【GreatSQL优化器-06】条件过滤导致选择非最佳

一、condition_fanout_filter导致计划非最佳

GreatSQL 的优化器对于 join 的表需要根据行数和 cost 来确定最后哪张表先执行哪张表后执行，这里面就涉及到预估满足条件的表数据，condition_fanout_filter会根据一系列方法计算出一个数据过滤百分比，这个比百分比就是 filtered 系数，这个值区间在[0,1]，值越小代表过滤效果越好。用这个系数乘以总的行数就可以得出最后需要扫描的表行数的数量，可以大幅节省开销和执行时间。

这个功能是由OPTIMIZER_SWITCH_COND_FANOUT_FILTER这个OPTIMIZER_SWITCH来控制的，默认是打开的。因此一般情况下不需要特意去关闭，但是如果遇到执行特别慢的一些情况可以考虑关闭。

下面用一个例子来说明condition_fanout_filter有可能导致选择错误的情况：

# 创建2张表，都只在第二列创建索引，其中t3的最后一列也创建一个索引。
CREATE TABLE t3 (ccc1 INT, ccc2 int,ccc3 datetime(6));
INSERT INTO t3 VALUES (1,2,'2021-03-25 16:44:00.123456'),(2,10,'2021-03-25 16:44:00.123456'),(3,4,'2022-03-25 16:44:00.123456'),(4,6,'2023-03-25 16:44:00.123456'),(null,7,'2024-03-25 16:44:00.123456'),(4,3,'2024-04-25 16:44:00.123456'),(null,8,'2025-03-25 16:44:00.123456'),(3,4,'2022-06-25 16:44:00.123456'),(5,4,'2021-11-25 16:44:00.123456');
CREATE TABLE t4 (d1 INT, d2 int, d3 varchar(100));
INSERT INTO t4 VALUES (1,2,'aa1'),(2,1,'bb1'),(2,3,'cc1'),(3,3,'cc1'),(4,2,'ff1'),(4,4,'ert'),(4,2,'f5fg'),(null,2,'ee'),(5,30,'cc1'),(5,4,'fcc1'),(4,10,'cc1'),(6,4,'ccd1'),(null,1,'fee'),(1,2,'aa1'),(2,1,'bb1'),(2,3,'cc1'),(3,3,'cc1'),(4,2,'ff1'),(4,4,'ert'),(4,2,'f5fg'),(null,2,'ee'),(5,30,'cc1'),(5,4,'fcc1'),(4,10,'cc1'),(6,4,'ccd1'),(null,1,'fee'),(1,2,'aa1'),(2,1,'bb1'),(2,3,'cc1'),(3,3,'cc1'),(4,2,'ff1'),(4,4,'ert'),(4,2,'f5fg'),(null,2,'ee'),(5,30,'cc1'),(5,4,'fcc1'),(4,10,'cc1'),(6,4,'ccd1'),(null,1,'fee');
CREATE INDEX idx3_2 ON t3(ccc2);
CREATE INDEX idx3_3 ON t3(ccc3);
CREATE INDEX idx4_2 ON t4(d2);

执行一个join命令，where条件涉及的列不含t4的索引列，但是包含t3的索引列。
首先查看条件过滤开启的情况，结果是t4先执行全表扫描，预估的扫描行数为39 * 33.33%=13行，而t3执行ref索引扫描，行数为1 * 11.11%=0.1行，总行数为2行

greatsql> EXPLAIN SELECT * FROM t4 join t3 ON t4.d1=t3.ccc1 and t4.d2=t3.ccc2 where t4.d1<5 and t3.ccc3 < '2023-11-15';
+----+-------------+-------+------------+------+---------------+--------+---------+-----------+------+----------+-------------+
| id | select_type | table | partitions | type | possible_keys | key    | key_len | ref       | rows | filtered | Extra       |
+----+-------------+-------+------------+------+---------------+--------+---------+-----------+------+----------+-------------+
|  1 | SIMPLE      | t4    | NULL       | ALL  | idx4_2        | NULL   | NULL    | NULL      |   39 |    33.33 | Using where |
|  1 | SIMPLE      | t3    | NULL       | ref  | idx3_2,idx3_3 | idx3_2 | 5       | db1.t4.d2 |    1 |    11.11 | Using where |
+----+-------------+-------+------------+------+---------------+--------+---------+-----------+------+----------+-------------+

接着查看条件过滤关闭的情况，结果是t3先执行范围扫描，预估的扫描行数为6 * 100%=6行，而t4执行ref索引扫描，行数为6 * 100%=6行，总行数为39行。

greatsql> EXPLAIN SELECT /*+ set_var(optimizer_switch='condition_fanout_filter=off') */ * FROM t4 join t3 ON t4.d1=t3.ccc1 and t4.d2=t3.ccc2 where t4.d1<5 and t3.ccc3 < '2023-11-15';
+----+-------------+-------+------------+-------+---------------+--------+---------+-------------+------+----------+------------------------------------+
| id | select_type | table | partitions | type  | possible_keys | key    | key_len | ref         | rows | filtered | Extra                              |
+----+-------------+-------+------------+-------+---------------+--------+---------+-------------+------+----------+------------------------------------+
|  1 | SIMPLE      | t3    | NULL       | range | idx3_2,idx3_3 | idx3_3 | 9       | NULL        |    6 |   100.00 | Using index condition; Using where |
|  1 | SIMPLE      | t4    | NULL       | ref   | idx4_2        | idx4_2 | 5       | db1.t3.ccc2 |    6 |   100.00 | Using where                        |
+----+-------------+-------+------------+-------+---------------+--------+---------+-------------+------+----------+------------------------------------+

接下来关掉condition_fanout_filter然后强制用t4 & t3来连接，对比一下计算出来的cost实际达到多少。从下面2个结果可以看出，t4走了全表扫描实际的cost达到21.70，是估计值的2倍多。

greatsql> EXPLAIN FORMAT=TREE SELECT * FROM t4 join t3 ON t4.d1=t3.ccc1 and t4.d2=t3.ccc2 where t4.d1<5 and t3.ccc3 < '2023-11-15';
+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| EXPLAIN                                                                                                                                                                                                                                                                                                                                                        |
+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| -> Nested loop inner join  (cost=10.00 rows=2)
    -> Filter: ((t4.d1 < 5) and (t4.d2 is not null))  (cost=4.15 rows=13)
        -> Table scan on t4  (cost=4.15 rows=39)
    -> Filter: ((t3.ccc1 = t4.d1) and (t3.ccc3 < TIMESTAMP'2023-11-15 00:00:00'))  (cost=0.32 rows=0.1)
        -> Index lookup on t3 using idx3_2 (ccc2=t4.d2)  (cost=0.32 rows=1)
 |
+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+

greatsql> EXPLAIN FORMAT=TREE SELECT /*+ set_var(optimizer_switch='condition_fanout_filter=off') qb_name(qb1) JOIN_ORDER(@qb1 t4,t3) */ * FROM t4 join t3 ON t4.d1=t3.ccc1 and t4.d2=t3.ccc2 where t4.d1<5 and t3.ccc3 < '2023-11-15';
+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| EXPLAIN                                                                                                                                                                                                                                                                                                                                                       |
+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| -> Nested loop inner join  (cost=21.70 rows=50)
    -> Filter: ((t4.d1 < 5) and (t4.d2 is not null))  (cost=4.15 rows=39)
        -> Table scan on t4  (cost=4.15 rows=39)
    -> Filter: ((t3.ccc1 = t4.d1) and (t3.ccc3 < TIMESTAMP'2023-11-15 00:00:00'))  (cost=0.32 rows=1)
        -> Index lookup on t3 using idx3_2 (ccc2=t4.d2)  (cost=0.32 rows=1)
 |
+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+

以上例子因为condition_fanout_filter的设置不同而导致选择了不同的驱动表，最后的扫描行为也不一样。但是明显先执行t3的索引范围扫描比t4的全表扫描效率高，因此这个例子可以看出condition_fanout_filter的预估过滤百分比有更多主观性，最终可能导致错误的优化路径。

附表：join_type访问方法的类型

以上各类扫描方式由快到慢排序为：system > const > eq_ref > ref > range > index > ALL

二、不关condition_fanout_filter的解决办法

如果不关闭condition_fanout_filter有没有办法强制指定连接顺序呢？答案是有的。一共如下3个方法，可以按照自己的需要进行灵活操作。

1、使用 qb_name 提示词来指定连接顺序

greatsql> EXPLAIN SELECT /*+ qb_name(qb1) JOIN_ORDER(@qb1 t3,t4) */ * FROM t4 join t3 ON t4.d1=t3.ccc1 and t4.d2=t3.ccc2 where t4.d1<5 and t3.ccc3 < '2023-11-15';
+----+-------------+-------+------------+-------+---------------+--------+---------+-------------+------+----------+------------------------------------+
| id | select_type | table | partitions | type  | possible_keys | key    | key_len | ref         | rows | filtered | Extra                              |
+----+-------------+-------+------------+-------+---------------+--------+---------+-------------+------+----------+------------------------------------+
|  1 | SIMPLE      | t3    | NULL       | range | idx3_2,idx3_3 | idx3_3 | 9       | NULL        |    6 |   100.00 | Using index condition; Using where |
|  1 | SIMPLE      | t4    | NULL       | ref   | idx4_2        | idx4_2 | 5       | db1.t3.ccc2 |    6 |     3.33 | Using where                        |
+----+-------------+-------+------------+-------+---------------+--------+---------+-------------+------+----------+------------------------------------+

2、在所有 WHERE 条件列上建立索引

greatsql> CREATE INDEX idx4_1 ON t4(d1);

greatsql> EXPLAIN SELECT * FROM t4 join t3 ON t4.d1=t3.ccc1 and t4.d2=t3.ccc2 where t4.d1<5 and t3.ccc3 < '2023-11-15';
+----+-------------+-------+------------+-------+---------------+--------+---------+-------------+------+----------+------------------------------------+
| id | select_type | table | partitions | type  | possible_keys | key    | key_len | ref         | rows | filtered | Extra                              |
+----+-------------+-------+------------+-------+---------------+--------+---------+-------------+------+----------+------------------------------------+
|  1 | SIMPLE      | t3    | NULL       | range | idx3_2,idx3_3 | idx3_3 | 9       | NULL        |    6 |   100.00 | Using index condition; Using where |
|  1 | SIMPLE      | t4    | NULL       | ref   | idx4_2,idx4_1 | idx4_1 | 5       | db1.t3.ccc1 |    5 |    16.67 | Using where                        |
+----+-------------+-------+------------+-------+---------------+--------+---------+-------------+------+----------+------------------------------------+

3、用 JOIN_FIXED_ORDER hint 加上表顺序来强制连接顺序。

greatsql> EXPLAIN SELECT /*+ qb_name(qb1) JOIN_FIXED_ORDER(@qb1) */ * FROM t3 join t4 ON t4.d1=t3.ccc1 AND t4.d2=t3.ccc2 WHERE t4.d1<5 AND t3.ccc3 < '2023-11-15';
+----+-------------+-------+------------+-------+---------------+--------+---------+-------------+------+----------+------------------------------------+
| id | select_type | table | partitions | type  | possible_keys | key    | key_len | ref         | rows | filtered | Extra                              |
+----+-------------+-------+------------+-------+---------------+--------+---------+-------------+------+----------+------------------------------------+
|  1 | SIMPLE      | t3    | NULL       | range | idx3_2,idx3_3 | idx3_3 | 9       | NULL        |    6 |   100.00 | Using index condition; Using where |
|  1 | SIMPLE      | t4    | NULL       | ref   | idx4_2        | idx4_2 | 5       | db1.t3.ccc2 |    6 |     3.33 | Using where                        |
+----+-------------+-------+------------+-------+---------------+--------+---------+-------------+------+----------+------------------------------------+

三、如何排查类似问题

从以上例子看出，打开条件过滤有时并不总是能提高性能，优化器可能会高估条件过滤的影响，个别场景下使用条件过滤反而会导致性能下降。GreatSQL的condition_fanout_filter参数默认是打开的，因此需要自己来判断是否需要这个功能。一般来说，遇到以下场景需要特别注意条件过滤错估的情况。

四、总结

这节用了一个例子展示了条件过滤误判的情况，知道了打开条件过滤有时并不总是能提高性能，优化器可能会高估条件过滤的影响，个别场景下使用条件过滤反而会导致性能下降。GreatSQL的condition_fanout_filter参数默认是打开的，因此需要自己来判断是否需要这个功能。