southeast linuxfest -- mysql queries-- - damned lies and best guesses
DESCRIPTION
This session covers how to understand what MySQL is trying to tell you about queries.TRANSCRIPT
MySQL Queries -- DamnedLies and Best GuessesVery few programmers really understand SQL or how to speed queries to their databases. This session covers that basics of relational calculus (no actual math/calculus will be demanded of attendees), how a RDMS like MySQL tries to optimize the query, and introduces query tuning.
Dave [email protected]@stokerslideshare.net/davestokes
SQL Structured Query Language
Structured Query Language (/ˈɛs kjuː ˈɛl/,[4] or /ˈsiːkwəl/; (SQL)[5][6][7][8]) is a
special-purpose programming language designed for managing data held in a
relational database management system (RDBMS).
Originally based upon relational algebra and tuple relational calculus, SQL consists of a data definition language
and a data manipulation language. The scope of SQL includes data insert, query, update and delete, schema
creation and modification, and data access control. Although SQL is often described as, and to a great extent is, a
declarative language (4GL), it also includesprocedural elements.
relational algebra is an offshoot of first-order logic and of algebra of sets concerned with operations over
finitary relations, usually made more convenient to work with by identifying the components of a tuple by a name
(called attribute) rather than by a numeric column index, which is called a relation in database terminology.
--Wikipedia
You send SQL to the server …
The mysqld process will take your input and parse it for VALID syntax.
Then it will build a query plan on how best to retrieve the data.
Finally it goes to fetch the data.MySQL’s NoSQL queries that skip these steps are MUCH faster
GOALs
1. Get the data that you need and only what you need as fast as possible. No ‘SELECT * FROM’
2. Avoid unnecessary disk/memory reads and disk writes.
3. Make data as compact as is usefull, no BIGINTs for zipcodes.
Cost Based Optimizer
C.5.6. Optimizer-Related Issues
MySQL uses a cost-based optimizer to determine the best way to resolve a query. In many cases, MySQL can calculate the
best possible query plan, but sometimes MySQL does not have enough information about the data at hand and has to make
“educated” guesses about the data.
So MySQL wants to get your data as cheaply as possible and plans accordingly.
Query Plan not lockable with MySQL
Each time MySQL gets a query it will optimise it!
It builds a list of statistics over time to help keep track of data & speed retrieval of the data (5.6 lets you save/restore this information)
Clue: You want FAST!
EXPLAIN
EXPLAIN is a tool to ask the server how it wants to optimize the query.
Prepend to a QUERY
Example Table
Example Query
Example EXPLAIN
Example EXPLAIN with \G
Query#
A Quick Word on Indexes
Indexes allow you to go directly to the record(s) you want (think SSN) instead of reading all records to find the one(s) wanted.
But they require maintenance and overhead.
Not a panacea!
What the heck is a B-Tree?!??!?!
select_type
Using WHERE
274 Records Read!
Previous query w/o INDEX
No index used and all records in table readto find 274 re
How to find index(es) already in use
OR ...
A more common example
Optimizer estimates 8 reads to get desired info
Could use the PRIMARY key but does not!!
Has to read all records
239 x 8 = 1,912 records to read
Slightly more complex query
SELECT a.Name as 'City',
b.Name as 'Country',
a.population
FROM City a
JOIN Country b
ON (a.CountryCode = b.Code)
WHERE a.population > 3000000
AND b.LifeExpectancy > 66
ORDER BY b.name, a.Population
LIMIT 20;
Gee, we add all those qualifiers and it still has to readAll those records AND we get a temp table plus a file sort!
And we ONLY wanted 20 records!!!
Visual Explain
MySQL 5.6 and
Workbench 6.1 use
JSON format output
to generate diagram.
Costs published with
5.7 and 6.1!
Yet a little deeper into complexitySELECT 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 5;
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A little easier to understand
Compound Indexes
We can use this index searching on
1. City, State, and Zip
2. City, State
3. City
Covering Indexes
ALTER TABLE city ADD INDEX country_idx (CountryCode, Population);
The INDEX contains all the data we are searching for which means less data to look-up
Musts for better queries
1. Read chapter 8 of the MySQL Manual
2. Join on like data types, INTs with INTS
3. Keep columns as small as practical (PROCEDURE ANALYSE)
4. Maintain B-tree index with ANALYSE TABLE when things are quiet
5. Keep looking for improvments
Hard to teach all in a few minutes
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