MySQL不走索引的原因
1、基本结论
SQL 的执行成本（cost）是 MySQL 优化器选择 SQL 执行计划时一个重要考量因素。当优化器认为使用索引的成本高于全表扫描的时候，优化器将会选择全表扫描，而不是使用索引。
下面通过一个实验来说明。
2、问题现象
如下结构的一张表，表中约有104w行数据：
CREATE TABLE `test03` (
`id` int(11) NOT NULL AUTO_INCREMENT COMMENT '自增主键',
`dept` tinyint(4) NOT NULL COMMENT '部门id',
`name` varchar(30) COLLATE utf8mb4_bin DEFAULT NULL COMMENT '用户名称',
`create_time` datetime NOT NULL COMMENT '注册时间',
`last_login_time` datetime DEFAULT NULL COMMENT '最后登录时间',
PRIMARY KEY (`id`),
KEY `ct_index` (`create_time`)
) ENGINE=InnoDB AUTO_INCREMENT=1048577 DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_bin COMMENT='测试表'
查询1，并未用到 ct_index(create_time) 索引:
- type 为 ALL ，而不是 range
- rows 行数和全表行数接近
# 查询1
mysql> explain select * from test03 where create_time > '2021-10-01 02:04:36';
+----+-------------+--------+------------+------+---------------+------+---------+------+---------+----------+-------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+--------+------------+------+---------------+------+---------+------+---------+----------+-------------+
| 1 | SIMPLE | test03 | NULL | ALL | ct_index | NULL | NULL | NULL | 1045955 | 50.00 | Using where |
+----+-------------+--------+------------+------+---------------+------+---------+------+---------+----------+-------------+
1 row in set, 1 warning (0.00 sec)
而查询2，则用到了 ct_index(create_time) 索引:
# 查询2
mysql> explain select * from test03 where create_time < '2021-01-01 02:04:36';
+----+-------------+--------+------------+-------+---------------+----------+---------+------+------+----------+-----------------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+--------+------------+-------+---------------+----------+---------+------+------+----------+-----------------------+
| 1 | SIMPLE | test03 | NULL | range | ct_index | ct_index | 5 | NULL | 169 | 100.00 | Using index condition |
+----+-------------+--------+------------+-------+---------------+----------+---------+------+------+----------+-----------------------+
3、获得SQL优化器处理信息
这里使用 optimizer trace 工具，观察 MySQL 对 SQL 的优化处理过程：
# 调大trace的容量，防止被截断
set global optimizer_trace_max_mem_size = 1048576;
# 开启optimizer_trace
set optimizer_trace="enabled=on";
# 执行SQL
select * from test03 where create_time > '2021-10-01 02:04:36';
# SQL执行完成之后，查看TRACE
select TRACE from INFORMATION_SCHEMA.OPTIMIZER_TRACE\G
获得关于此 SQL 的详细优化器处理信息：
mysql> select TRACE from INFORMATION_SCHEMA.OPTIMIZER_TRACE\G
*************************** 1. row ***************************
TRACE: {
"steps": [
{
"join_preparation": {
"select#": 1,
"steps": [
{
"expanded_query": "/* select#1 */ select `test03`.`id` AS `id`,`test03`.`dept` AS `dept`,`test03`.`name` AS `name`,`test03`.`create_time` AS `create_time`,`test03`.`last_login_time` AS `last_login_time` from `test03` where (`test03`.`create_time` > '2021-10-01 02:04:36')"
}
]
}
},
{
"join_optimization": {
"select#": 1,
"steps": [
{
"condition_processing": {
"condition": "WHERE",
"original_condition": "(`test03`.`create_time` > '2021-10-01 02:04:36')",
"steps": [
{
"transformation": "equality_propagation",
"resulting_condition": "(`test03`.`create_time` > '2021-10-01 02:04:36')"
},
{
"transformation": "constant_propagation",
"resulting_condition": "(`test03`.`create_time` > '2021-10-01 02:04:36')"
},
{
"transformation": "trivial_condition_removal",
"resulting_condition": "(`test03`.`create_time` > '2021-10-01 02:04:36')"
}
]
}
},
{
"substitute_generated_columns": {
}
},
{
"table_dependencies": [
{
"table": "`test03`",
"row_may_be_null": false,
"map_bit": 0,
"depends_on_map_bits": [
]
}
]
},
{
"ref_optimizer_key_uses": [
]
},
{
"rows_estimation": [
{
"table": "`test03`",
"range_analysis": {
"table_scan": {
"rows": 1045955,
"cost": 212430
},
"potential_range_indexes": [
{
"index": "PRIMARY",
"usable": false,
"cause": "not_applicable"
},
{
"index": "ct_index",
"usable": true,
"key_parts": [
"create_time",
"id"
]
}
],
"setup_range_conditions": [
],
"group_index_range": {
"chosen": false,
"cause": "not_group_by_or_distinct"
},
"analyzing_range_alternatives": {
"range_scan_alternatives": [
{
"index": "ct_index",
"ranges": [
"0x99aac22124 < create_time"
],
"index_dives_for_eq_ranges": true,
"rowid_ordered": false,
"using_mrr": false,
"index_only": false,
"rows": 522977,
"cost": 627573,
"chosen": false,
"cause": "cost"
}
],
"analyzing_roworder_intersect": {
"usable": false,
"cause": "too_few_roworder_scans"
}
}
}
}
]
},
{
"considered_execution_plans": [
{
"plan_prefix": [
],
"table": "`test03`",
"best_access_path": {
"considered_access_paths": [
{
"rows_to_scan": 1045955,
"access_type": "scan",
"resulting_rows": 1.05e6,
"cost": 212428,
"chosen": true
}
]
},
"condition_filtering_pct": 100,
"rows_for_plan": 1.05e6,
"cost_for_plan": 212428,
"chosen": true
}
]
},
{
"attaching_conditions_to_tables": {
"original_condition": "(`test03`.`create_time` > '2021-10-01 02:04:36')",
"attached_conditions_computation": [
],
"attached_conditions_summary": [
{
"table": "`test03`",
"attached": "(`test03`.`create_time` > '2021-10-01 02:04:36')"
}
]
}
},
{
"refine_plan": [
{
"table": "`test03`"
}
]
}
]
}
},
{
"join_execution": {
"select#": 1,
"steps": [
]
}
}
]
}
1 row in set (0.00 sec)
通过逐行阅读，发现优化器在 join_optimization（SQL优化阶段）部分的 rows_estimation内容里：
-
明确指出了使用索引 ct_index(create_time) 和全表扫描的成本差异
- 同时指出了未选择索引的原因：cost
4、为什么使用索引的成本比全表扫描还高？
通过观察优化器的信息，不难发现，使用索引扫描行数约52w行，而全表扫描约为104w行。为什么优化器反而认为使用索引的成本比全表扫描还高呢？
因为当 ct_index(create_time) 这个普通索引并不包括查询的所有列，因此需要通过 ct_index 的索引树找到对应的主键 id ，然后再到 id 的索引树进行数据查询，即回表（通过索引查出主键，再去查数据行），这样成本必然上升。尤其是当回表的数据量比较大的时候，经常会出现 MySQL 优化器认为回表查询代价过高而不选择索引的情况。
这里可以回头看查询1和查询2的数据量占比：
-
查询1的数据量占整个表的60%，回表成本高，因此优化器选择了全表扫描
- 查询2的数据量占整个表的0.02%，因此优化器选择了索引
mysql> select (select count(*) from test03 where create_time > '2021-10-01 02:04:36')/(select count(*) from test03) as '>20211001', (select count(*) from test03 where create_time < '2021-01-01 02:04:36')/(select count(*) from test03) as '<20210101';
+-----------+-----------+
| >20211001 | <20210101 |
+-----------+-----------+
| 0.5997 | 0.0002 |
+-----------+-----------+
1 row in set (0.44 sec)
另外，在 MySQL 的官方文档中对此也有简要的描述：
-
当优化器认为全表扫描成本更低的时候，就不会使用索引
-
并没有一个固定的数据量占比来决定优化器是否使用全表扫描（曾经是30%）
-
优化器在选择的时候会考虑更多的因素，如：表大小，行数量，IO块大小等
https://dev.mysql.com/doc/refman/5.7/en/where-optimization.html
转载自爱可生技术文档
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