关于java:MySQL-调优-OPTIMIZERTRACE详解

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TIPS

本文基于 MySQL 8.0 编写,实践反对 MySQL 5.6 及更高版本。

OPTIMIZER_TRACE 是 MySQL 5.6 引入的一项跟踪性能,它能够跟踪优化器做出的各种决策(比方拜访表的办法、各种开销计算、各种转换等),并将跟踪后果记录到 INFORMATION_SCHEMA.OPTIMIZER_TRACE 表中。此性能默认敞开,开启后,可剖析如下语句:

  • SELECT
  • INSERT
  • REPLACE
  • UPDATE
  • DELETE
  • EXPLAIN
  • SET
  • DECLARE
  • CASE
  • IF
  • RETURN
  • CALL

OPTIMIZER_TRACE 相干参数

TIPS

参考 https://dev.mysql.com/doc/int…

  • optimizer_trace

    • optimizer_trace 总开关,默认值:enabled=off,one_line=off
    • enabled:是否开启 optimizer_trace;on 示意开启,off 示意敞开。
    • one_line:是否开启单行存储。on 示意开启;off 示意敞开,将会用规范的 JSON 格式化存储。设置成 on 将会有良好的格局,设置成 off 可节俭一些空间。
  • optimizer_trace_features

    • 管制 optimizer_trace 跟踪的内容,默认值:greedy_search=on,range_optimizer=on,dynamic_range=on,repeated_subselect=on,示意开启所有跟踪项。
  • greedy_search:是否跟踪贪婪搜寻,无关贪婪算法详见 https://blog.csdn.net/weixin_…

    • range_optimizer:是否跟踪范畴优化器
  • dynamic_range:是否跟踪动静范畴优化

    • repeated_subselect:是否跟踪子查问,如果设置成 off,只跟踪第一条 Item_subselect 的执行
  • 详见 https://dev.mysql.com/doc/int…
  • optimizer_trace_limit:管制 optimizer_trace 展现多少条后果,默认 1
  • optimizer_trace_max_mem_size:optimizer_trace 堆栈信息容许的最大内存,默认 1048576
  • optimizer_trace_offset:第一个要展现的 optimizer trace 的偏移量,默认 -1。
  • end_markers_in_json:如果 JSON 构造很大,则很难将右括号和左括号配对。为了帮忙读者浏览,可将其设置成 on,这样会在右括号左近加上正文,默认 off。

    参考:https://dev.mysql.com/doc/int…

TIPS

  • 以上参数可用 SET 语句操作,例如,用如下命令即可关上 OPTIMIZER TRACE

    >   SET OPTIMIZER_TRACE="enabled=on",END_MARKERS_IN_JSON=on;
    >

也可用 SET GLOBAL 全局开启。但即便全局开启 OPTIMIZER_TRACE,每个 Session 也只能跟踪它本人执行的语句:

>   SET GLOBAL OPTIMIZER_TRACE="enabled=on",END_MARKERS_IN_JSON=on;
>
  • optimizer_trace_limit 和 optimizer_trace_offset 这两个参数常常配合应用,例如:

    >   SET optimizer_trace_offset=<OFFSET>, optimizer_trace_limit=<LIMIT>
    >

这两个参数配合应用,有点相似 MySQL 外面的 limit 语句。

默认状况下,因为 optimizer_trace_offset=-1,optimizer_trace_limit=1,记录最近的一条 SQL 语句,展现时,每次展现 1 条数据;

如果改成 SET optimizer_trace_offset=-2, optimizer_trace_limit=1,则会记录倒数第二条 SQL 语句;

无关 optimizer_trace_offset、optimizer_trace_limit 更多细节,可参考 https://dev.mysql.com/doc/int…

OPTIMIZER_TRACE 应用

  • 开启 OPTIMIZER_TRACE 性能,并设置要展现的数据条目数:

    SET OPTIMIZER_TRACE="enabled=on",END_MARKERS_IN_JSON=on;
    SET optimizer_trace_offset=-30, optimizer_trace_limit=30;
  • 发送你想要剖析的 SQL 语句,例如:

    select *
    from salaries
    where from_date = '1986-06-26'
      and to_date = '1987-06-26';
  • 应用如下语句剖析,即可取得相似如下的后果:

      mysql> SELECT * FROM INFORMATION_SCHEMA.OPTIMIZER_TRACE limit 30 \G;
      *************************** 1. row ***************************
                                QUERY: select *
      from salaries
    where from_date = '1986-06-26'
        and to_date = '1987-06-26'
                                  TRACE: {
        "steps": [
          {
            "join_preparation": {
              "select#": 1,
              "steps": [
                {"expanded_query": "/* select#1 */ select `salaries`.`emp_no` AS `emp_no`,`salaries`.`salary` AS `salary`,`salaries`.`from_date` AS `from_date`,`salaries`.`to_date` AS `to_date` from `salaries` where ((`salaries`.`from_date` ='1986-06-26') and (`salaries`.`to_date` ='1987-06-26'))"
                }
              ] /* steps */
            } /* join_preparation */
          },
          {
            "join_optimization": {
              "select#": 1,
              "steps": [
                {
                  "condition_processing": {
                    "condition": "WHERE",
                    "original_condition": "((`salaries`.`from_date` ='1986-06-26') and (`salaries`.`to_date` ='1987-06-26'))",
                    "steps": [
                      {
                        "transformation": "equality_propagation",
                        "resulting_condition": "(multiple equal('1986-06-26', `salaries`.`from_date`) and multiple equal('1987-06-26', `salaries`.`to_date`))"
                      },
                      {
                        "transformation": "constant_propagation",
                        "resulting_condition": "(multiple equal('1986-06-26', `salaries`.`from_date`) and multiple equal('1987-06-26', `salaries`.`to_date`))"
                      },
                      {
                        "transformation": "trivial_condition_removal",
                        "resulting_condition": "(multiple equal(DATE'1986-06-26', `salaries`.`from_date`) and multiple equal(DATE'1987-06-26', `salaries`.`to_date`))"
                      }
                    ] /* steps */
                  } /* condition_processing */
                },
                {"substitute_generated_columns": {} /* substitute_generated_columns */
                },
                {
                  "table_dependencies": [
                    {
                      "table": "`salaries`",
                      "row_may_be_null": false,
                      "map_bit": 0,
                      "depends_on_map_bits": [] /* depends_on_map_bits */}
                  ] /* table_dependencies */
                },
                {
                  "ref_optimizer_key_uses": [
                    {
                      "table": "`salaries`",
                      "field": "from_date",
                      "equals": "DATE'1986-06-26'","null_rejecting": false
                    },
                    {
                      "table": "`salaries`",
                      "field": "to_date",
                      "equals": "DATE'1987-06-26'","null_rejecting": false
                    }
                  ] /* ref_optimizer_key_uses */
                },
                {
                  "rows_estimation": [
                    {
                      "table": "`salaries`",
                      "range_analysis": {
                        "table_scan": {
                          "rows": 2838216,
                          "cost": 286799
                        } /* table_scan */,
                        "potential_range_indexes": [
                          {
                            "index": "PRIMARY",
                            "usable": false,
                            "cause": "not_applicable"
                          },
                          {
                            "index": "salaries_from_date_to_date_index",
                            "usable": true,
                            "key_parts": [
                              "from_date",
                              "to_date",
                              "emp_no"
                            ] /* key_parts */
                          }
                        ] /* potential_range_indexes */,
                        "setup_range_conditions": [ ] /* setup_range_conditions */,
                        "group_index_range": {
                          "chosen": false,
                          "cause": "not_group_by_or_distinct"
                        } /* group_index_range */,
                        "skip_scan_range": {
                          "potential_skip_scan_indexes": [
                            {
                              "index": "salaries_from_date_to_date_index",
                              "usable": false,
                              "cause": "query_references_nonkey_column"
                            }
                          ] /* potential_skip_scan_indexes */
                        } /* skip_scan_range */,
                        "analyzing_range_alternatives": {
                          "range_scan_alternatives": [
                            {
                              "index": "salaries_from_date_to_date_index",
                              "ranges": ["0xda840f <= from_date <= 0xda840f AND 0xda860f <= to_date <= 0xda860f"] /* ranges */,
                              "index_dives_for_eq_ranges": true,
                              "rowid_ordered": true,
                              "using_mrr": false,
                              "index_only": false,
                              "rows": 86,
                              "cost": 50.909,
                              "chosen": true
                            }
                          ] /* range_scan_alternatives */,
                          "analyzing_roworder_intersect": {
                            "usable": false,
                            "cause": "too_few_roworder_scans"
                          } /* analyzing_roworder_intersect */
                        } /* analyzing_range_alternatives */,
                        "chosen_range_access_summary": {
                          "range_access_plan": {
                            "type": "range_scan",
                            "index": "salaries_from_date_to_date_index",
                            "rows": 86,
                            "ranges": ["0xda840f <= from_date <= 0xda840f AND 0xda860f <= to_date <= 0xda860f"] /* ranges */
                          } /* range_access_plan */,
                          "rows_for_plan": 86,
                          "cost_for_plan": 50.909,
                          "chosen": true
                        } /* chosen_range_access_summary */
                      } /* range_analysis */
                    }
                  ] /* rows_estimation */
                },
                {
                  "considered_execution_plans": [
                    {"plan_prefix": [] /* plan_prefix */,
                      "table": "`salaries`",
                      "best_access_path": {
                        "considered_access_paths": [
                          {
                            "access_type": "ref",
                            "index": "salaries_from_date_to_date_index",
                            "rows": 86,
                            "cost": 50.412,
                            "chosen": true
                          },
                          {
                            "access_type": "range",
                            "range_details": {"used_index": "salaries_from_date_to_date_index"} /* range_details */,
                            "chosen": false,
                            "cause": "heuristic_index_cheaper"
                          }
                        ] /* considered_access_paths */
                      } /* best_access_path */,
                      "condition_filtering_pct": 100,
                      "rows_for_plan": 86,
                      "cost_for_plan": 50.412,
                      "chosen": true
                    }
                  ] /* considered_execution_plans */
                },
                {
                  "attaching_conditions_to_tables": {"original_condition": "((`salaries`.`to_date` = DATE'1987-06-26') and (`salaries`.`from_date` = DATE'1986-06-26'))",
                    "attached_conditions_computation": [ ] /* attached_conditions_computation */,
                    "attached_conditions_summary": [
                      {
                        "table": "`salaries`",
                        "attached": "((`salaries`.`to_date` = DATE'1987-06-26') and (`salaries`.`from_date` = DATE'1986-06-26'))"
                      }
                    ] /* attached_conditions_summary */
                  } /* attaching_conditions_to_tables */
                },
                {
                  "finalizing_table_conditions": [
                    {
                      "table": "`salaries`",
                      "original_table_condition": "((`salaries`.`to_date` = DATE'1987-06-26') and (`salaries`.`from_date` = DATE'1986-06-26'))",
                      "final_table_condition": null
                    }
                  ] /* finalizing_table_conditions */
                },
                {
                  "refine_plan": [
                    {"table": "`salaries`"}
                  ] /* refine_plan */
                }
              ] /* steps */
            } /* join_optimization */
          },
          {
            "join_execution": {
              "select#": 1,
              "steps": [] /* steps */} /* join_execution */
          }
        ] /* steps */
      }
      MISSING_BYTES_BEYOND_MAX_MEM_SIZE: 0
                INSUFFICIENT_PRIVILEGES: 0
      1 row in set (0.00 sec)
  • 剖析实现,敞开 OPTIMIZER_TRACE

    SET optimizer_trace="enabled=off";

OPTIMIZER_TRACE 后果剖析

由下面的后果可知,OPTIMIZER_TRACE 有四个字段:

  • QUERY:查问语句
  • TRACE:QUERY 字段对应语句的跟踪信息
  • MISSING_BYTES_BEYOND_MAX_MEM_SIZE:跟踪信息过长时,被截断的跟踪信息的字节数。
  • INSUFFICIENT_PRIVILEGES:执行跟踪语句的用户是否有查看对象的权限。当不具备权限时,该列信息为 1 且 TRACE 字段为空,个别在调用带有 SQL SECURITY DEFINER 的视图或者是存储过程的状况下,会呈现此问题。

TIPS

参考:https://dev.mysql.com/doc/ref…

最外围的是 TRACE 字段的内容。咱们逐段剖析:

join_preparation

join_preparation 段落展现了筹备阶段的执行过程。

{
  "join_preparation": {
    "select#": 1,
    "steps": [
      {
        -- 比照下原始语句,能够晓得,这一步做了个格式化。"expanded_query": "/* select#1 */ select `salaries`.`emp_no` AS `emp_no`,`salaries`.`salary` AS `salary`,`salaries`.`from_date` AS `from_date`,`salaries`.`to_date` AS `to_date` from `salaries` where ((`salaries`.`from_date` ='1986-06-26') and (`salaries`.`to_date` ='1987-06-26'))"
      }
    ]
    /* steps */
  }
  /* join_preparation */
}

join_optimization

join_optimization 展现了优化阶段的执行过程,是剖析 OPTIMIZER TRACE 的重点。这段内容超级长,而且分了好多步骤,无妨依照步骤逐段剖析:

condition_processing

该段用来做条件解决,次要对 WHERE 条件进行优化解决。

"condition_processing": {
  "condition": "WHERE",
  "original_condition": "((`salaries`.`from_date` ='1986-06-26') and (`salaries`.`to_date` ='1987-06-26'))",
  "steps": [
    {
      "transformation": "equality_propagation",
      "resulting_condition": "(multiple equal('1986-06-26', `salaries`.`from_date`) and multiple equal('1987-06-26', `salaries`.`to_date`))"
    },
    {
      "transformation": "constant_propagation",
      "resulting_condition": "(multiple equal('1986-06-26', `salaries`.`from_date`) and multiple equal('1987-06-26', `salaries`.`to_date`))"
    },
    {
      "transformation": "trivial_condition_removal",
      "resulting_condition": "(multiple equal(DATE'1986-06-26', `salaries`.`from_date`) and multiple equal(DATE'1987-06-26', `salaries`.`to_date`))"
    }
  ] /* steps */
} /* condition_processing */

其中:

  • condition:优化对象类型。WHERE 条件句或者是 HAVING 条件句
  • original_condition:优化前的原始语句
  • steps:次要包含三步,别离是 quality_propagation(等值条件句转换),constant_propagation(常量条件句转换),trivial_condition_removal(有效条件移除的转换)

    • transformation:转换类型句
    • resulting_condition:转换之后的后果输入

substitute_generated_columns

substitute_generated_columns 用于替换虚构生成列

"substitute_generated_columns": {} /* substitute_generated_columns */

table_dependencies

剖析表之间的依赖关系

{
  "table_dependencies": [
    {
      "table": "`salaries`",
      "row_may_be_null": false,
      "map_bit": 0,
      "depends_on_map_bits": [] /* depends_on_map_bits */}
  ] /* table_dependencies */
}

其中:

  • table:波及的表名,如果有别名,也会展现进去
  • row_may_be_null:行是否可能为 NULL,这里是指 JOIN 操作之后,这张表里的数据是不是可能为 NULL。如果语句中应用了 LEFT JOIN,则后一张表的 row_may_be_null 会显示为 true
  • map_bit:表的映射编号,从 0 开始递增
  • depends_on_map_bits:依赖的映射表。次要是当应用 STRAIGHT_JOIN 强行管制连贯程序或者 LEFT JOIN/RIGHT JOIN 有程序差异时,会在 depends_on_map_bits 中展现前置表的 map_bit 值。

ref_optimizer_key_uses

列出所有可用的 ref 类型的索引。如果应用了组合索引的多个局部(例如本例,用到了 index(from_date, to_date) 的多列索引),则会在 ref_optimizer_key_uses 下列出多个元素,每个元素中会列出 ref 应用的索引及对应值。

{
  "ref_optimizer_key_uses": [
    {
      "table": "`salaries`",
      "field": "from_date",
      "equals": "DATE'1986-06-26'","null_rejecting": false
    },
    {
      "table": "`salaries`",
      "field": "to_date",
      "equals": "DATE'1987-06-26'","null_rejecting": false
    }
  ] /* ref_optimizer_key_uses */
}

rows_estimation

顾名思义,用于估算须要扫描的记录数。

{
  "rows_estimation": [
    {
      "table": "`salaries`",
      "range_analysis": {
        "table_scan": {
          "rows": 2838216,
          "cost": 286799
        } /* table_scan */,
        "potential_range_indexes": [
          {
            "index": "PRIMARY",
            "usable": false,
            "cause": "not_applicable"
          },
          {
            "index": "salaries_from_date_to_date_index",
            "usable": true,
            "key_parts": [
              "from_date",
              "to_date",
              "emp_no"
            ] /* key_parts */
          }
        ] /* potential_range_indexes */,
        "setup_range_conditions": [ ] /* setup_range_conditions */,
        "group_index_range": {
          "chosen": false,
          "cause": "not_group_by_or_distinct"
        } /* group_index_range */,
        "skip_scan_range": {
          "potential_skip_scan_indexes": [
            {
              "index": "salaries_from_date_to_date_index",
              "usable": false,
              "cause": "query_references_nonkey_column"
            }
          ] /* potential_skip_scan_indexes */
        } /* skip_scan_range */,
        "analyzing_range_alternatives": {
          "range_scan_alternatives": [
            {
              "index": "salaries_from_date_to_date_index",
              "ranges": ["0xda840f <= from_date <= 0xda840f AND 0xda860f <= to_date <= 0xda860f"] /* ranges */,
              "index_dives_for_eq_ranges": true,
              "rowid_ordered": true,
              "using_mrr": false,
              "index_only": false,
              "rows": 86,
              "cost": 50.909,
              "chosen": true
            }
          ] /* range_scan_alternatives */,
          "analyzing_roworder_intersect": {
            "usable": false,
            "cause": "too_few_roworder_scans"
          } /* analyzing_roworder_intersect */
        } /* analyzing_range_alternatives */,
        "chosen_range_access_summary": {
          "range_access_plan": {
            "type": "range_scan",
            "index": "salaries_from_date_to_date_index",
            "rows": 86,
            "ranges": ["0xda840f <= from_date <= 0xda840f AND 0xda860f <= to_date <= 0xda860f"] /* ranges */
          } /* range_access_plan */,
          "rows_for_plan": 86,
          "cost_for_plan": 50.909,
          "chosen": true
        } /* chosen_range_access_summary */
      } /* range_analysis */
    }
  ] /* rows_estimation */
}

其中:

  • table:表名
  • range_analysis:

    • table_scan:如果全表扫描的话,须要扫描多少行(row,2838216),以及须要的代价(cost,286799)
    • potential_range_indexes:列出表中所有的索引并剖析其是否可用。如果不可用的话,会列出不可用的起因是什么;如果可用会列出索引中可用的字段;
    • setup_range_conditions:如果有可下推的条件,则带条件思考范畴查问
    • group_index_range:当应用了 GROUP BY 或 DISTINCT 时,是否有适合的索引可用。当未应用 GROUP BY 或 DISTINCT 时,会显示 chosen=false, cause=not_group_by_or_distinct;如应用了 GROUP BY 或 DISTINCT,然而多表查问时,会显示 chosen=false,cause =not_single_table。其余状况下会尝试剖析可用的索引(potential_group_range_indexes)并计算对应的扫描行数及其所需代价
    • skip_scan_range:是否应用了 skip scan

      TIPS

      skip_scan_range 是 MySQL 8.0 的新个性,感兴趣的可详见 https://blog.csdn.net/weixin_…

    • analyzing_range_alternatives:剖析各个索引的应用老本

      • range_scan_alternatives:range 扫描剖析

        • index:索引名
        • ranges:range 扫描的条件范畴
        • index_dives_for_eq_ranges:是否应用了 index dive,该值会被参数 eq_range_index_dive_limit 变量值影响。
        • rowid_ordered:该 range 扫描的后果集是否依据 PK 值进行排序
        • using_mrr:是否应用了 mrr
        • index_only:示意是否应用了笼罩索引
        • rows:扫描的行数
        • cost:索引的应用老本
        • chosen:示意是否应用了该索引
      • analyzing_roworder_intersect:剖析是否应用了索引合并(index merge),如果未应用,会在 cause 中展现起因;如果应用了索引合并,会在该局部展现索引合并的代价。
    • chosen_range_access_summary:在前一个步骤中剖析了各类索引应用的办法及代价,得出了肯定的两头后果之后,在 summary 阶段汇总前一阶段的两头后果确认最初的计划

      • range_access_plan:range 扫描最终抉择的执行打算。

        • type:展现执行打算的 type,如果应用了索引合并,则会显示 index_roworder_intersect
        • index:索引名
        • rows:扫描的行数
        • ranges:range 扫描的条件范畴
      • rows_for_plan:该执行打算的扫描行数
      • cost_for_plan:该执行打算的执行代价
      • chosen:是否抉择该执行打算

considered_execution_plans

负责比照各可行打算的开销,并抉择绝对最优的执行打算。

{
  "considered_execution_plans": [
    {"plan_prefix": [] /* plan_prefix */,
      "table": "`salaries`",
      "best_access_path": {
        "considered_access_paths": [
          {
            "access_type": "ref",
            "index": "salaries_from_date_to_date_index",
            "rows": 86,
            "cost": 50.412,
            "chosen": true
          },
          {
            "access_type": "range",
            "range_details": {"used_index": "salaries_from_date_to_date_index"} /* range_details */,
            "chosen": false,
            "cause": "heuristic_index_cheaper"
          }
        ] /* considered_access_paths */
      } /* best_access_path */,
      "condition_filtering_pct": 100,
      "rows_for_plan": 86,
      "cost_for_plan": 50.412,
      "chosen": true
    }
  ] /* considered_execution_plans */
}

其中:

  • plan_prefix:以后打算的前置执行打算。
  • table:波及的表名,如果有别名,也会展现进去
  • best_access_path:通过比照 considered_access_paths,抉择一个最优的拜访门路

    • considered_access_paths:以后思考的拜访门路

      • access_type:应用索引的形式,可参考 explain 中的 type 字段
      • index:索引
      • rows:行数
      • cost:开销
      • chosen:是否选用这种执行门路
  • condition_filtering_pct:相似于 explain 的 filtered 列,是一个估算值
  • rows_for_plan:执行打算最终的扫描行数,由 considered_access_paths.rows X condition_filtering_pct 计算取得。
  • cost_for_plan:执行打算的代价,由 considered_access_paths.cost 相加取得
  • chosen:是否抉择了该执行打算

attaching_conditions_to_tables

基于 considered_execution_plans 中抉择的执行打算,革新原有 where 条件,并针对表减少适当的附加条件,以便于单表数据的筛选。

TIPS

  • 这部分条件的减少次要是为了便于 ICP(索引条件下推),但 ICP 是否开启并不影响这部分内容的结构。
  • ICP 参考文档:https://www.cnblogs.com/Terry…
{
  "attaching_conditions_to_tables": {"original_condition": "((`salaries`.`to_date` = DATE'1987-06-26') and (`salaries`.`from_date` = DATE'1986-06-26'))",
    "attached_conditions_computation": [ ] /* attached_conditions_computation */,
    "attached_conditions_summary": [
      {
        "table": "`salaries`",
        "attached": "((`salaries`.`to_date` = DATE'1987-06-26') and (`salaries`.`from_date` = DATE'1986-06-26'))"
      }
    ] /* attached_conditions_summary */
  } /* attaching_conditions_to_tables */
}

其中:

  • original_condition:原始的条件语句
  • attached_conditions_computation:应用启发式算法计算已应用的索引,如果已应用的索引的拜访类型是 ref,则计算用 range 是否应用组合索引中更多的列,如果能够,则用 range 的形式替换 ref。
  • attached_conditions_summary:附加之后的状况汇总

    • table:表名
    • attached:附加的条件或原语句中能间接下推给单表筛选的条件。

finalizing_table_conditions

最终的、通过优化后的表条件。

{
  "finalizing_table_conditions": [
    {
      "table": "`salaries`",
      "original_table_condition": "((`salaries`.`to_date` = DATE'1987-06-26') and (`salaries`.`from_date` = DATE'1986-06-26'))",
      "final_table_condition": null
    }
  ] /* finalizing_table_conditions */
}

refine_plan

改善执行打算:

{
  "refine_plan": [
    {"table": "`salaries`"}
  ] /* refine_plan */
}

其中:

  • table:表名及别名

join_execution

join_execution 段落展现了执行阶段的执行过程。

"join_execution": {
  "select#": 1,
  "steps": [] /* steps */}

参考文档

  • Tracing the Optimizer
  • 手把手教你意识 OPTIMIZER_TRACE
  • MYSQL sql 执行过程的一些跟踪剖析 (二.mysql 优化器追踪剖析)
  • 应用 Trace 进行执行打算剖析

相干文章

  • 全网最全 | MySQL EXPLAIN 齐全解读
  • MySQL 建表语句转 PostgreSQL 建表语句全纪录

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