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我的回复：

oracle 的优化器 CBO optimizer 目前应该是所有 RDBMS 里最复杂的（不说是最先进的）。MYSQL 至少在优化器上还处于比较初级的阶段，虽然 MySQL 的目标可能并不希望实现非常复杂的优化器算法。其他一些东西 例如 undo 的实现等等 可能优势并不明显， 这里就不提了。

举一个例子， 都不使用索引的情况下，NO INDEX ! NO INDEX | NO INDEX !

以下数据量是一样的，机器是同一台。 Oracle 11.2.0.4 MySQL 8.0.14

都没有索引的情况下：oracle 使用 0.04 秒， MySQL 等了 10 分钟也没运行完

对于简单的 SQL 而言，差别不会有那么大。对于复杂的 SQL 而言， 能明显体现出优化器的优势。

对于拔高某个技术，没有兴趣。 所以 MYSQL 死忠请勿拍。

Oracle : 

SQL> set timing on;
SQL> SELECT c.cust_city,
  2         t.calendar_quarter_desc,
  3         SUM(s.amount_sold) sales_amount
  4    FROM sh.sales s, sh.times t, sh.customers c, sh.channels ch
  5   WHERE s.time_id = t.time_id
  6     AND s.cust_id = c.cust_id
  7     AND s.channel_id = ch.channel_id
  8     AND c.cust_state_province = 'FL'
  9     AND ch.channel_desc = 'Direct Sales'
 10     AND t.calendar_quarter_desc IN ('2000-01', '2000-02','1999-12')
 11   GROUP BY c.cust_city, t.calendar_quarter_desc;

CUST_CITY                      CALENDA SALES_AMOUNT
------------------------------ ------- ------------
Cypress Gardens                2000-01      3545.82
Candler                        2000-01      4166.32
Sanibel                        2000-02     17908.67
Ocala                          2000-02      7081.73
Molino                         2000-01     18765.25
Ocala                          2000-01      7146.73
Palmdale                       2000-02     25829.24
Palmdale                       2000-01     37793.44
Molino                         2000-02      17144.7
Saint Marks                    2000-01     55781.37
Noma                           2000-01     33572.55
Evinston                       2000-02     62657.21
Candler                        2000-02      6493.94
Winter Springs                 2000-02           20
Sugarloaf Key                  2000-01     12027.66
Saint Marks                    2000-02      48858.7
Blountstown                    2000-02     38052.58
Sugarloaf Key                  2000-02      9659.44
Cypress Gardens                2000-02      4928.93
Evinston                       2000-01     53509.69
Blountstown                    2000-01      27024.7
Sanibel                        2000-01     15870.34
Winter Springs                 2000-01        31.46
Noma                           2000-02     23903.58

已选择 24 行。

已用时间:  00: 00: 00.04

执行计划
----------------------------------------------------------
Plan hash value: 1865285285

------------------------------------------------------------------------------------------------------------
| Id  | Operation                      | Name      | Rows  | Bytes | Cost (%CPU)| Time     | Pstart| Pstop |
------------------------------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT               |           |   607 | 46132 |   955   (2)| 00:00:12 |       |       |
|   1 |  HASH GROUP BY                 |           |   607 | 46132 |   955   (2)| 00:00:12 |       |       |
|*  2 |   HASH JOIN                    |           |  2337 |   173K|   954   (2)| 00:00:12 |       |       |
|   3 |    PART JOIN FILTER CREATE     | :BF0000   |   274 |  4384 |    18   (0)| 00:00:01 |       |       |
|*  4 |     TABLE ACCESS FULL          | TIMES     |   274 |  4384 |    18   (0)| 00:00:01 |       |       |
|*  5 |    HASH JOIN                   |           | 12456 |   729K|   936   (2)| 00:00:12 |       |       |
|   6 |     MERGE JOIN CARTESIAN       |           |   383 | 14937 |   408   (1)| 00:00:05 |       |       |
|*  7 |      TABLE ACCESS FULL         | CHANNELS  |     1 |    13 |     3   (0)| 00:00:01 |       |       |
|   8 |      BUFFER SORT               |           |   383 |  9958 |   405   (1)| 00:00:05 |       |       |
|*  9 |       TABLE ACCESS FULL        | CUSTOMERS |   383 |  9958 |   405   (1)| 00:00:05 |       |       |
|  10 |     PARTITION RANGE JOIN-FILTER|           |   918K|    18M|   526   (2)| 00:00:07 |:BF0000|:BF0000|
|  11 |      TABLE ACCESS FULL         | SALES     |   918K|    18M|   526   (2)| 00:00:07 |:BF0000|:BF0000|
------------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

   2 - access("S"."TIME_ID"="T"."TIME_ID")
   4 - filter("T"."CALENDAR_QUARTER_DESC"='1999-12' OR "T"."CALENDAR_QUARTER_DESC"='2000-01' OR
              "T"."CALENDAR_QUARTER_DESC"='2000-02')
   5 - access("S"."CUST_ID"="C"."CUST_ID" AND "S"."CHANNEL_ID"="CH"."CHANNEL_ID")
   7 - filter("CH"."CHANNEL_DESC"='Direct Sales')
   9 - filter("C"."CUST_STATE_PROVINCE"='FL')


统计信息
----------------------------------------------------------
          0  recursive calls
          0  db block gets
       1726  consistent gets
          0  physical reads
          0  redo size
       1495  bytes sent via SQL*Net to client
        531  bytes received via SQL*Net from client
          3  SQL*Net roundtrips to/from client
          1  sorts (memory)
          0  sorts (disk)
         24  rows processed


SQL> select count(*) from sh.sales;

  COUNT(*)
----------
    918843

SQL> select * From v$VERSION;

BANNER
--------------------------------------------------------------------------------
Oracle Database 11g Enterprise Edition Release 11.2.0.4.0 - 64bit Production
PL/SQL Release 11.2.0.4.0 - Production
CORE    11.2.0.4.0      Production
TNS for 64-bit Windows: Version 11.2.0.4.0 - Production
NLSRTL Version 11.2.0.4.0 - Production

MySQL :

mysql> SELECT c.cust_city,
    ->        t.calendar_quarter_desc,
    ->        SUM(s.amount_sold) sales_amount
    ->   FROM sh.sales s, sh.times t, sh.customers c, sh.channels ch
    ->  WHERE s.time_id = t.time_id
    ->    AND s.cust_id = c.cust_id
    ->    AND s.channel_id = ch.channel_id
    ->    AND c.cust_state_province = 'FL'
    ->    AND ch.channel_desc = 'Direct Sales'
    ->    AND t.calendar_quarter_desc IN ('2000-01', '2000-02','1999-12')
    ->  GROUP BY c.cust_city, t.calendar_quarter_desc;


+----+-------------+-------+------------+------+---------------+------+---------+------+--------+----------+----------------------------------------------------+
| id | select_type | table | partitions | type | possible_keys | key  | key_len | ref  | rows   | filtered | Extra                                              |
+----+-------------+-------+------------+------+---------------+------+---------+------+--------+----------+----------------------------------------------------+
|  1 | SIMPLE      | ch    | NULL       | ALL  | NULL          | NULL | NULL    | NULL |      5 |    20.00 | Using where; Using temporary                       |
|  1 | SIMPLE      | t     | NULL       | ALL  | NULL          | NULL | NULL    | NULL |   1804 |    30.00 | Using where; Using join buffer (Block Nested Loop) |
|  1 | SIMPLE      | c     | NULL       | ALL  | NULL          | NULL | NULL    | NULL |  55065 |    10.00 | Using where; Using join buffer (Block Nested Loop) |
|  1 | SIMPLE      | s     | NULL       | ALL  | NULL          | NULL | NULL    | NULL | 914584 |     0.10 | Using where; Using join buffer (Block Nested Loop) |
+----+-------------+-------+------------+------+---------------+------+---------+------+--------+----------+----------------------------------------------------+



mysql> select version();
+-----------+
| version() |
+-----------+
| 8.0.14    |
+-----------+
1 row in set (0.00 sec)

mysql> select count(*) from sh.sales;
+----------+
| count(*) |
+----------+
|   918843 |
+----------+
1 row in set (0.96 sec)