我們在開發系統時,對SQL Query 總是希望能夠有效率.
了解一道SQL Query執行的細節,有助於提昇效率.
以之前介紹Sakila範例資料庫為例,我們先建立一個Saikla的user,
對Sakila有相關權限.然後登入.
首先要把這次登入的Session啟用Profile功能.
sakila@[sakila]>SET profiling=1;
Query OK, 0 rows affected (0.00 sec)
查詢 city 這個Table.
sakila@[sakila]>SELECT *
FROM city;
檢查PROFILE 裡的紀錄
sakila@[sakila]>SHOW PROFILES;
+----------+------------+-----------------------+
| Query_ID | Duration | Query |
+----------+------------+-----------------------+
| 1 | 0.00086850 | SELECT *
FROM city |
+----------+------------+-----------------------+
1 row in set (0.00 sec)
得知 Query_ID 是 1
查看相關細節.
sakila@[sakila]>SHOW PROFILE FOR QUERY 1;
+--------------------------------+----------+
| Status | Duration |
+--------------------------------+----------+
| starting | 0.000015 |
| Waiting for query cache lock | 0.000003 |
| checking query cache for query | 0.000024 |
| checking permissions | 0.000006 |
| Opening tables | 0.000022 |
| System lock | 0.000006 |
| Waiting for query cache lock | 0.000016 |
| init | 0.000011 |
| optimizing | 0.000003 |
| statistics | 0.000007 |
| preparing | 0.000005 |
| executing | 0.000002 |
| Sending data | 0.000488 |
| Waiting for query cache lock | 0.000002 |
| Sending data | 0.000234 |
| end | 0.000003 |
| query end | 0.000002 |
| closing tables | 0.000004 |
| freeing items | 0.000004 |
| Waiting for query cache lock | 0.000001 |
| freeing items | 0.000005 |
| Waiting for query cache lock | 0.000001 |
| freeing items | 0.000001 |
| storing result in query cache | 0.000002 |
| logging slow query | 0.000001 |
| cleaning up | 0.000001 |
+--------------------------------+----------+
26 rows in set (0.00 sec)
可以看到一道SQL Query 的執行細分為許多步驟,以及各個步驟的執行時間.
也可以更詳細觀察如CPU的使用情形.
sakila@[sakila]>SHOW PROFILE CPU FOR QUERY 1;
+--------------------------------+----------+----------+------------+
| Status | Duration | CPU_user | CPU_system |
+--------------------------------+----------+----------+------------+
| starting | 0.000015 | 0.000000 | 0.000000 |
| Waiting for query cache lock | 0.000003 | 0.000000 | 0.000000 |
| checking query cache for query | 0.000024 | 0.000000 | 0.000000 |
| checking permissions | 0.000006 | 0.000000 | 0.000000 |
| Opening tables | 0.000022 | 0.000000 | 0.000000 |
| System lock | 0.000006 | 0.000000 | 0.000000 |
| Waiting for query cache lock | 0.000016 | 0.000000 | 0.000000 |
| init | 0.000011 | 0.000000 | 0.000000 |
| optimizing | 0.000003 | 0.000000 | 0.000000 |
| statistics | 0.000007 | 0.000000 | 0.000000 |
| preparing | 0.000005 | 0.000000 | 0.000000 |
| executing | 0.000002 | 0.000000 | 0.000000 |
| Sending data | 0.000488 | 0.000000 | 0.000000 |
| Waiting for query cache lock | 0.000002 | 0.000000 | 0.000000 |
| Sending data | 0.000234 | 0.000000 | 0.000000 |
| end | 0.000003 | 0.000000 | 0.000000 |
| query end | 0.000002 | 0.000000 | 0.000000 |
| closing tables | 0.000004 | 0.000000 | 0.000000 |
| freeing items | 0.000004 | 0.000000 | 0.000000 |
| Waiting for query cache lock | 0.000001 | 0.000000 | 0.000000 |
| freeing items | 0.000005 | 0.000000 | 0.000000 |
| Waiting for query cache lock | 0.000001 | 0.000000 | 0.000000 |
| freeing items | 0.000001 | 0.000000 | 0.000000 |
| storing result in query cache | 0.000002 | 0.000000 | 0.000000 |
| logging slow query | 0.000001 | 0.000000 | 0.000000 |
| cleaning up | 0.000001 | 0.000000 | 0.000000 |
+--------------------------------+----------+----------+------------+
26 rows in set (0.00 sec)
這個Table 很小,CPU耗用的時間很少,所以變成在小數點後面很遠了,顯示出來就看不到了.
我們換查詢一下 VIEW.
登出後將MySQL 重開,再登入,前面步驟省略.
sakila@[sakila]>SHOW PROFILES;
+----------+------------+------------------------------------------+
| Query_ID | Duration | Query |
+----------+------------+------------------------------------------+
| 1 | 0.04519025 | SELECT * FROM nicer_but_slower_film_list |
+----------+------------+------------------------------------------+
查看細節.
sakila@[sakila]>SHOW PROFILE CPU FOR QUERY 1;
+--------------------------------+----------+----------+------------+
| Status | Duration | CPU_user | CPU_system |
+--------------------------------+----------+----------+------------+
| starting | 0.000016 | 0.000000 | 0.000000 |
| Waiting for query cache lock | 0.000002 | 0.000000 | 0.000000 |
| checking query cache for query | 0.000024 | 0.000000 | 0.000000 |
| checking permissions | 0.000006 | 0.000000 | 0.000000 |
| Opening tables | 0.000166 | 0.000000 | 0.000000 |
| System lock | 0.000012 | 0.000000 | 0.000000 |
| checking permissions | 0.000002 | 0.000000 | 0.000000 |
| checking permissions | 0.000001 | 0.000000 | 0.000000 |
| checking permissions | 0.000001 | 0.000000 | 0.000000 |
| checking permissions | 0.000001 | 0.000000 | 0.000000 |
| checking permissions | 0.000202 | 0.000000 | 0.000000 |
| optimizing | 0.000019 | 0.000000 | 0.000000 |
| statistics | 0.000055 | 0.000000 | 0.000000 |
| preparing | 0.000019 | 0.000000 | 0.000000 |
| Creating tmp table | 0.000132 | 0.000000 | 0.000000 |
| executing | 0.000002 | 0.000000 | 0.000000 |
| Copying to tmp table | 0.026277 | 0.019997 | 0.005999 |
| Sorting result | 0.003313 | 0.002000 | 0.001000 |
| Sending data | 0.011883 | 0.003999 | 0.007999 |
| removing tmp table | 0.001509 | 0.000000 | 0.000999 |
| Sending data | 0.000005 | 0.000000 | 0.000000 |
| Waiting for query cache lock | 0.000002 | 0.000000 | 0.000000 |
| Sending data | 0.000028 | 0.000000 | 0.000000 |
| init | 0.000013 | 0.000000 | 0.000000 |
| optimizing | 0.000003 | 0.000000 | 0.000000 |
| statistics | 0.000007 | 0.000000 | 0.000000 |
| preparing | 0.000005 | 0.000000 | 0.000000 |
| executing | 0.000001 | 0.000000 | 0.000000 |
| Sending data | 0.000100 | 0.000000 | 0.000000 |
| Waiting for query cache lock | 0.000002 | 0.000000 | 0.000000 |
| Sending data | 0.000102 | 0.001000 | 0.000000 |
| Waiting for query cache lock | 0.000002 | 0.000000 | 0.000000 |
| Sending data | 0.000072 | 0.000000 | 0.000000 |
| Waiting for query cache lock | 0.000001 | 0.000000 | 0.000000 |
| Sending data | 0.000092 | 0.000000 | 0.000000 |
| Waiting for query cache lock | 0.000002 | 0.000000 | 0.000000 |
| Sending data | 0.000075 | 0.000000 | 0.000000 |
| Waiting for query cache lock | 0.000001 | 0.000000 | 0.000000 |
| Sending data | 0.000118 | 0.000000 | 0.000000 |
| Waiting for query cache lock | 0.000002 | 0.000000 | 0.000000 |
| Sending data | 0.000106 | 0.000000 | 0.000000 |
| Waiting for query cache lock | 0.000002 | 0.000000 | 0.000000 |
| Sending data | 0.000090 | 0.000000 | 0.000000 |
| Waiting for query cache lock | 0.000001 | 0.000000 | 0.000000 |
| Sending data | 0.000096 | 0.000000 | 0.000000 |
| Waiting for query cache lock | 0.000002 | 0.000000 | 0.000000 |
| Sending data | 0.000070 | 0.000000 | 0.000000 |
| Waiting for query cache lock | 0.000002 | 0.000000 | 0.000000 |
| Sending data | 0.000089 | 0.000000 | 0.000000 |
| Waiting for query cache lock | 0.000002 | 0.000000 | 0.000000 |
| Sending data | 0.000084 | 0.000000 | 0.000000 |
| Waiting for query cache lock | 0.000002 | 0.000000 | 0.000000 |
| Sending data | 0.000082 | 0.001000 | 0.000000 |
| Waiting for query cache lock | 0.000001 | 0.000000 | 0.000000 |
| Sending data | 0.000043 | 0.000000 | 0.000000 |
| end | 0.000003 | 0.000000 | 0.000000 |
| query end | 0.000003 | 0.000000 | 0.000000 |
| closing tables | 0.000001 | 0.000000 | 0.000000 |
| removing tmp table | 0.000199 | 0.000000 | 0.000000 |
| closing tables | 0.000015 | 0.000000 | 0.000000 |
| freeing items | 0.000007 | 0.000000 | 0.000000 |
| removing tmp table | 0.000004 | 0.000000 | 0.000000 |
| freeing items | 0.000005 | 0.000000 | 0.000000 |
| Waiting for query cache lock | 0.000001 | 0.000000 | 0.000000 |
| freeing items | 0.000008 | 0.000000 | 0.000000 |
| Waiting for query cache lock | 0.000001 | 0.000000 | 0.000000 |
| freeing items | 0.000001 | 0.000000 | 0.000000 |
| storing result in query cache | 0.000002 | 0.000000 | 0.000000 |
| logging slow query | 0.000001 | 0.000000 | 0.000000 |
| cleaning up | 0.000002 | 0.000000 | 0.000000 |
+--------------------------------+----------+----------+------------+
70 rows in set (0.00 sec)
可以發現步驟變多了,既要檢查權限,也要產生暫存表,最後還要清除暫存表等等.
請問如何對MS SQL 也做相同的測試?
wilson1966提到：
請問如何對MS SQL 也做相同的測試?
SQL Server 也是一門很深的學問,待敝人先把MySQL鐵人賽的部份完成.再把對SQL Server一些粗淺的研究心得與大家分享.
感謝您的關注.
iThome鐵人賽
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