【GreatSQL优化器-09】make_join_query_block

一、make_join_query_block介绍

GreatSQL优化器对于多张表join的连接顺序在前面的章节介绍过的best_access_path函数已经执行了，接着就是把where条件进行切割然后推给合适的表。这个过程就是由函数make_join_query_block来执行的。

下面用几个简单的例子来说明join连接中条件推送是什么。

 CREATE TABLE t1 (c1 INT PRIMARY KEY, c2 INT,date1 DATETIME); INSERT INTO t1 VALUES (1,10,'2021-03-25 16:44:00.123456'),(2,1,'2022-03-26 16:44:00.123456'),(3,4,'2023-03-27 16:44:00.123456'),(5,5,'2024-03-25 16:44:00.123456'),(7,null,'2020-03-25 16:44:00.123456'),(8,10,'2020-10-25 16:44:00.123456'),(11,16,'2023-03-25 16:44:00.123456'); CREATE TABLE t2 (cc1 INT PRIMARY KEY, cc2 INT); INSERT INTO t2 VALUES (1,3),(2,1),(3,2),(4,3),(5,15); CREATE TABLE t3 (ccc1 INT, ccc2 varchar(100)); INSERT INTO t3 VALUES (1,'aa1'),(2,'bb1'),(3,'cc1'),(4,'dd1'),(null,'ee'); CREATE INDEX idx1 ON t1(c2); CREATE INDEX idx2 ON t1(c2,date1); CREATE INDEX idx2_1 ON t2(cc2); CREATE INDEX idx3_1 ON t3(ccc1);

下面这个例子((t1.c1 = t3.ccc1) or (t3.ccc1 < 3))条件推送给t1

 greatsql> EXPLAIN FORMAT=TREE SELECT * FROM t1 join t3 ON t1.c1=t3.ccc1 or t3.ccc1<3; +-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ | EXPLAIN | +-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ | -> Filter: ((t1.c1 = t3.ccc1) or (t3.ccc1 < 3)) (cost=5.26 rows=35) -> Inner hash join (no condition) (cost=5.26 rows=35) -> Index scan on t1 using idx2 (cost=0.34 rows=7) -> Hash -> Table scan on t3 (cost=0.75 rows=5) | +-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ 1 row in set (0.00 sec)

下面例子(t1.c1 < 3)条件推给t1，(ccc1=t1.c1)条件推给t3

 greatsql> EXPLAIN FORMAT=TREE SELECT * FROM t1 join t3 ON t1.c1=t3.ccc1 and t3.ccc1<3; +----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ | EXPLAIN | +----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ | -> Nested loop inner join (cost=2.40 rows=2) -> Filter: (t1.c1 < 3) (cost=1.70 rows=2) -> Index scan on t1 using idx2 (cost=1.70 rows=7) -> Index lookup on t3 using idx3_1 (ccc1=t1.c1) (cost=0.30 rows=1) | +----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+

下面例子((t3.ccc1 = t1.c2) or (t3.ccc1 is null) or (t3.ccc2 like 'a%'))条件推给t3，(((t3.ccc1 = t1.c2) and (t2.cc1 = t1.c1)) or (t3.ccc1 is null) or (t3.ccc2 like 'a%'))条件推给t2

 greatsql> EXPLAIN SELECT * FROM t2,t1,t3 WHERE t1.c1=t2.cc1 AND t1.c2=t3.ccc1 OR t3.ccc1 IS NULL OR t3.ccc2 LIKE 'a%'; | -> Filter: (((t3.ccc1 = t1.c2) and (t2.cc1 = t1.c1)) or (t3.ccc1 is null) or (t3.ccc2 like 'a%')) (cost=14.27 rows=85) -> Inner hash join (no condition) (cost=14.27 rows=85) -> Index scan on t2 using idx2_1 (cost=0.09 rows=5) -> Hash -> Filter: ((t3.ccc1 = t1.c2) or (t3.ccc1 is null) or (t3.ccc2 like 'a%')) (cost=4.70 rows=17) -> Inner hash join (no condition) (cost=4.70 rows=17) -> Table scan on t3 (cost=0.07 rows=5) -> Hash -> Index scan on t1 using idx2 (cost=0.95 rows=7)

二、make_join_query_block代码解释

make_join_query_block函数通过join表顺序和每张表的table_map属性以及cond条件的属性来决定cond条件添加到哪张表,并且可能会重新对表的索引进行check找出cost更低的索引，下面是代码解析。

 bool JOIN::optimize() { make_join_query_block(); } static bool make_join_query_block(JOIN *join, Item *cond) { for (uint i = join->const_tables; i < join->tables; i++) { // 这四个变量说明见表一 JOIN_TAB *const tab = join->best_ref[i]; const plan_idx first_inner = tab->first_inner(); const table_map used_tables = tab->prefix_tables(); const table_map current_map = tab->added_tables(); if (cond) // 这里通过table_map属性决定了是否给这个表添加条件，见下面表二、表四和表五说明 tmp = make_cond_for_table(thd, cond, used_tables, current_map, false); // 如果recheck_reason=true，这里需要重新做一次确认，找出cost最低的索引。见表六 if (recheck_reason) test_if_order_by_key(); test_if_cheaper_ordering(); test_quick_select(); } /* Add conditions added by add_not_null_conds(). */ if (and_conditions(&tmp, tab->condition())) return true; if (join->attach_join_conditions(i)) return true; } } // 条件添加基本原则是条件带有表列的添加到该表，但是如果属性不一致的话也不会添加，只会添加到最后一张表。具体解释见下面实际例子。

表一：上面四个变量解释

变量	解释	说明
tab	当前检测是否需要加条件的表	这里是排序后的表
first_inner	多张表join的时候排序后的第一张表	例如：SELECT * FROM t1 LEFT OUTER JOIN (t2 JOIN t3) ON X
used_tables	包括当前表以及之前的左连接表的信息	如果该值=0代表所有表，used_tables信息在之前的set_prefix_tables()获得
current_map	当前检测表信息	包含被添加的一些信息

表二：make_cond_for_table()动作

场景	解释	返回
AND条件	遍历Item_cond包含的所有list，判断list是否有包含该表左连接的表的列，有的话加入新的Item_cond_and	new Item_cond_and
OR条件	遍历Item_cond包含的所有list，判断list是否有包含该表左连接的表的列，有的话加入新的Item_cond_or	new Item_cond_or
其他Item	如果条件没有涉及左连接的表，或者给所有表添加条件cond->is_expensive()	nullptr(无条件)
其他Item	如果条件涉及左连接的表并且item与表的属性一致(见表四)	该Item条件

表三：is_expensive_processor()函数

Item	is_expensive	说明
Item_udf_func	true	这个Item作为条件不会添加到所有join表里面
Item_func_sp	true	这个Item作为条件不会添加到所有join表里面
普通Item	false	这个Item作为条件可能会添加到join表里面

表四：Item的table_map属性

table_map	使用的Item	说明	举例
INNER_TABLE_BIT	Item_trigger_field，Item_sp_variable，Item_param，Item_func_connection_id，Item_func_get_system_var，Item_func_user，Item_load_file, Item_func_sp，Item_func_get_user_var	确定的常量，在表每行都一样	f1(1)@@optimizer_search_depth
OUTER_REF_TABLE_BIT	Item_field,Item_ref,Item_view_ref,Item_outer_ref	内部field需要外部query block的item信息	select (select t1.a from t1 as t2 limit 1) from t1 group by t1.pk，t1.a就是OUTER_REF_TABLE_BIT
RAND_TABLE_BIT	Item_func_rand,Item_func_sleep,Item_func_uuid,Item_func_sysdate_local，Item_func_reject_if,Item_func_sp，Item_func_get_user_var	不确定的，表每行都要换数据，非只有一行表，跟INNER_TABLE_BIT相反	f1(t1.c1)
PSEUDO_TABLE_BITS		包含以上三个

表五：表连接添加的属性

table_map	第一张表	中间的表	最后一张表
INNER_TABLE_BIT	yes	无	无
OUTER_REF_TABLE_BIT	allow_outer_refs	无	无
RAND_TABLE_BIT	无	无	yes

表六：表的索引是否要重新check

recheck_reason	说明
DONT_RECHECK	没有索引的表不需要重新check
NOT_FIRST_TABLE	不是第一张表需要重新check
LOW_LIMIT	带有limit语句的sql需要重新check

三、实际例子说明

接下来看几个例子来说明上面的代码。

首先看一下最后确定的连接顺序，为t1,t3,t2，因为条件不带有RAND_TABLE_BIT的Item，因此最后是按照cond含有的列推送给对应表来实现的。

例子一：

 greatsql> EXPLAIN SELECT * FROM t2,t1,t3 WHERE t1.c1=t2.cc1 AND t1.c2=t3.ccc1 OR t3.ccc1 IS NULL OR t3.ccc2 LIKE 'a%'; +----+-------------+-------+------------+-------+-------------------+--------+---------+------+------+----------+---------------------------------------------------------+ | id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra | +----+-------------+-------+------------+-------+-------------------+--------+---------+------+------+----------+---------------------------------------------------------+ | 1 | SIMPLE | t1 | NULL | index | PRIMARY,idx1,idx2 | idx2 | 11 | NULL | 7 | 100.00 | Using index | | 1 | SIMPLE | t3 | NULL | ALL | idx3_1 | NULL | NULL | NULL | 5 | 48.80 | Using where; Using join buffer (hash join) | | 1 | SIMPLE | t2 | NULL | index | PRIMARY | idx2_1 | 5 | NULL | 5 | 100.00 | Using where; Using index; Using join buffer (hash join) | +----+-------------+-------+------------+-------+-------------------+--------+---------+------+------+----------+---------------------------------------------------------+

表一：是否把cond条件推送给表

COND	t1	[t1,]t3	[t1,t3,]t2
(t1.c1=t2.cc1)	no	no	yes
(t3.ccc1 = t1.c2)	no	yes	yes
(t3.ccc1 is null)	no	yes	yes
(t3.ccc2 like 'a%')	no	yes	yes

注：这里的中括号代表当前检测表的左连接表，中括号右边就是当前正在检测的表

表二：表的table_map值

COND	t1	t3	t2
best_ref->table_ref->map()	0x010	0x100	0x001
best_ref->prefix_tables()	INNER_TABLE_BIT+ OUTER_REF_TABLE_BIT+0x010	INNER_TABLE_BIT+ OUTER_REF_TABLE_BIT+0x010+0x100	INNER_TABLE_BIT+OUTER_REF_TABLE_BIT +RAND_TABLE_BIT+0x010+0x100+0x001
best_ref->added_tables()	INNER_TABLE_BIT+ OUTER_REF_TABLE_BIT+0x010	0x100	RAND_TABLE_BIT+0x001

注：这里的INNER_TABLE_BIT和OUTER_REF_TABLE_BIT在函数JOIN::set_prefix_tables()默认加上了

看一下结果是否符合预期，确实如上表所述。这里看到又执行了一次test_quick_select()来确定走哪个索引。

 "attaching_conditions_to_tables": { "original_condition": "(((`t3`.`ccc1` = `t1`.`c2`) and (`t2`.`cc1` = `t1`.`c1`)) or (`t3`.`ccc1` is null) or (`t3`.`ccc2` like 'a%'))", "attached_conditions_computation": [ { "table": "`t2`", "rechecking_index_usage": { 这里对索引重新做了一次check "recheck_reason": "not_first_table", "range_analysis": { "table_scan": { "rows": 5, "cost": 3.6 }, "potential_range_indexes": [ { "index": "PRIMARY", "usable": true, "key_parts": [ "cc1" ] }, { "index": "idx2_1", "usable": false, "cause": "not_applicable" } ], "best_covering_index_scan": { "index": "idx2_1", "cost": 0.751098, "chosen": true }, "setup_range_conditions": [ ], "group_index_range": { "chosen": false, "cause": "not_single_table" }, "skip_scan_range": { "chosen": false, "cause": "not_single_table" } } } } ], "attached_conditions_summary": [ { "table": "`t1`", "attached": null }, { "table": "`t3`", "attached": "((`t3`.`ccc1` = `t1`.`c2`) or (`t3`.`ccc1` is null) or (`t3`.`ccc2` like 'a%'))" }, { "table": "`t2`", "attached": "(((`t3`.`ccc1` = `t1`.`c2`) and (`t2`.`cc1` = `t1`.`c1`)) or (`t3`.`ccc1` is null) or (`t3`.`ccc2` like 'a%'))" } ] } }, { "finalizing_table_conditions": [ { "table": "`t3`", "original_table_condition": "((`t3`.`ccc1` = `t1`.`c2`) or (`t3`.`ccc1` is null) or (`t3`.`ccc2` like 'a%'))", "final_table_condition ": "((`t3`.`ccc1` = `t1`.`c2`) or (`t3`.`ccc1` is null) or (`t3`.`ccc2` like 'a%'))" }, { "table": "`t2`", "original_table_condition": "(((`t3`.`ccc1` = `t1`.`c2`) and (`t2`.`cc1` = `t1`.`c1`)) or (`t3`.`ccc1` is null) or (`t3`.`ccc2` like 'a%'))", "final_table_condition ": "(((`t3`.`ccc1` = `t1`.`c2`) and (`t2`.`cc1` = `t1`.`c1`)) or (`t3`.`ccc1` is null) or (`t3`.`ccc2` like 'a%'))" } ] }, { "refine_plan": [ { "table": "`t1`" }, { "table": "`t3`" }, { "table": "`t2`" } ] } ] } }

如果条件带有RAND_TABLE_BIT的Item，那么即使cond带有表的列，也不会推送给对应的表，而是推送到最后一张表。看下面的t1.c1 < rand()这个条件。

例子二：

 greatsql> SELECT * FROM t2,t1,t3 WHERE t1.c1=t2.cc1 AND t1.c2=t3.ccc1 OR t3.ccc1 IS NULL AND t1.c1 < rand(); "attached_conditions_summary": [ { "table": "`t1`", "attached": null }, { "table": "`t3`", "attached": "((`t3`.`ccc1` = `t1`.`c2`) or (`t3`.`ccc1` is null))" }, { "table": "`t2`", "attached": "(((`t3`.`ccc1` = `t1`.`c2`) and (`t2`.`cc1` = `t1`.`c1`)) or ((`t3`.`ccc1` is null) and (`t1`.`c1` < rand())))" 看到条件t1.c1 < rand()没有推送给t1而是推送到最后一张表t2去了 } ] } }, { "finalizing_table_conditions": [ { "table": "`t3`", "original_table_condition": "((`t3`.`ccc1` = `t1`.`c2`) or (`t3`.`ccc1` is null))", "final_table_condition ": "((`t3`.`ccc1` = `t1`.`c2`) or (`t3`.`ccc1` is null))" }, { "table": "`t2`", "original_table_condition": "(((`t3`.`ccc1` = `t1`.`c2`) and (`t2`.`cc1` = `t1`.`c1`)) or ((`t3`.`ccc1` is null) and (`t1`.`c1` < rand())))", "final_table_condition ": "(((`t3`.`ccc1` = `t1`.`c2`) and (`t2`.`cc1` = `t1`.`c1`)) or ((`t3`.`ccc1` is null) and (`t1`.`c1` < rand())))" } ] }, { "refine_plan": [ { "table": "`t1`" }, { "table": "`t3`" }, { "table": "`t2`" }

看一下每张表的属性：

COND	t1	t3	t2
best_ref->table_ref->map()	0x010	0x100	0x001
best_ref->prefix_tables()	INNER_TABLE_BIT+ OUTER_REF_TABLE_BIT+0x010	INNER_TABLE_BIT+ OUTER_REF_TABLE_BIT+0x010+0x100	INNER_TABLE_BIT+OUTER_REF_TABLE_BIT +RAND_TABLE_BIT+0x010+0x100+0x001
best_ref->added_tables()	INNER_TABLE_BIT+ OUTER_REF_TABLE_BIT+0x010	0x100	RAND_TABLE_BIT+0x001

四、总结

从上面优化器最早的步骤我们认识了make_join_query_block函数的作用，知道了通过join表顺序和每张表的table_map属性以及cond条件的属性来决定cond条件添加到哪张表,并且可能会重新对表的索引进行check找出cost更低的索引，需要注意的是有的带有表列的条件不会被添加到对应表，因为Item的属性跟表的属性不一致所以最后只会被添加到最后一张join表。