docs：MySQL执行计划分析新增测试案例

Author: Snailclimb

docs/database/mysql/mysql-query-execution-plan.md

@@ -29,13 +29,33 @@ MySQL 为我们提供了 `EXPLAIN` 命令，来获取执行计划的相关信息
 MySQL 8.0.18 引入了 `EXPLAIN ANALYZE`，它会**真正执行**查询并输出每个步骤的实际耗时与行数，比标准 `EXPLAIN` 的估算数据更可靠，适合在测试环境深度排查慢查询：
 
 ```sql
-EXPLAIN ANALYZE SELECT * FROM dept_emp WHERE emp_no = 10001;
+mysql> EXPLAIN ANALYZE SELECT * FROM users WHERE age = 25\G
+*************************** 1. row ***************************
+EXPLAIN: -> Covering index lookup on users using idx_age_score_name (age=25)
+(cost=1.52 rows=12) (actual time=0.0272..0.0344 rows=12 loops=1)
 ```
 
 此外，`EXPLAIN FORMAT=JSON` 可以输出优化器的成本模型数据（`query_cost`），比表格形式更能反映各步骤的实际代价，在多表 JOIN 或子查询调优时尤为有用：
 
 ```sql
-EXPLAIN FORMAT=JSON SELECT * FROM dept_emp WHERE emp_no = 10001;
+mysql> EXPLAIN FORMAT=JSON SELECT * FROM users WHERE age = 25\G
+*************************** 1. row ***************************
+EXPLAIN: {
+  "query_block": {
+    "select_id": 1,
+    "cost_info": {
+      "query_cost": "1.52"
+    },
+    "table": {
+      "table_name": "users",
+      "access_type": "ref",
+      "key": "idx_age_score_name",
+      "rows_examined_per_scan": 12,
+      "filtered": "100.00",
+      "using_index": true
+    }
+  }
+}
 ```
 
 `EXPLAIN` 执行计划支持 `SELECT`、`DELETE`、`INSERT`、`REPLACE` 以及 `UPDATE` 语句。我们一般多用于分析 `SELECT` 查询语句，使用起来非常简单，语法如下：
@@ -46,14 +66,29 @@ EXPLAIN SELECT 查询语句；
 
 我们简单来看下一条查询语句的执行计划：
 
+**示例 1：单表查询（使用索引）**
+
+```sql
+-- 表结构：users(id, age, score, name, address)，联合索引 idx_age_score_name(age, score, name)
+mysql> EXPLAIN SELECT * FROM users WHERE age = 25;
++----+-------------+-------+------------+------+---------------------+---------------------+---------+-------+------+----------+-------------+
+| id | select_type | table | partitions | type | possible_keys       | key                 | key_len | ref   | rows | filtered | Extra       |
++----+-------------+-------+------------+------+---------------------+---------------------+---------+-------+------+----------+-------------+
+|  1 | SIMPLE      | users | NULL       | ref  | idx_age_score_name  | idx_age_score_name  | 5       | const |   12 |   100.00 | Using index |
++----+-------------+-------+------------+------+---------------------+---------------------+---------+-------+------+----------+-------------+
+```
+
+**示例 2：UNION 查询（id 为 NULL 的场景）**
+
 ```sql
-mysql> explain SELECT * FROM dept_emp WHERE emp_no IN (SELECT emp_no FROM dept_emp GROUP BY emp_no HAVING COUNT(emp_no)>1);
-+----+-------------+----------+------------+-------+-----------------+---------+---------+------+--------+----------+-------------+
-| id | select_type | table    | partitions | type  | possible_keys   | key     | key_len | ref  | rows   | filtered | Extra       |
-+----+-------------+----------+------------+-------+-----------------+---------+---------+------+--------+----------+-------------+
-|  1 | PRIMARY     | dept_emp | NULL       | ALL   | NULL            | NULL    | NULL    | NULL | 331143 |   100.00 | Using where |
-|  2 | SUBQUERY    | dept_emp | NULL       | index | PRIMARY,dept_no | PRIMARY | 16      | NULL | 331143 |   100.00 | Using index |
-+----+-------------+----------+------------+-------+-----------------+---------+---------+------+--------+----------+-------------+
+mysql> EXPLAIN SELECT * FROM users WHERE id = 1 UNION SELECT * FROM users WHERE id = 2;
++----+--------------+------------+------------+-------+---------------+---------+---------+-------+------+----------+-------+
+| id | select_type  | table      | partitions | type  | possible_keys | key     | key_len | ref   | rows | filtered | Extra |
++----+--------------+------------+------------+-------+---------------+---------+---------+-------+------+----------+-------+
+|  1 | PRIMARY      | users      | NULL       | const | PRIMARY       | PRIMARY | 4       | const |    1 |   100.00 | NULL  |
+|  2 | UNION        | users      | NULL       | const | PRIMARY       | PRIMARY | 4       | const |    1 |   100.00 | NULL  |
+|  3 | UNION RESULT | <union1,2> | NULL       | ALL   | NULL          | NULL    | NULL    | NULL  | NULL |     NULL | Using temporary |
++----+--------------+------------+------------+-------+---------------+---------+---------+-------+------+----------+-------+
 ```
 
 可以看到，执行计划结果中共有 12 列，各列代表的含义总结如下表：
@@ -90,12 +125,28 @@ mysql> explain SELECT * FROM dept_emp WHERE emp_no IN (SELECT emp_no FROM dept_e
 **示例**：
 
 ```sql
-EXPLAIN SELECT * FROM dept_emp WHERE emp_no = 10001
-UNION
-SELECT * FROM dept_emp WHERE dept_no = 'd001';
+mysql> EXPLAIN SELECT * FROM users WHERE id = 1
+    -> UNION
+    -> SELECT * FROM users WHERE id = 2\G
+*************************** 1. row ***************************
+           id: 1
+  select_type: PRIMARY
+        table: users
+         type: const
+*************************** 2. row ***************************
+           id: 2
+  select_type: UNION
+        table: users
+         type: const
+*************************** 3. row ***************************
+           id: NULL
+  select_type: UNION RESULT
+        table: <union1,2>
+         type: ALL
+        Extra: Using temporary
 ```
 
-输出中最后一行的 `id = NULL`，table = `<union1,2>`，表示这是前两个查询结果的合并。
+第三行的 `id = NULL`，table = `<union1,2>`，表示这是前两个查询结果的合并。
 
 ### select_type
 
@@ -180,10 +231,16 @@ rows 列表示根据表统计信息及索引选用情况，**估算**出找到
 
 ```sql
 -- 执行计划估算行数
-EXPLAIN SELECT * FROM dept_emp WHERE emp_no = 10001;
+mysql> EXPLAIN SELECT * FROM users WHERE age = 25\G
+rows: 12
 
 -- 实际行数（注意：在大表上慎用 COUNT(*)）
-SELECT COUNT(*) FROM dept_emp WHERE emp_no = 10001;
+mysql> SELECT COUNT(*) FROM users WHERE age = 25;
++----------+
+| COUNT(*) |
++----------+
+|       12 |
++----------+
 ```
 
 遇到执行计划与实际性能不符时，可以执行 `ANALYZE TABLE` 重新采样，再观察执行计划的变化。