43--單表查詢之關鍵字執行優先級（重點）