Alkin Tezuysal "MySQL Query Optimization Best Practices and Indexing"
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The document provides best practices for MySQL query optimization and indexing, emphasizing the importance of proper indexing to enhance query performance. It discusses techniques for identifying slow queries, using tools like explain plans and slow query logs, and offers indexing best practices for effective data retrieval. The presentation also covers advanced topics such as optimizer hints, query rewriting, and the types of MySQL indexes available.
![© 2017 Percona21
Explain Plan (JSON)
> EXPLAIN format=JSON SELECT CONCAT(customer.last_name, ', ', customer.first_name) AS customer, address.phone, film.title FROM rental INNER JOIN customer ON rental.customer_id =
customer.customer_id INNER JOIN address ON customer.address_id = address.address_id INNER JOIN inventory ON rental.inventory_id = inventory.inventory_id INNER JOIN film ON inventory.film_id =
film.film_id WHERE rental.return_date IS NULL AND rental_date + INTERVAL film.rental_duration DAY < CURRENT_DATE() LIMIT 5G
*************************** 1. row ***************************
EXPLAIN: {
"query_block": {
"select_id": 1,
"nested_loop": [
{
"table": {
"table_name": "film",
"access_type": "ALL",
"possible_keys": [
"PRIMARY"
],
"rows": 1000,
"filtered": 100
}
},
…
…](https://image.slidesharecdn.com/b12-40tezuysal-180918111315/85/Alkin-Tezuysal-MySQL-Query-Optimization-Best-Practices-and-Indexing-21-320.jpg)
Alkin Tezuysal "MySQL Query Optimization Best Practices and Indexing"
- 1. © 2017 Percona1 MySQL Query Optimization Best Practices and Indexing Alkin Tezuysal – Sr. Technical Manager Percona
- 2. © 2017 Percona2 Who am I? @ask_dba
- 3. © 2017 Percona3 About Percona Solutions for your success with MySQL , MongoDB and PostgreSQL Support, Managed Services, Software Our Software is 100% Open Source Support Broad Ecosystem – MySQL, MariaDB, Amazon RDS In Business for 12 years More than 3000 customers, including top Internet companies and enterprises
- 4. © 2017 Percona4 About This Presentation Indexing Basics Finding and Identifying Slow Queries Utilizing Explain Plan Advanced Indexing Tooling and more
- 5. © 2017 Percona5 Indexing Basics • What it does? • Increase speed of given lookup (SQL) • Access and maintain changes • Helps Optimizer to reach its goal
- 6. © 2017 Percona6 Why do we need indexes? • Data persists on disks • Disks cheap but slow • Data can be in memory • Memory fast but expensive Index is the answer to access data fast. CREATE INDEX part_of_name ON customer (name(10));
- 7. © 2017 Percona7 Traversal 1. Tree Traversal 2. Follow leaf node chain 3. Fetch the table data
- 8. © 2017 Percona8 Leaf Nodes 1. Establish doubly linked list 2. Connect index leaf nodes 3. Indexed columns
- 9. © 2017 Percona9 B-tree Structure
- 10. © 2017 Percona10 Slow Index Lookups • Low cardinality • Large data sets • Multiple index traversal • Index column used as argument • Looking for suffix • Non-leading column lookup • Data type mismatch • Character Set / Collation mismatch • MySQL Bug
- 11. © 2017 Percona11 The Optimizer
- 12. © 2017 Percona12 MySQL Optimizer • Cost based • Assign costs to select operations • Assign costs to partial or alternate plans • Seek for lowest cost Access Method Join Order Subquery Strategy
- 13. © 2017 Percona13 Cost Model
- 14. © 2017 Percona14 Finding and Identifying Slow Queries • Slow Query Log • PMM/QAN • Network sniff • Others (Licensed) • MySQL EM • Vividcortex • Solarwinds • Monyog
- 15. © 2017 Percona15 Slow Query Tools • Explain Plan • Tabular • JSON (5.7) • Visual (Workbench) • Running Query (5.7) • pt-query-digest • pt-visual-explain • Performance Schema • MySQL Sys Schema • Optimizer Trace • MySQL Workbench • Status Variables • show status like ‘Sort%’ • show status like ‘Handler%’
- 19. © 2017 Percona19 PMM Demo - https://pmmdemo.percona.com/
- 20. © 2017 Percona20 Explain Plan
- 21. © 2017 Percona21 Explain Plan (JSON) > EXPLAIN format=JSON SELECT CONCAT(customer.last_name, ', ', customer.first_name) AS customer, address.phone, film.title FROM rental INNER JOIN customer ON rental.customer_id = customer.customer_id INNER JOIN address ON customer.address_id = address.address_id INNER JOIN inventory ON rental.inventory_id = inventory.inventory_id INNER JOIN film ON inventory.film_id = film.film_id WHERE rental.return_date IS NULL AND rental_date + INTERVAL film.rental_duration DAY < CURRENT_DATE() LIMIT 5G *************************** 1. row *************************** EXPLAIN: { "query_block": { "select_id": 1, "nested_loop": [ { "table": { "table_name": "film", "access_type": "ALL", "possible_keys": [ "PRIMARY" ], "rows": 1000, "filtered": 100 } }, … …
- 22. © 2017 Percona22 Explain Plan (pt-visual-explain) JOIN +- Bookmark lookup | +- Table | | table address | | possible_keys PRIMARY | +- Unique index lookup | key address->PRIMARY | possible_keys PRIMARY | key_len 2 | ref sakila.customer.address_id | rows 1 +- JOIN +- Bookmark lookup | +- Table | | table customer | | possible_keys PRIMARY,idx_fk_address_id | +- Unique index lookup | key customer->PRIMARY | possible_keys PRIMARY,idx_fk_address_id | key_len 2 | ref sakila.rental.customer_id | rows 1 ...
- 23. © 2017 Percona23 Cost Based Access Method 1. Find the optimal method 2. Check if access method useful 3. Estimate the cost of using access method 4. Select low cost access method
- 24. © 2017 Percona24 Query Execution Table Scan Index Scan Index Lookup Range Scan Index Merge Loose Index Scan
- 25. © 2017 Percona25 Indexing Best Practices • Always have Primary Key • Physical order of table, if not created explicitly, MySQL will create hidden one (Global Mutex) • Fastest lookup is PK
- 26. © 2017 Percona26 Indexing Best Practices • Single index with multiple columns • Left most first and each additional field in a composite key • Composite indexes better a.k.a Covering indexes • PK is already part of composite indexes
- 27. © 2017 Percona27 Indexing Best Practices • Equality first, range next • Ex: select first_name, last_name, birth_date from employees where date_of_birth => to_date (?, `YYYY-MM-DD`) and date_of_birth <= to_date (?, `YYYY-MM-DD`) and branch_id = ?
- 28. © 2017 Percona28 Indexing Best Practices • One index scan is faster than two • Avoid duplicate indexes pt-duplicate-key-checker
- 29. © 2017 Percona29 Indexing Best Practices • Data types matter. Numeric for numbers. • Ex: select … from … where numeric_value = `48`
- 30. © 2017 Percona30 Query Optimization Best Practices • Negative clauses and subqueries aren’t as good as positive clauses • Ex: • IS NOT • IS NOT NULL • NOT IN • NOT LIKE
- 31. © 2017 Percona31 Query Optimization Best Practices • User INNER instead of LEFT where you can
- 32. © 2017 Percona32 Query Optimization Best Practices • UNION ALL is better than UNION UNION UNION ALL
- 33. © 2017 Percona33 Query Optimization Best Practices • ORDER BY can be expensive SELECT * FROM t1 ORDER BY idx_c1, idx_c2; • Avoid while sorting small set of data (Use code) cust _id first_na me last_ name email 1 Billy Joel bb7@bluen ot.com 2 Jane Fond a jf1950@yah oo.com 3 Mark Welt on markW1912 @gmail.co m 4 Linda Joey linda.joey@ yandex.com 5 Sidney Travo r sidney.travo [email protected] m 6 Jordan Velez jordanv@a mazon.com
- 34. © 2017 Percona34 Query Optimization Best Practices • Watch out those ORDER BY + LIMIT operations • These usually return small set of data with big cost (filesort) SELECT col1, ... FROM t1 ... ORDER BY name LIMIT 10; SELECT col1, ... FROM t1 ... ORDER BY RAND() LIMIT 15;
- 35. © 2017 Percona35 Query Optimization Best Practices • Watch out those ORDER BY + LIMIT operations • These usually return small set of data with big cost (filesort) SELECT col1, ... FROM t1 ... ORDER BY name LIMIT 10; SELECT col1, ... FROM t1 ... ORDER BY RAND() LIMIT 15;
- 36. © 2017 Percona36 MySQL Index Types • B-tree (Common) • Fractal Tree • LSM Tree • R-Tree (Spatial) • Hash (Memory) • Engine-dependent
- 37. © 2017 Percona37 Advanced Indexing • Optimizer hints • Global: The hint affects the entire statement • Query block: The hint affects a particular query block within a statement • Table-level: The hint affects a particular table within a query block • Index-level: The hint affects a particular index within a table • Index hints • SELECT * FROM t1 USE INDEX (i1) IGNORE INDEX FOR ORDER BY (i2) ORDER BY a;
- 38. © 2017 Percona38 If indexes not enough • Query Re-write • ProxySQL • https://www.percona.com/blog/2018/05/02/proxysql-query-rewrite- use-case/ • MySQL 5.7: Query Rewrite Plugin • Add hints • Modify join order
- 39. © 2017 Percona39 Advanced Queries with ProxySQL – Query rewrite engine • Most wanted feature by DBAs • Rewrite queries overloading the database on the fly. Application A ProxySQL • Simply buy time until application can be modified Application B MySQL Master MySQL Slave MySQL Slave MySQL Slave Query Rewriting MySQL Slave MySQL Slave
- 40. © 2017 Percona40 Final Thoughts Optimizer is not smart as DBAs • Help to choose best possible path • Improve throughput Add only indexes you need • Avoid duplicate indexing • Avoid overhead disk space, extra i/o ops Stay on current version of MySQL • Several bugs fixed • Optimizer and Engine improvements in place
- 41. © 2017 Percona41 References and Credits • Markus Winand (2018) - SQL Performance Explained (2018) • Otstein Grovlen (2017- How to Analyze and Tune MySQL Queries for Better Performance • Sveta Smirnova (2018) – Introduction into MySQL Query Tuning • Oracle Reference Manual • Jeremy Cole (2013) - How does InnoDB behave without a Primary Key? • Tata McDaniel (2018) - Visualize This! MySQL Tools That Explain Queries • Reviewers: Daniel G Burgos, Tate McDaniel, Janos Ruszo
- 42. DATABASE PERFORMANCE MATTERS Database Performance MattersDatabase Performance MattersDatabase Performance MattersDatabase Performance MattersDatabase Performance Matters