In years past, MySQL was a bit of a black box when it came to understanding what was happening and why. In MySQL 5.6 and 5.7, we’ve added many new features that provide much needed transparency and insight into the inner workings of MySQL. The single biggest feature was the new Performance Schema, but some other examples are:
- The ability to see what query generated a row based binary log event.
- The ability to see a tremendous amount of data points for InnoDB.
- The ability to see an extended query execution plan using EXPLAIN FORMAT=JSON (which can also now be used for running queries).
- The ability to see a query execution trace via the new optimizer trace functionality.
I’m going to focus on #3 and #4 here. This will hopefully whet your appetite for a webinar coming up where I will dive deeper into the EXPLAIN related features.
Toward that end, I’ll show you an example of the JSON formatted explain, an optimizer trace, and finally of Workbench’s Visual Explain. For all of these, I’ll be using the Sakila test database.
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mysql> explain format=json select `a`.`actor_id` AS `actor_id`,`a`.`first_name` AS `first_name`,`a`.`last_name` AS `last_name`,group_concat(distinct concat(`c`.`name`,': ',(select group_concat(`f`.`title` order by `f`.`title` ASC separator ', ') from ((`film` `f` join `film_category` `fc` on((`f`.`film_id` = `fc`.`film_id`))) join `film_actor` `fa` on((`f`.`film_id` = `fa`.`film_id`))) where ((`fc`.`category_id` = `c`.`category_id`) and (`fa`.`actor_id` = `a`.`actor_id`)))) order by `c`.`name` ASC separator '; ') AS `film_info` from (((`actor` `a` left join `film_actor` `fa` on((`a`.`actor_id` = `fa`.`actor_id`))) left join `film_category` `fc` on((`fa`.`film_id` = `fc`.`film_id`))) left join `category` `c` on((`fc`.`category_id` = `c`.`category_id`))) group by `a`.`actor_id`,`a`.`first_name`,`a`.`last_name`\G *************************** 1. row *************************** EXPLAIN: { "query_block": { "select_id": 1, "cost_info": { "query_cost": "9603.34" }, "grouping_operation": { "using_filesort": true, "cost_info": { "sort_cost": "2600.00" }, "nested_loop": [ { "table": { "table_name": "a", "access_type": "index", "possible_keys": [ "last_name", "ln_fn_idx" ], "key": "last_name", "used_key_parts": [ "last_name", "first_name" ], "key_length": "274", "rows_examined_per_scan": 200, "rows_produced_per_join": 200, "filtered": 100, "using_index": true, "cost_info": { "read_cost": "1.00", "eval_cost": "40.00", "prefix_cost": "41.00", "data_read_per_join": "54K" }, "used_columns": [ "actor_id", "first_name", "last_name" ] } }, { "table": { "table_name": "fa", "access_type": "ref", "possible_keys": [ "PRIMARY" ], "key": "PRIMARY", "used_key_parts": [ "actor_id" ], "key_length": "2", "ref": [ "sakila.a.actor_id" ], "rows_examined_per_scan": 13, "rows_produced_per_join": 2600, "filtered": 100, "using_index": true, "cost_info": { "read_cost": "202.34", "eval_cost": "520.00", "prefix_cost": "763.34", "data_read_per_join": "40K" }, "used_columns": [ "actor_id", "film_id" ] } }, { "table": { "table_name": "fc", "access_type": "ref", "possible_keys": [ "PRIMARY" ], "key": "PRIMARY", "used_key_parts": [ "film_id" ], "key_length": "2", "ref": [ "sakila.fa.film_id" ], "rows_examined_per_scan": 1, "rows_produced_per_join": 2600, "filtered": 100, "using_index": true, "cost_info": { "read_cost": "2600.00", "eval_cost": "520.00", "prefix_cost": "3883.34", "data_read_per_join": "40K" }, "used_columns": [ "film_id", "category_id" ] } }, { "table": { "table_name": "c", "access_type": "eq_ref", "possible_keys": [ "PRIMARY" ], "key": "PRIMARY", "used_key_parts": [ "category_id" ], "key_length": "1", "ref": [ "sakila.fc.category_id" ], "rows_examined_per_scan": 1, "rows_produced_per_join": 2600, "filtered": 100, "cost_info": { "read_cost": "2600.00", "eval_cost": "520.00", "prefix_cost": "7003.34", "data_read_per_join": "223K" }, "used_columns": [ "category_id", "name" ] } } ], "select_list_subqueries": [ { "dependent": true, "cacheable": false, "query_block": { "select_id": 2, "cost_info": { "query_cost": "34.81" }, "nested_loop": [ { "table": { "table_name": "fa", "access_type": "ref", "possible_keys": [ "PRIMARY", "idx_fk_film_id" ], "key": "PRIMARY", "used_key_parts": [ "actor_id" ], "key_length": "2", "ref": [ "sakila.a.actor_id" ], "rows_examined_per_scan": 13, "rows_produced_per_join": 13, "filtered": 100, "using_index": true, "cost_info": { "read_cost": "1.01", "eval_cost": "2.60", "prefix_cost": "3.61", "data_read_per_join": "208" }, "used_columns": [ "actor_id", "film_id" ] } }, { "table": { "table_name": "f", "access_type": "eq_ref", "possible_keys": [ "PRIMARY" ], "key": "PRIMARY", "used_key_parts": [ "film_id" ], "key_length": "2", "ref": [ "sakila.fa.film_id" ], "rows_examined_per_scan": 1, "rows_produced_per_join": 13, "filtered": 100, "cost_info": { "read_cost": "13.00", "eval_cost": "2.60", "prefix_cost": "19.21", "data_read_per_join": "10K" }, "used_columns": [ "film_id", "title" ] } }, { "table": { "table_name": "fc", "access_type": "eq_ref", "possible_keys": [ "PRIMARY", "fk_film_category_category" ], "key": "PRIMARY", "used_key_parts": [ "film_id", "category_id" ], "key_length": "3", "ref": [ "sakila.fa.film_id", "sakila.c.category_id" ], "rows_examined_per_scan": 1, "rows_produced_per_join": 13, "filtered": 100, "using_index": true, "cost_info": { "read_cost": "13.00", "eval_cost": "2.60", "prefix_cost": "34.81", "data_read_per_join": "208" }, "used_columns": [ "film_id", "category_id" ] } } ] } } ] } } } 1 row in set, 3 warnings (0.02 sec) |
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mysql> SET OPTIMIZER_TRACE="enabled=on",END_MARKERS_IN_JSON=on; # be readable Query OK, 0 rows affected (0.00 sec) mysql> SET OPTIMIZER_TRACE_MAX_MEM_SIZE=90000000; # avoid small default Query OK, 0 rows affected (0.00 sec) mysql> select `a`.`actor_id` AS `actor_id`,`a`.`first_name` AS `first_name`,`a`.`last_name` AS `last_name`,group_concat(distinct concat(`c`.`name`,': ',(/* select#2 */ select group_concat(`f`.`title` order by `f`.`title` ASC separator ', ') from `sakila`.`film` `f` join `sakila`.`film_category` `fc` join `sakila`.`film_actor` `fa` where ((`f`.`film_id` = `fa`.`film_id`) and (`fc`.`film_id` = `fa`.`film_id`) and (`fc`.`category_id` = `c`.`category_id`) and (`fa`.`actor_id` = `a`.`actor_id`)))) order by `c`.`name` ASC separator '; ') AS `film_info` from `sakila`.`actor` `a` left join `sakila`.`film_actor` `fa` on((`a`.`actor_id` = `fa`.`actor_id`)) left join `sakila`.`film_category` `fc` on((`fa`.`film_id` = `fc`.`film_id`)) left join `sakila`.`category` `c` on((`fc`.`category_id` = `c`.`category_id`)) where 1 group by `a`.`actor_id`,`a`.`first_name`,`a`.`last_name`; +----------+-------------+--------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ | actor_id | first_name | last_name | film_info | +----------+-------------+--------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ | 1 | PENELOPE | GUINESS | Animation: ANACONDA CONFESSIONS; Children: LANGUAGE COWBOY; Classics: COLOR PHILADELPHIA, WESTWARD SEABISCUIT; Comedy: VERTIGO NORTHWEST; Documentary: ACADEMY DINOSAUR; Family: KING EVOLUTION, SPLASH GUMP; Foreign: MULHOLLAND BEAST; Games: BULWORTH COMMANDMENTS, HUMAN GRAFFITI; Horror: ELEPHANT TROJAN, LADY STAGE, RULES HUMAN; Music: WIZARD COLDBLOODED; New: ANGELS LIFE, OKLAHOMA JUMANJI; Sci-Fi: CHEAPER CLYDE; Sports: GLEAMING JAWBREAKER ... | 200 | THORA | TEMPLE | Animation: CAROL TEXAS; Children: CHRISTMAS MOONSHINE, WRONG BEHAVIOR; Classics: CANDIDATE PERDITION, GALAXY SWEETHEARTS, LOVER TRUMAN; Documentary: MADISON TRAP, VIRGINIAN PLUTO; Drama: WARDROBE PHANTOM; Family: AFRICAN EGG, BLANKET BEVERLY, HOCUS FRIDA; Music: INSIDER ARIZONA, TELEGRAPH VOYAGE; New: INTERVIEW LIAISONS, LOVERBOY ATTACKS; Sci-Fi: BADMAN DAWN, RANDOM GO, TROJAN TOMORROW; Sports: JADE BUNCH | +----------+-------------+--------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ 200 rows in set (0.44 sec) mysql> select * from information_schema.optimizer_trace\G *************************** 1. row *************************** QUERY: select `a`.`actor_id` AS `actor_id`,`a`.`first_name` AS `first_name`,`a`.`last_name` AS `last_name`,group_concat(distinct concat(`c`.`name`,': ',( select group_concat(`f`.`title` order by `f`.`title` ASC separator ', ') from `sakila`.`film` `f` join `sakila`.`film_category` `fc` join `sakila`.`film_actor` `fa` where ((`f`.`film_id` = `fa`.`film_id`) and (`fc`.`film_id` = `fa`.`film_id`) and (`fc`.`category_id` = `c`.`category_id`) and (`fa`.`actor_id` = `a`.`actor_id`)))) order by `c`.`name` ASC separator '; ') AS `film_info` from `sakila`.`actor` `a` left join `sakila`.`film_actor` `fa` on((`a`.`actor_id` = `fa`.`actor_id`)) left join `sakila`.`film_category` `fc` on((`fa`.`film_id` = `fc`.`film_id`)) left join `sakila`.`category` `c` on((`fc`.`category_id` = `c`.`category_id`)) where 1 group by `a`.`actor_id`,`a`.`first_name`,`a`.`last_name` TRACE: { "steps": [ { "join_preparation": { "select#": 1, "steps": [ { "join_preparation": { "select#": 2, "steps": [ { "expanded_query": "/* select#2 */ select group_concat(`f`.`title` order by `f`.`title` ASC separator ', ') from ((`film` `f` join `film_category` `fc`) join `film_actor` `fa`) where ((`f`.`film_id` = `fa`.`film_id`) and (`fc`.`film_id` = `fa`.`film_id`) and (`fc`.`category_id` = `c`.`category_id`) and (`fa`.`actor_id` = `a`.`actor_id`))" } ] /* steps */ } /* join_preparation */ }, { "expanded_query": "/* select#1 */ select `a`.`actor_id` AS `actor_id`,`a`.`first_name` AS `first_name`,`a`.`last_name` AS `last_name`,group_concat(distinct concat(`c`.`name`,': ',(/* select#2 */ select group_concat(`f`.`title` order by `f`.`title` ASC separator ', ') from ((`film` `f` join `film_category` `fc`) join `film_actor` `fa`) where ((`f`.`film_id` = `fa`.`film_id`) and (`fc`.`film_id` = `fa`.`film_id`) and (`fc`.`category_id` = `c`.`category_id`) and (`fa`.`actor_id` = `a`.`actor_id`)))) order by `c`.`name` ASC separator '; ') AS `film_info` from (((`actor` `a` left join `film_actor` `fa` on((`a`.`actor_id` = `fa`.`actor_id`))) left join `film_category` `fc` on((`fa`.`film_id` = `fc`.`film_id`))) left join `category` `c` on((`fc`.`category_id` = `c`.`category_id`))) where 1 group by `a`.`actor_id`,`a`.`first_name`,`a`.`last_name`" }, { "transformations_to_nested_joins": { "transformations": [ "parenthesis_removal" ] /* transformations */, "expanded_query": "/* select#2 */ select group_concat(`f`.`title` order by `f`.`title` ASC separator ', ') from `film` `f` join `film_category` `fc` join `film_actor` `fa` where ((`f`.`film_id` = `fa`.`film_id`) and (`fc`.`film_id` = `fa`.`film_id`) and (`fc`.`category_id` = `c`.`category_id`) and (`fa`.`actor_id` = `a`.`actor_id`))" } /* transformations_to_nested_joins */ }, { "transformations_to_nested_joins": { "transformations": [ "parenthesis_removal" ] /* transformations */, "expanded_query": "/* select#1 */ select `a`.`actor_id` AS `actor_id`,`a`.`first_name` AS `first_name`,`a`.`last_name` AS `last_name`,group_concat(distinct concat(`c`.`name`,': ',(/* select#2 */ select group_concat(`f`.`title` order by `f`.`title` ASC separator ', ') from `film` `f` join `film_category` `fc` join `film_actor` `fa` where ((`f`.`film_id` = `fa`.`film_id`) and (`fc`.`film_id` = `fa`.`film_id`) and (`fc`.`category_id` = `c`.`category_id`) and (`fa`.`actor_id` = `a`.`actor_id`)))) order by `c`.`name` ASC separator '; ') AS `film_info` from `actor` `a` left join `film_actor` `fa` on((`a`.`actor_id` = `fa`.`actor_id`)) left join `film_category` `fc` on((`fa`.`film_id` = `fc`.`film_id`)) left join `category` `c` on((`fc`.`category_id` = `c`.`category_id`)) where 1 group by `a`.`actor_id`,`a`.`first_name`,`a`.`last_name`" } /* transformations_to_nested_joins */ } ] /* steps */ } /* join_preparation */ }, { "join_optimization": { "select#": 1, "steps": [ { "condition_processing": { "condition": "WHERE", "original_condition": "1", "steps": [ { "transformation": "equality_propagation", "resulting_condition": "1" }, { "transformation": "constant_propagation", "resulting_condition": "1" }, { "transformation": "trivial_condition_removal", "resulting_condition": null } ] /* steps */ } /* condition_processing */ }, { "table_dependencies": [ { "table": "`actor` `a`", "row_may_be_null": false, "map_bit": 0, "depends_on_map_bits": [ ] /* depends_on_map_bits */ }, { "table": "`film_actor` `fa`", "row_may_be_null": true, "map_bit": 1, "depends_on_map_bits": [ 0 ] /* depends_on_map_bits */ }, { "table": "`film_category` `fc`", "row_may_be_null": true, "map_bit": 2, "depends_on_map_bits": [ 0, 1 ] /* depends_on_map_bits */ }, { "table": "`category` `c`", "row_may_be_null": true, "map_bit": 3, "depends_on_map_bits": [ 0, 1, 2 ] /* depends_on_map_bits */ } ] /* table_dependencies */ }, { "ref_optimizer_key_uses": [ { "table": "`film_actor` `fa`", "field": "actor_id", "equals": "`a`.`actor_id`", "null_rejecting": false }, { "table": "`film_category` `fc`", "field": "film_id", "equals": "`fa`.`film_id`", "null_rejecting": true }, { "table": "`category` `c`", "field": "category_id", "equals": "`fc`.`category_id`", "null_rejecting": true } ] /* ref_optimizer_key_uses */ }, { "rows_estimation": [ { "table": "`actor` `a`", "const_keys_added": { "keys": [ "last_name", "ln_fn_idx" ] /* keys */, "cause": "group_by" } /* const_keys_added */, "range_analysis": { "table_scan": { "rows": 200, "cost": 43.1 } /* table_scan */, "potential_range_indexes": [ { "index": "PRIMARY", "usable": false, "cause": "not_applicable" }, { "index": "idx_actor_last_name", "usable": false, "cause": "not_applicable" }, { "index": "first_name", "usable": false, "cause": "not_applicable" }, { "index": "last_name", "usable": true, "key_parts": [ "last_name", "first_name", "actor_id" ] /* key_parts */ }, { "index": "ln_fn_idx", "usable": true, "key_parts": [ "last_name", "first_name", "actor_id" ] /* key_parts */ } ] /* potential_range_indexes */, "best_covering_index_scan": { "index": "last_name", "cost": 47.633, "chosen": false, "cause": "cost" } /* best_covering_index_scan */, "group_index_range": { "chosen": false, "cause": "not_single_table" } /* group_index_range */ } /* range_analysis */ }, { "table": "`film_actor` `fa`", "table_scan": { "rows": 5462, "cost": 12 } /* table_scan */ }, { "table": "`film_category` `fc`", "table_scan": { "rows": 1000, "cost": 4 } /* table_scan */ }, { "table": "`category` `c`", "table_scan": { "rows": 16, "cost": 1 } /* table_scan */ } ] /* rows_estimation */ }, { "considered_execution_plans": [ { "plan_prefix": [ ] /* plan_prefix */, "table": "`actor` `a`", "best_access_path": { "considered_access_paths": [ { "rows_to_scan": 200, "access_type": "scan", "resulting_rows": 200, "cost": 41, "chosen": true, "use_tmp_table": true } ] /* considered_access_paths */ } /* best_access_path */, "condition_filtering_pct": 100, "rows_for_plan": 200, "cost_for_plan": 41, "rest_of_plan": [ { "plan_prefix": [ "`actor` `a`" ] /* plan_prefix */, "table": "`film_actor` `fa`", "best_access_path": { "considered_access_paths": [ { "access_type": "ref", "index": "PRIMARY", "rows": 13, "cost": 722.34, "chosen": true }, { "access_type": "scan", "chosen": false, "cause": "covering_index_better_than_full_scan" } ] /* considered_access_paths */ } /* best_access_path */, "condition_filtering_pct": 100, "rows_for_plan": 2600, "cost_for_plan": 763.34, "rest_of_plan": [ { "plan_prefix": [ "`actor` `a`", "`film_actor` `fa`" ] /* plan_prefix */, "table": "`film_category` `fc`", "best_access_path": { "considered_access_paths": [ { "access_type": "ref", "index": "PRIMARY", "rows": 1, "cost": 3120, "chosen": true }, { "access_type": "scan", "chosen": false, "cause": "covering_index_better_than_full_scan" } ] /* considered_access_paths */ } /* best_access_path */, "condition_filtering_pct": 100, "rows_for_plan": 2600, "cost_for_plan": 3883.3, "rest_of_plan": [ { "plan_prefix": [ "`actor` `a`", "`film_actor` `fa`", "`film_category` `fc`" ] /* plan_prefix */, "table": "`category` `c`", "best_access_path": { "considered_access_paths": [ { "access_type": "eq_ref", "index": "PRIMARY", "rows": 1, "cost": 3120, "chosen": true, "cause": "clustered_pk_chosen_by_heuristics" }, { "rows_to_scan": 16, "access_type": "scan", "using_join_cache": true, "buffers_needed": 3, "resulting_rows": 16, "cost": 8323.8, "chosen": false } ] /* considered_access_paths */ } /* best_access_path */, "added_to_eq_ref_extension": true, "condition_filtering_pct": 100, "rows_for_plan": 2600, "cost_for_plan": 7003.3, "sort_cost": 2600, "new_cost_for_plan": 9603.3, "chosen": true } ] /* rest_of_plan */ } ] /* rest_of_plan */ } ] /* rest_of_plan */ } ] /* considered_execution_plans */ }, { "condition_on_constant_tables": "1", "condition_value": true }, { "attaching_conditions_to_tables": { "original_condition": "1", "attached_conditions_computation": [ ] /* attached_conditions_computation */, "attached_conditions_summary": [ { "table": "`actor` `a`", 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`fa`", "`film` `f`" ] /* plan_prefix */, "table": "`film_category` `fc`", "best_access_path": { "considered_access_paths": [ { "access_type": "eq_ref", "index": "PRIMARY", "rows": 1, "cost": 15.6, "chosen": true, "cause": "clustered_pk_chosen_by_heuristics" }, { "access_type": "scan", "chosen": false, "cause": "covering_index_better_than_full_scan" } ] /* considered_access_paths */ } /* best_access_path */, "added_to_eq_ref_extension": true, "condition_filtering_pct": 100, "rows_for_plan": 13, "cost_for_plan": 34.812, "chosen": true } ] /* rest_of_plan */ } } ] /* rest_of_plan */ } ] /* considered_execution_plans */ }, { "attaching_conditions_to_tables": { "original_condition": "((`f`.`film_id` = `fa`.`film_id`) and (`fc`.`film_id` = `fa`.`film_id`) and (`fc`.`category_id` = `c`.`category_id`) and (`fa`.`actor_id` = `a`.`actor_id`))", "attached_conditions_computation": [ ] /* attached_conditions_computation */, "attached_conditions_summary": [ { "table": "`film_actor` `fa`", 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false, "cause": "not applicable (no LIMIT)" } /* filesort_priority_queue_optimization */, "filesort_execution": [ ] /* filesort_execution */, "filesort_summary": { "rows": 200, "examined_rows": 200, "number_of_tmp_files": 0, "sort_buffer_size": 261896, "sort_mode": "" } /* filesort_summary */ }, { "subselect_execution": { "select#": 2, "select#": 2, "steps": [ { "join_execution": { "select#": 2, "steps": [ ] /* steps */ } /* join_execution */ } ] /* steps */ } /* subselect_execution */ }, ...# repeats for each row { "subselect_execution": { "select#": 2, "steps": [ { "join_execution": { "select#": 2, "steps": [ ] /* steps */ } /* join_execution */ } ] /* steps */ } /* subselect_execution */ } ] /* steps */ } /* join_execution */ } ] /* steps */ } MISSING_BYTES_BEYOND_MAX_MEM_SIZE: 0 INSUFFICIENT_PRIVILEGES: 0 1 row in set (0.01 sec) |
Workbench Visual Explain
These new insights also allow for clients to provide additional visual representations of this data. The new Visual Explain functionality in MySQL Workbench 6.1 is a great example. Let’s look at that query again:
Conclusion
Again, if all of this looks interesting, but a bit overwhelming, then please join Matt and I for our webinar coming up this month.