分页优化
表结构如下
CREATE TABLE `employees` (
`id` int NOT NULL AUTO_INCREMENT,
`name` varchar(24) NOT NULL DEFAULT '' COMMENT '姓名',
`age` int NOT NULL DEFAULT '0' COMMENT '年龄',
`position` varchar(20) NOT NULL DEFAULT '' COMMENT '职位',
`hire_time` timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP COMMENT '入职时间',
PRIMARY KEY (`id`),
KEY `idx_name_age_position` (`name`,`age`,`position`) USING BTREE
) ENGINE=InnoDB AUTO_INCREMENT=100001 DEFAULT CHARSET=utf8 COMMENT='员工记录表'
根据主键的查询排序
select * from employees limit 10000,10;
sql查询 会用到索引吗？
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select * from employees where id > 10000 limit 10;
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非主键的排序分页查询
sql查询 会用到索引吗？
select * from employees ORDER BY name limit 10
select * from employees ORDER BY name limit 10,10；
select * from employees ORDER BY name limit 100,10；
select * from employees ORDER BY name limit 1000,10；
select name from employees ORDER BY name limit 1000,10 ;
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按照B+Tree的结构，应该会走name字段索引，但是，操作的结果集太多，又要回表等等原因 ， MySQL可能不选name 字段的索引 ， key 字段对应的值为 null ，从而走了全表扫描 。。
select * from employees a inner join (select id from employees order by name limit 10000,10) b on a.id = b.id;
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索引优化
select * from employees where name > 'a';
select * from employees where name > 'zzz';
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SQL优化
- 条件优化
- 计算全表扫描成本
- 根据查询条件，找出所有可用的索引
- 计算各个索引的访问成本
- 选择成本最小的索引以及访问方式
开启查询优化器日志
为了能查看查询优化器优化的细节，我们需要开启查询优化器日志。
--开启
set optimizer_trace="enabled=on";
--执行sql
--查询日志信息
select * from information_schema.OPTIMIZER_TRACE;
--关闭
set optimizer_trace="enabled=off";
{
"steps": [
{
"join_preparation": {
"select#": 1,
"steps": [
{
"expanded_query": "/* select#1 */ select `employees`.`id` AS `id`,`employees`.`name` AS `name`,`employees`.`age` AS `age`,`employees`.`position` AS `position`,`employees`.`hire_time` AS `hire_time` from `employees` where (`employees`.`name` > 'a') order by `employees`.`position` limit 0,200"
}
]
}
},
{
"join_optimization": {
"select#": 1,
"steps": [
{
"condition_processing": {
"condition": "WHERE",
"original_condition": "(`employees`.`name` > 'a')",
"steps": [
{
"transformation": "equality_propagation",
"resulting_condition": "(`employees`.`name` > 'a')"
},
{
"transformation": "constant_propagation",
"resulting_condition": "(`employees`.`name` > 'a')"
},
{
"transformation": "trivial_condition_removal",
"resulting_condition": "(`employees`.`name` > 'a')"
}
]
}
},
{
"substitute_generated_columns": {}
},
{
"table_dependencies": [
{
"table": "`employees`",
"row_may_be_null": false,
"map_bit": 0,
"depends_on_map_bits": []
}
]
},
{
"ref_optimizer_key_uses": []
},
{
"rows_estimation": [
{
"table": "`employees`",
"range_analysis": {
"table_scan": {
"rows": 100166,
"cost": 10107
},
"potential_range_indexes": [
{
"index": "PRIMARY",
"usable": false,
"cause": "not_applicable"
},
{
"index": "idx_name_age_position",
"usable": true,
"key_parts": [
"name",
"age",
"position",
"id"
]
}
],
"setup_range_conditions": [],
"group_index_range": {
"chosen": false,
"cause": "not_group_by_or_distinct"
},
"skip_scan_range": {
"potential_skip_scan_indexes": [
{
"index": "idx_name_age_position",
"usable": false,
"cause": "query_references_nonkey_column"
}
]
},
"analyzing_range_alternatives": {
"range_scan_alternatives": [
{
"index": "idx_name_age_position",
"ranges": [
"a < name"
],
"index_dives_for_eq_ranges": true,
"rowid_ordered": false,
"using_mrr": false,
"index_only": false,
"rows": 50083,
"cost": 17529,
"chosen": false,
"cause": "cost"
}
],
"analyzing_roworder_intersect": {
"usable": false,
"cause": "too_few_roworder_scans"
}
}
}
}
]
},
{
"considered_execution_plans": [
{
"plan_prefix": [],
"table": "`employees`",
"best_access_path": {
"considered_access_paths": [
{
"rows_to_scan": 100166,
"filtering_effect": [],
"final_filtering_effect": 0.5,
"access_type": "scan",
"resulting_rows": 50083,
"cost": 10105,
"chosen": true
}
]
},
"condition_filtering_pct": 100,
"rows_for_plan": 50083,
"cost_for_plan": 10105,
"chosen": true
}
]
},
{
"attaching_conditions_to_tables": {
"original_condition": "(`employees`.`name` > 'a')",
"attached_conditions_computation": [
{
"table": "`employees`",
"rechecking_index_usage": {
"recheck_reason": "low_limit",
"limit": 200,
"row_estimate": 50083
}
}
],
"attached_conditions_summary": [
{
"table": "`employees`",
"attached": "(`employees`.`name` > 'a')"
}
]
}
},
{
"optimizing_distinct_group_by_order_by": {
"simplifying_order_by": {
"original_clause": "`employees`.`position`",
"items": [
{
"item": "`employees`.`position`"
}
],
"resulting_clause_is_simple": true,
"resulting_clause": "`employees`.`position`"
}
}
},
{
"reconsidering_access_paths_for_index_ordering": {
"clause": "ORDER BY",
"steps": [],
"index_order_summary": {
"table": "`employees`",
"index_provides_order": false,
"order_direction": "undefined",
"index": "unknown",
"plan_changed": false
}
}
},
{
"finalizing_table_conditions": [
{
"table": "`employees`",
"original_table_condition": "(`employees`.`name` > 'a')",
"final_table_condition ": "(`employees`.`name` > 'a')"
}
]
},
{
"refine_plan": [
{
"table": "`employees`"
}
]
},
{
"considering_tmp_tables": [
{
"adding_sort_to_table": "employees"
}
]
}
]
}
},
{
"join_execution": {
"select#": 1,
"steps": [
{
"sorting_table": "employees",
"filesort_information": [
{
"direction": "asc",
"expression": "`employees`.`position`"
}
],
"filesort_priority_queue_optimization": {
"limit": 200,
"chosen": true
},
"filesort_execution": [],
"filesort_summary": {
"memory_available": 262144,
"key_size": 40,
"row_size": 186,
"max_rows_per_buffer": 201,
"num_rows_estimate": 100166,
"num_rows_found": 100000,
"num_initial_chunks_spilled_to_disk": 0,
"peak_memory_used": 38994,
"sort_algorithm": "std::stable_sort",
"unpacked_addon_fields": "using_priority_queue",
"sort_mode": "<fixed_sort_key, additional_fields>"
}
}
]
}
}
]
}
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