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Efficient MySQL Indexing &
What's New in MySQL Explain
Presented by
Jebashalomie Immanuel
Mydbops
Mydbops MyWebinar - 32
May 11th, 2024
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About Us
Agenda
❏ Index Overview
❏ Types of Indexes
❏ Increasing Indexing Efficiency
❏ Example
❏ Before Optimization
❏ Optimization
❏ After Optimization
❏ New Features
❏ Capturing EXPLAIN FORMAT=JSON Output
❏ explain_json_format_version
Index Overview
Index Overview
❏ Enhances data retrieval speed, uses extra space.
❏ Created on table columns, choosing the right index is vital.
❏ Needs regular updates to stay efficient.
❏ Index types: Includes primary, unique, composite, and full-text.
Types of Indexes
Types of Indexes
Increasing Index Efficiency
Increasing Index Efficiency
❏ Analysing the queries
❏ Avoid over indexing
❏ Analyze the cardinality
❏ Pick the correct columns
❏ Pick the suitable index
❏ Regular maintenance
Example
Example
Datatype:
column1 - text
Query:
SELECT * FROM test_function WHERE column1 LIKE
'flexibility';
Total rows: 96
Before Optimization
Before Optimization
mysql> explain SELECT * FROM test_function WHERE column1 LIKE 'flexibility'G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: test_function
partitions: NULL
type: ALL
possible_keys: NULL
key: NULL
key_len: NULL
ref: NULL
rows: 96
filtered: 11.11
Extra: Using where
Optimization
Index creation:
mysql> Alter table test_function add fulltext index idx_column1(column1);
Query OK, 0 rows affected, 1 warning (0.20 sec)
mysql> explain SELECT * FROM test_function WHERE column1 LIKE 'flexibility';
+----+-------------+---------------+------------+------+---------------+------+---------+------+-
-----+----------+-------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref |
rows | filtered | Extra |
+----+-------------+---------------+------------+------+---------------+------+---------+------+-
-----+----------+-------------+
| 1 | SIMPLE | test_function | NULL | ALL | idx_column1 | NULL | NULL | NULL |
96 | 11.11 | Using where |
+----+-------------+---------------+------------+------+---------------+------+---------+------+-
-----+----------+-------------+
After Optimization
After Optimization
mysql> EXPLAIN SELECT * FROM test_function WHERE MATCH(column1) AGAINST
('flexibility')G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: test_function
partitions: NULL
type: fulltext
possible_keys: idx_column1
key: idx_column1
key_len: 0
ref: const
rows: 1
filtered: 100.00
Extra: Using where; Ft_hints: sorted
1 row in set, 1 warning (0.00 sec)
mysql> EXPLAIN SELECT * FROM test_function WHERE MATCH(column1) AGAINST ('flexibility')G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: test_function
partitions: NULL
type: fulltext
possible_keys: idx_column1
key: idx_column1
key_len: 0
ref: const
rows: 1
filtered: 100.00
Extra: Using where; Ft_hints: sorted
1 row in set, 1 warning (0.00 sec)
New Features
❏ Capturing EXPLAIN FORMAT=JSON output (MySQL 8.1.0)
❏ explain_json_format_version (MySQL 8.3.0)
Capturing EXPLAIN FORMAT=JSON Output
Query:
mysql> EXPLAIN FORMAT=JSON INTO @myvar SELECT * FROM city WHERE
District='Texas';
Query OK, 0 rows affected (0.00 sec)
mysql> EXPLAIN FORMAT=JSON INTO @myvar SELECT * FROM city WHERE
District='Texas';
Query OK, 0 rows affected (0.00 sec)
mysql> select @myvarG
*************************** 1. row ***************************
@myvar: {
"query_block": {
"select_id": 1,
"cost_info": {
"query_cost": "428.50"
},
"table": {
"table_name": "city",
"access_type": "ALL",
"rows_examined_per_scan": 4035,
"rows_produced_per_join": 403,
"filtered": "10.00",
"cost_info": {
"read_cost": "388.15",
"eval_cost": "40.35",
"prefix_cost": "428.50",
"data_read_per_join": "97K"
},
"used_columns": [
"ID",
"Name",
"CountryCode",
"District",
"Population"
],
"attached_condition": "(`world`.`city`.`District` = 'Texas')"}}
1 row in set (0.00 sec)
explain_json_format_version variable
● Two versions available for EXPLAIN FORMAT=JSON.
● Version 2 reveals optimizer access paths.
● Ensures compatibility with upcoming MySQL Optimizer.
● Supports the JSON output format for EXPLAIN statements.
Version 1
Validation of the variable:
mysql> select @@explain_json_format_version;
+-------------------------------+
| @@explain_json_format_version |
+-------------------------------+
| 1 |
+-------------------------------+
mysql> select @@explain_json_format_version;
+-------------------------------+
| @@explain_json_format_version |
+-------------------------------+
| 1 |
+-------------------------------+
mysql> Explain format = JSON select ID, Name, CountryCode, District,
Population from city where Population between 127800 and 137500G
*************************** 1. row ***************************
EXPLAIN: {
"query_block": {
"select_id": 1,
"cost_info": {
"query_cost": "409.75"
},
"table": {
"table_name": "city",
"access_type": "ALL",
"rows_examined_per_scan": 4035,
"rows_produced_per_join": 448,
"filtered": "11.11",
"cost_info": {
"read_cost": "364.92",
"eval_cost": "44.83",
"prefix_cost": "409.75",
"data_read_per_join": "108K"
},
"used_columns": [
"ID", "Name","CountryCode", "District",
"Population"
],
"attached_condition": "(`world`.`city`.`Population` between 127800 and 137500)”} } }
Version 2
Setting the variable:
mysql> SET @@explain_json_format_version = 2;
Query OK, 0 rows affected (0.00 sec)
mysql> Explain format = JSON select ID, Name, CountryCode, District, Population
from city where Population between 127800 and 137500G
*************************** 1. row ***************************
EXPLAIN: {
"query": "/* select#1 */ select `world`.`city`.`ID` AS `ID`,`world`.`city`.`Name` AS
`Name`,`world`.`city`.`CountryCode` AS `CountryCode`,`world`.`city`.`District` AS
`District`,`world`.`city`.`Population` AS `Population` from `world`.`city` where (`world`.`city`.`Population`
between 127800 and 137500)",
"inputs": [
{
"operation": "Table scan on city",
"table_name": "city",
"access_type": "table",
"schema_name": "world",
"used_columns": [
"ID",
"Name",
"CountryCode",
"District",
"Population"
],
"estimated_rows": 4035.0,
"estimated_total_cost": 409.75
}
],
"condition": "(city.Population between 127800 and 137500)",
"operation": "Filter: (city.Population between 127800 and 137500)",
"access_type": "filter",
"estimated_rows": 448.28851260244846,
"estimated_total_cost": 409.75
}
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Efficient MySQL Indexing and what's new in MySQL Explain

  • 1. Efficient MySQL Indexing & What's New in MySQL Explain Presented by Jebashalomie Immanuel Mydbops Mydbops MyWebinar - 32 May 11th, 2024
  • 2. Consulting Services Consulting Services Managed Services ● Database Management and consultancy provider ● Founded in 2016 ● Assisted 800+ happy customers ● AWS partners ● PCI & ISO certified About Us
  • 3. Agenda ❏ Index Overview ❏ Types of Indexes ❏ Increasing Indexing Efficiency ❏ Example ❏ Before Optimization ❏ Optimization ❏ After Optimization ❏ New Features ❏ Capturing EXPLAIN FORMAT=JSON Output ❏ explain_json_format_version
  • 5. Index Overview ❏ Enhances data retrieval speed, uses extra space. ❏ Created on table columns, choosing the right index is vital. ❏ Needs regular updates to stay efficient. ❏ Index types: Includes primary, unique, composite, and full-text.
  • 9. Increasing Index Efficiency ❏ Analysing the queries ❏ Avoid over indexing ❏ Analyze the cardinality ❏ Pick the correct columns ❏ Pick the suitable index ❏ Regular maintenance
  • 11. Example Datatype: column1 - text Query: SELECT * FROM test_function WHERE column1 LIKE 'flexibility'; Total rows: 96
  • 13. Before Optimization mysql> explain SELECT * FROM test_function WHERE column1 LIKE 'flexibility'G *************************** 1. row *************************** id: 1 select_type: SIMPLE table: test_function partitions: NULL type: ALL possible_keys: NULL key: NULL key_len: NULL ref: NULL rows: 96 filtered: 11.11 Extra: Using where
  • 14. Optimization Index creation: mysql> Alter table test_function add fulltext index idx_column1(column1); Query OK, 0 rows affected, 1 warning (0.20 sec) mysql> explain SELECT * FROM test_function WHERE column1 LIKE 'flexibility'; +----+-------------+---------------+------------+------+---------------+------+---------+------+- -----+----------+-------------+ | id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra | +----+-------------+---------------+------------+------+---------------+------+---------+------+- -----+----------+-------------+ | 1 | SIMPLE | test_function | NULL | ALL | idx_column1 | NULL | NULL | NULL | 96 | 11.11 | Using where | +----+-------------+---------------+------------+------+---------------+------+---------+------+- -----+----------+-------------+
  • 16. After Optimization mysql> EXPLAIN SELECT * FROM test_function WHERE MATCH(column1) AGAINST ('flexibility')G *************************** 1. row *************************** id: 1 select_type: SIMPLE table: test_function partitions: NULL type: fulltext possible_keys: idx_column1 key: idx_column1 key_len: 0 ref: const rows: 1 filtered: 100.00 Extra: Using where; Ft_hints: sorted 1 row in set, 1 warning (0.00 sec) mysql> EXPLAIN SELECT * FROM test_function WHERE MATCH(column1) AGAINST ('flexibility')G *************************** 1. row *************************** id: 1 select_type: SIMPLE table: test_function partitions: NULL type: fulltext possible_keys: idx_column1 key: idx_column1 key_len: 0 ref: const rows: 1 filtered: 100.00 Extra: Using where; Ft_hints: sorted 1 row in set, 1 warning (0.00 sec)
  • 17. New Features ❏ Capturing EXPLAIN FORMAT=JSON output (MySQL 8.1.0) ❏ explain_json_format_version (MySQL 8.3.0)
  • 18. Capturing EXPLAIN FORMAT=JSON Output Query: mysql> EXPLAIN FORMAT=JSON INTO @myvar SELECT * FROM city WHERE District='Texas'; Query OK, 0 rows affected (0.00 sec) mysql> EXPLAIN FORMAT=JSON INTO @myvar SELECT * FROM city WHERE District='Texas'; Query OK, 0 rows affected (0.00 sec)
  • 19. mysql> select @myvarG *************************** 1. row *************************** @myvar: { "query_block": { "select_id": 1, "cost_info": { "query_cost": "428.50" }, "table": { "table_name": "city", "access_type": "ALL", "rows_examined_per_scan": 4035, "rows_produced_per_join": 403, "filtered": "10.00", "cost_info": { "read_cost": "388.15", "eval_cost": "40.35", "prefix_cost": "428.50", "data_read_per_join": "97K" }, "used_columns": [ "ID", "Name", "CountryCode", "District", "Population" ], "attached_condition": "(`world`.`city`.`District` = 'Texas')"}} 1 row in set (0.00 sec)
  • 20. explain_json_format_version variable ● Two versions available for EXPLAIN FORMAT=JSON. ● Version 2 reveals optimizer access paths. ● Ensures compatibility with upcoming MySQL Optimizer. ● Supports the JSON output format for EXPLAIN statements.
  • 21. Version 1 Validation of the variable: mysql> select @@explain_json_format_version; +-------------------------------+ | @@explain_json_format_version | +-------------------------------+ | 1 | +-------------------------------+ mysql> select @@explain_json_format_version; +-------------------------------+ | @@explain_json_format_version | +-------------------------------+ | 1 | +-------------------------------+
  • 22. mysql> Explain format = JSON select ID, Name, CountryCode, District, Population from city where Population between 127800 and 137500G *************************** 1. row *************************** EXPLAIN: { "query_block": { "select_id": 1, "cost_info": { "query_cost": "409.75" }, "table": { "table_name": "city", "access_type": "ALL", "rows_examined_per_scan": 4035, "rows_produced_per_join": 448, "filtered": "11.11", "cost_info": { "read_cost": "364.92", "eval_cost": "44.83", "prefix_cost": "409.75", "data_read_per_join": "108K" }, "used_columns": [ "ID", "Name","CountryCode", "District", "Population" ], "attached_condition": "(`world`.`city`.`Population` between 127800 and 137500)”} } }
  • 23. Version 2 Setting the variable: mysql> SET @@explain_json_format_version = 2; Query OK, 0 rows affected (0.00 sec)
  • 24. mysql> Explain format = JSON select ID, Name, CountryCode, District, Population from city where Population between 127800 and 137500G *************************** 1. row *************************** EXPLAIN: { "query": "/* select#1 */ select `world`.`city`.`ID` AS `ID`,`world`.`city`.`Name` AS `Name`,`world`.`city`.`CountryCode` AS `CountryCode`,`world`.`city`.`District` AS `District`,`world`.`city`.`Population` AS `Population` from `world`.`city` where (`world`.`city`.`Population` between 127800 and 137500)", "inputs": [ { "operation": "Table scan on city", "table_name": "city", "access_type": "table", "schema_name": "world", "used_columns": [ "ID", "Name", "CountryCode", "District", "Population" ], "estimated_rows": 4035.0, "estimated_total_cost": 409.75 } ], "condition": "(city.Population between 127800 and 137500)", "operation": "Filter: (city.Population between 127800 and 137500)", "access_type": "filter", "estimated_rows": 448.28851260244846, "estimated_total_cost": 409.75 }
  • 25. Demo