SELECT DISTINCT <select_list> FROM <left_table> <join_type> JOIN <right_table> ON <join_condition> WHERE <where_condition> GROUP BY <group_by_list> HAVING <having_condition> ORDER BY <order_by_condition> LIMIT <limit_number>
(7) SELECT (8) DISTINCT <select_list> (1) FROM <left_table> (3) <join_type> JOIN <right_table> (2) ON <join_condition> (4) WHERE <where_condition> (5) GROUP BY <group_by_list> (6) HAVING <having_condition> (9) ORDER BY <order_by_condition> (10) LIMIT <limit_number>
\1. 新建一個測試數據庫TestDB;mysql
create database TestDB;
2.建立測試表table1和table2;sql
CREATE TABLE table1 ( customer_id VARCHAR(10) NOT NULL, city VARCHAR(10) NOT NULL, PRIMARY KEY(customer_id) )ENGINE=INNODB DEFAULT CHARSET=UTF8; CREATE TABLE table2 ( order_id INT NOT NULL auto_increment, customer_id VARCHAR(10), PRIMARY KEY(order_id) )ENGINE=INNODB DEFAULT CHARSET=UTF8;
3.插入測試數據;數據庫
INSERT INTO table1(customer_id,city) VALUES('163','hangzhou'); INSERT INTO table1(customer_id,city) VALUES('9you','shanghai'); INSERT INTO table1(customer_id,city) VALUES('tx','hangzhou'); INSERT INTO table1(customer_id,city) VALUES('baidu','hangzhou'); INSERT INTO table2(customer_id) VALUES('163'); INSERT INTO table2(customer_id) VALUES('163'); INSERT INTO table2(customer_id) VALUES('9you'); INSERT INTO table2(customer_id) VALUES('9you'); INSERT INTO table2(customer_id) VALUES('9you'); INSERT INTO table2(customer_id) VALUES('tx'); INSERT INTO table2(customer_id) VALUES(NULL);
準備工做作完之後,table1和table2看起來應該像下面這樣緩存
mysql> select * from table1; +-------------+----------+ | customer_id | city | +-------------+----------+ | 163 | hangzhou | | 9you | shanghai | | baidu | hangzhou | | tx | hangzhou | +-------------+----------+ 4 rows in set (0.00 sec) mysql> select * from table2; +----------+-------------+ | order_id | customer_id | +----------+-------------+ | 1 | 163 | | 2 | 163 | | 3 | 9you | | 4 | 9you | | 5 | 9you | | 6 | tx | | 7 | NULL | +----------+-------------+ 7 rows in set (0.00 sec)
#查詢來自杭州,而且訂單數少於2的客戶。 SELECT a.customer_id, COUNT(b.order_id) as total_orders FROM table1 AS a LEFT JOIN table2 AS b ON a.customer_id = b.customer_id WHERE a.city = 'hangzhou' GROUP BY a.customer_id HAVING count(b.order_id) < 2 ORDER BY total_orders DESC;
在這些SQL語句的執行過程當中,都會產生一個虛擬表,用來保存SQL語句的執行結果(這是重點),我如今就來跟蹤這個虛擬表的變化,獲得最終的查詢結果的過程,來分析整個SQL邏輯查詢的執行順序和過程。測試
執行FROM語句大數據
第一步,執行FROM語句。咱們首先須要知道最開始從哪一個表開始的,這就是FROM告訴咱們的。如今有了
關於什麼是笛卡爾積,請自行Google補腦。通過FROM語句對兩個表執行笛卡爾積,會獲得一個虛擬表,暫且叫VT1(vitual table 1),內容以下:排序
+-------------+----------+----------+-------------+ | customer_id | city | order_id | customer_id | +-------------+----------+----------+-------------+ | 163 | hangzhou | 1 | 163 | | 9you | shanghai | 1 | 163 | | baidu | hangzhou | 1 | 163 | | tx | hangzhou | 1 | 163 | | 163 | hangzhou | 2 | 163 | | 9you | shanghai | 2 | 163 | | baidu | hangzhou | 2 | 163 | | tx | hangzhou | 2 | 163 | | 163 | hangzhou | 3 | 9you | | 9you | shanghai | 3 | 9you | | baidu | hangzhou | 3 | 9you | | tx | hangzhou | 3 | 9you | | 163 | hangzhou | 4 | 9you | | 9you | shanghai | 4 | 9you | | baidu | hangzhou | 4 | 9you | | tx | hangzhou | 4 | 9you | | 163 | hangzhou | 5 | 9you | | 9you | shanghai | 5 | 9you | | baidu | hangzhou | 5 | 9you | | tx | hangzhou | 5 | 9you | | 163 | hangzhou | 6 | tx | | 9you | shanghai | 6 | tx | | baidu | hangzhou | 6 | tx | | tx | hangzhou | 6 | tx | | 163 | hangzhou | 7 | NULL | | 9you | shanghai | 7 | NULL | | baidu | hangzhou | 7 | NULL | | tx | hangzhou | 7 | NULL | +-------------+----------+----------+-------------+
總共有28(table1的記錄條數 * table2的記錄條數)條記錄。這就是VT1的結果,接下來的操做就在VT1的基礎上進行。索引
執行ON過濾內存
執行完笛卡爾積之後,接着就進行ON a.customer_id = b.customer_id條件過濾,根據ON中指定的條件,去掉那些不符合條件的數據,獲得VT2表,內容以下:
+-------------+----------+----------+-------------+ | customer_id | city | order_id | customer_id | +-------------+----------+----------+-------------+ | 163 | hangzhou | 1 | 163 | | 163 | hangzhou | 2 | 163 | | 9you | shanghai | 3 | 9you | | 9you | shanghai | 4 | 9you | | 9you | shanghai | 5 | 9you | | tx | hangzhou | 6 | tx | +-------------+----------+----------+-------------+
VT2就是通過ON條件篩選之後獲得的有用數據,而接下來的操做將在VT2的基礎上繼續進行。
添加外部行
這一步只有在鏈接類型爲OUTER JOIN時才發生,如LEFT OUTER JOIN、RIGHT OUTER JOIN和FULL OUTER JOIN。在大多數的時候,咱們都是會省略掉OUTER關鍵字的,但OUTER表示的就是外部行的概念。
LEFT OUTER JOIN把左表記爲保留表,獲得的結果爲:
+-------------+----------+----------+-------------+ | customer_id | city | order_id | customer_id | +-------------+----------+----------+-------------+ | 163 | hangzhou | 1 | 163 | | 163 | hangzhou | 2 | 163 | | 9you | shanghai | 3 | 9you | | 9you | shanghai | 4 | 9you | | 9you | shanghai | 5 | 9you | | tx | hangzhou | 6 | tx | | baidu | hangzhou | NULL | NULL | +-------------+----------+----------+-------------+
RIGHT OUTER JOIN把右表記爲保留表,獲得的結果爲:
+-------------+----------+----------+-------------+ | customer_id | city | order_id | customer_id | +-------------+----------+----------+-------------+ | 163 | hangzhou | 1 | 163 | | 163 | hangzhou | 2 | 163 | | 9you | shanghai | 3 | 9you | | 9you | shanghai | 4 | 9you | | 9you | shanghai | 5 | 9you | | tx | hangzhou | 6 | tx | | NULL | NULL | 7 | NULL | +-------------+----------+----------+-------------+
FULL OUTER JOIN把左右表都做爲保留表,獲得的結果爲:
+-------------+----------+----------+-------------+ | customer_id | city | order_id | customer_id | +-------------+----------+----------+-------------+ | 163 | hangzhou | 1 | 163 | | 163 | hangzhou | 2 | 163 | | 9you | shanghai | 3 | 9you | | 9you | shanghai | 4 | 9you | | 9you | shanghai | 5 | 9you | | tx | hangzhou | 6 | tx | | baidu | hangzhou | NULL | NULL | | NULL | NULL | 7 | NULL | +-------------+----------+----------+-------------+
添加外部行的工做就是在VT2表的基礎上添加保留表中被過濾條件過濾掉的數據,非保留表中的數據被賦予NULL值,最後生成虛擬表VT3。
因爲我在準備的測試SQL查詢邏輯語句中使用的是LEFT JOIN,過濾掉了如下這條數據:
| baidu | hangzhou | NULL | NULL |
如今就把這條數據添加到VT2表中,獲得的VT3表以下:
+-------------+----------+----------+-------------+ | customer_id | city | order_id | customer_id | +-------------+----------+----------+-------------+ | 163 | hangzhou | 1 | 163 | | 163 | hangzhou | 2 | 163 | | 9you | shanghai | 3 | 9you | | 9you | shanghai | 4 | 9you | | 9you | shanghai | 5 | 9you | | tx | hangzhou | 6 | tx | | baidu | hangzhou | NULL | NULL | +-------------+----------+----------+-------------+
接下來的操做都會在該VT3表上進行。
執行WHERE過濾
對添加外部行獲得的VT3進行WHERE過濾,只有符合
+-------------+----------+----------+-------------+ | customer_id | city | order_id | customer_id | +-------------+----------+----------+-------------+ | 163 | hangzhou | 1 | 163 | | 163 | hangzhou | 2 | 163 | | tx | hangzhou | 6 | tx | | baidu | hangzhou | NULL | NULL | +-------------+----------+----------+-------------+
可是在使用WHERE子句時,須要注意如下兩點:
where_condition=MIN(col)
這類對分組統計的過濾;SELECT city as c FROM t WHERE c='shanghai';
是不容許出現的。執行GROUP BY分組
GROU BY子句主要是對使用WHERE子句獲得的虛擬表進行分組操做。咱們執行測試語句中的GROUP BY a.customer_id,就會獲得如下內容(默認只顯示組內第一條):
+-------------+----------+----------+-------------+ | customer_id | city | order_id | customer_id | +-------------+----------+----------+-------------+ | 163 | hangzhou | 1 | 163 | | baidu | hangzhou | NULL | NULL | | tx | hangzhou | 6 | tx | +-------------+----------+----------+-------------+
獲得的內容會存入虛擬表VT5中,此時,咱們就獲得了一個VT5虛擬表,接下來的操做都會在該表上完成。
執行HAVING過濾
HAVING子句主要和GROUP BY子句配合使用,對分組獲得的VT5虛擬表進行條件過濾。當我執行測試語句中的HAVING count(b.order_id) < 2時,將獲得如下內容:
+-------------+----------+----------+-------------+ | customer_id | city | order_id | customer_id | +-------------+----------+----------+-------------+ | baidu | hangzhou | NULL | NULL | | tx | hangzhou | 6 | tx | +-------------+----------+----------+-------------+
這就是虛擬表VT6。
SELECT列表
如今纔會執行到SELECT子句,不要覺得SELECT子句被寫在第一行,就是第一個被執行的。
咱們執行測試語句中的SELECT a.customer_id, COUNT(b.order_id) as total_orders,從虛擬表VT6中選擇出咱們須要的內容。咱們將獲得如下內容:
+-------------+--------------+ | customer_id | total_orders | +-------------+--------------+ | baidu | 0 | | tx | 1 | +-------------+--------------+
尚未完,這只是虛擬表VT7。
執行DISTINCT子句
若是在查詢中指定了DISTINCT子句,則會建立一張內存臨時表(若是內存放不下,就須要存放在硬盤了)。這張臨時表的表結構和上一步產生的虛擬表VT7是同樣的,不一樣的是對進行DISTINCT操做的列增長了一個惟一索引,以此來除重複數據。
因爲個人測試SQL語句中並無使用DISTINCT,因此,在該查詢中,這一步不會生成一個虛擬表。
執行ORDER BY子句
對虛擬表中的內容按照指定的列進行排序,而後返回一個新的虛擬表,咱們執行測試SQL語句中的ORDER BY total_orders DESC,就會獲得如下內容:
+-------------+--------------+ | customer_id | total_orders | +-------------+--------------+ | tx | 1 | | baidu | 0 | +-------------+--------------+
能夠看到這是對total_orders列進行降序排列的。上述結果會存儲在VT8中。
執行LIMIT子句
LIMIT子句從上一步獲得的VT8虛擬表中選出從指定位置開始的指定行數據。對於沒有應用ORDER BY的LIMIT子句,獲得的結果一樣是無序的,因此,不少時候,咱們都會看到LIMIT子句會和ORDER BY子句一塊兒使用。
MySQL數據庫的LIMIT支持以下形式的選擇:
LIMIT n, m
表示從第n條記錄開始選擇m條記錄。而不少開發人員喜歡使用該語句來解決分頁問題。對於小數據,使用LIMIT子句沒有任何問題,當數據量很是大的時候,使用LIMIT n, m是很是低效的。由於LIMIT的機制是每次都是從頭開始掃描,若是須要從第60萬行開始,讀取3條數據,就須要先掃描定位到60萬行,而後再進行讀取,而掃描的過程是一個很是低效的過程。因此,對於大數據處理時,是很是有必要在應用層創建必定的緩存機制(如今的大數據處理,大都使用緩存)