MariaDB workshopAlex Chistyakov, Git in Sky

Outline- Tables and DDL

- Queries and DML

- Indexes and compound indexes

- Transactions and how they work, isolation levels

- Authorization and authentication, client protocol

Outline- Basics of performance monitoring

- Notion of replication, types of replication

- Traditional replication in details

- Galera cluster and how it works

- MMM, PRM and query proxying

What’s in a box?- Ubuntu 16.04.2

- Python 2.7.12

- MariaDB 10.0.29

- Sakila DB, Employees DB

- Percona Toolkit 2.2.16

- Anemometer

How to use Vagrant- Create an empty folder

- Download https://goo.gl/ap6r6E there (rename it to

‘Vagrantfile’)

- Run ‘vagrant up’ in that folder

- Wait until a VM starts

- Run ‘vagrant ssh’ to get in

- My .mysql_history: https://goo.gl/AyrTW7

- Tables and DDL

- Queries and DML

- Indexes and compound indexes

- Transactions and how they work, isolation levels

- Authorization and authentication, client protocol

What is a table?- A collection of related data

What is a table?- A collection of related data

- Consists of columns and rows

What is a table?

The DDL- Manipulates the database structure (also called schema)

DDL statements- CREATE

- ALTER

- DROP

- TRUNCATE

- RENAME

How to create a table?CREATE TABLE language (

language_id TINYINT UNSIGNED NOT NULL AUTO_INCREMENT,

name CHAR(20) NOT NULL,

last_update TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,

PRIMARY KEY (language_id)

)ENGINE=InnoDB DEFAULT CHARSET=utf8;

Primary keys- Identify a record uniquely

- So, adding two equal keys is not possible

- Can be natural like “passport number”

- Or surrogate

- Surrogate keys are auto-generated on the DB side

Natural PKs can be compositeCREATE TABLE film_actor (

actor_id SMALLINT UNSIGNED NOT NULL,

film_id SMALLINT UNSIGNED NOT NULL,

last_update TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,

PRIMARY KEY (actor_id,film_id),

KEY idx_fk_film_id (`film_id`),

CONSTRAINT fk_film_actor_actor FOREIGN KEY (actor_id) REFERENCES actor (actor_id),

CONSTRAINT fk_film_actor_film FOREIGN KEY (film_id) REFERENCES film (film_id)

)ENGINE=InnoDB DEFAULT CHARSET=utf8;

Autoincrement primary keys- Are surrogate

- Are 1,2,3,4 or 8 bytes long

- BTW, INT(10) is 4 bytes long

- Are incremented on every INSERT

- Should be always used

- BTW, InnoDB table is a clustered index* around its PK

- If no explicit PK exists 6-byte row ID will be used

Exercise #1- Create a table

- Tables and DDL

- Queries and DML

- Indexes and compound indexes

- Transactions and how they work, isolation levels

- Authorization and authentication, client protocol

A trivial SELECT query- SELECT * FROM employees WHERE hire_date='1986-06-26'

- Please, never use “SELECT *”, always select certain

columns!

- A slightly better version:

- SELECT emp_no, first_name, last_name FROM employees

WHERE hire_date='1986-06-26';

Using a single table is impractical*- Four types of JOINs:

- INNER JOIN

- LEFT OUTER JOIN

- RIGHT OUTER JOIN

- CROSS JOIN

- Left and right outer joins are equivalent

Left outer join example- SELECT e.emp_no, first_name, last_name, salary FROM

employees e LEFT OUTER JOIN salaries s on e.emp_no =

s.emp_no WHERE hire_date='1986-06-26';

- This query selects an employee even if no payment

records exist in the salaries table

Aggregate queries and GROUP BY- SELECT e.emp_no, first_name, last_name, SUM(salary)

FROM employees e LEFT OUTER JOIN salaries s on

e.emp_no = s.emp_no WHERE hire_date='1986-06-26'

GROUP BY e.emp_no;

How to get people w/no salary recs- INSERT INTO employees(emp_no, first_name, last_name)

VALUES(600000, 'Alex', 'Chistyakov');

- Let’s count number of salary records using COUNT()

aggregate function

HAVING is like WHERE- SELECT e.emp_no, first_name, last_name,

COUNT(salary) FROM employees e LEFT OUTER JOIN

salaries s on e.emp_no = s.emp_no GROUP BY e.emp_no

HAVING COUNT(salary) = 0;

Another way to do the same - SELECT e.emp_no, first_name, last_name,

COUNT(salary) FROM employees e LEFT OUTER JOIN

salaries s on e.emp_no = s.emp_no WHERE s.emp_no IS

NULL;

- This query is more optimal*

Exercise #2- Write a SELECT query which get all employees with total

sum of all salary records greater than 40000

- Tables and DDL

- Queries and DML

- Indexes and compound indexes

- Transactions and how they work, isolation levels

- Authorization and authentication, client protocol

Why indexes?- Latency Numbers Every Programmer Should Know:

https://goo.gl/v4CEWU

- Indexes helps to avoid unnecessary disk operations

How indexes work?- Index is a data structure optimized for search

- There are several types of indexes: hash indexes, B-tree

indexes

- Hash indexes allow to find exact rows

- B-tree indexes allow to find ranges

- InnoDB and Aria support B-tree indexes only

B-tree index- “B” stands for “balanced”, not for “binary”

“SQL Tuning” by Dan Tow- https://goo.gl/jRbD5H

- A must read for every DBA!

- Discusses how to build effective

indexes in great details

- Unfortunately does not cover

aggregate functions and sorting

Column cardinality- Cardinality is a measure of data uniqueness

- Columns with more unique values have higher cardinality

- Columns with few unique values have lower cardinality

A composite index- Covers two or more columns

- Allows to find rows by subsequently applying a filter

column-by-column

- Order of columns in a composite index matters!

Index selectivity- An ability of a certain condition to filter

- Is expressed as a number of columns after filtering

divided by a total number of columns

- Lower values mean greater selectivity

- Some authors define selectivity as a total number of

columns divided by a resulting number of columns

Building a good composite index- Columns with higher individual selectivity should go first

in a composite index

- Non-selective columns should be the latest

Functional indexes- Original MySQL does not have functional indexes

- MariaDB adds support for virtual columns

- Functional indexes can be created over virtual columns

Virtual column example- ALTER TABLE employees ADD lower_last_name

varchar(16) GENERATED ALWAYS AS (lower(last_name))

PERSISTENT;

- CREATE INDEX lower_last_name ON

employees(lower_last_name);

- SELECT e.emp_no, first_name, last_name FROM

employees e WHERE lower_last_name LIKE 'chistya%';

Let’s add %- SELECT e.emp_no, first_name, last_name FROM

employees e WHERE lower_last_name LIKE '%chistya%';

- This will always lead to a full scan in current MariaDB

and MySQL implementations

- Full Text Search engine should be used instead

- I recommend Sphinx or Solr

Using ORDER BY- In most real life cases can’t be covered by an index

- Dan Tow doesn’t consider these cases at all

- No good solution exists

Exercise #3- Write a select which gets all salary records for the

employee w/emp_no = 10001 ordered by amount of the

salary record

- Create a covering index for this query

Things not to do in your life- Please never ever do ORDER BY RAND()!

- How to do it properly: get a good random number on the

client side

- LIMIT 50 OFFSET 5000000 is the next thing not to do

- How to do it properly: “emp_no > $last_emp_no LIMIT

50”

- Tables and DDL

- Queries and DML

- Indexes and compound indexes

- Transactions and how they work, isolation levels

- Authorization and authentication, client protocol

A bit of history- MySQL supported pluggable storage engines for years

- Two most notable were MyISAM and InnoDB

- MyISAM did not support transactions in any way

- InnoDB was transactional

MariaDB engines- Many mysql.* tables are still in MyISAM format

- Aria storage engine emerged and is optionally

transactional in a crash-proof sense (does not support

explicit transactions though)

- InnoDB fully supports transactions

- I recommend to use InnoDB

A bit of InnoDB internals- /var/lib/mysql/ib_logfile[01] are InnoDB redo logs

- The redo log works as a circular buffer

- It’s not practical to set the InnoDB log size

(innodb_log_file_size) to more than 128M

- This change requires restart

Generic recovery process- Works the same way for any engine with WAL/redo

log/intent log/whatever

- The service starts after crash

- Log records are examined

- Finished transactions are applied to their final

destinations, unfinished ones are thrown out

- Aria performs these steps when in transaction mode too

COMMIT and auto-commit- Every query starts and commits an implicit transaction

by default

- SET autocommit = 0; disables this

- START TRANSACTION or BEGIN should be used then to

start a transaction

- And COMMIT to finish it

- DDL statements perform COMMIT implicitly

ROLLBACK and savepoints- ROLLBACK is used to abort a transaction

- Transactions can’t be nested but this behavior can be

emulated using savepoints

- SAVEPOINT label

- ROLLBACK TO label

- RELEASE SAVEPOINT label

A bit of InnoDB internals - MVCC- MVCC stands for “Multiversion concurrency control”

- Records are declared dead but still occupy disk space

- InnoDB storage file never shrinks

- InnoDB uses a single file for everything by default and

this file can’t be compacted

It’s possible to overcome this- innodb_file_per_table=1

- Every table will occupy a separate file (two separate

files in fact)

- Beware of Unix file descriptors limits!

- ulimit -n 65535 somewhere before starting mysqld_safe

Long transactions can be evil- DDL statements require an exclusive lock on table

metadata

- An explicit transaction holds a read lock on every table it

uses

- If number of transactions per second is high enough the

DDL statement will wait forever

Transactions: logical perspective- The SQL standard defines 4 transaction isolation levels

- READ UNCOMMITTED

- READ COMMITTED

- REPEATABLE READ

- SERIALIZABLE

READ UNCOMMITTED- The weakest level

- Allows dirty reads

- A transaction can get non-committed data of other

transaction

READ COMMITTED- Non-repeatable reads are possible

- Phantom reads are possible

REPEATABLE READ- The default isolation level

- Non-repeatable reads are not possible

- Phantom reads are possible

SERIALIZABLE- The strongest level

- Non-repeatable reads and phantom reads are impossible

Exercise #4- Open two different connections to the employees DB, set

autocommit to 0;

- Set isolation level to READ COMMITED in both windows,

select total number of employees whose names started

with Alex in the 1st session, delete the employee with ID

499559 in the 2nd session (don’t forget to COMMIT),

repeat the query in the 1st session

Exercise #4- Set isolation level to REPEATABLE READ in both windows,

select total number of employees whose names started

with Alex in the 1st session, delete the employee with ID

499517 in the 2nd session (don’t forget to COMMIT),

repeat the query in the 1st session

Exercise #4- Set isolation level to REPEATABLE READ in both windows,

select total number of employees whose names started

with Alex in the 1st session, insert an employee called

Alexis Doe in the 2nd session (don’t forget to COMMIT),

repeat the query in the 1st session

Exercise #4- Set isolation level to SERIALIZABLE in both windows,

select total number of employees whose names started

with Alex in the 1st session, insert an employee called

Alex Didnotfail in the 2nd session (don’t forget to

COMMIT), repeat the query in the 1st session

- Tables and DDL

- Queries and DML

- Indexes and compound indexes

- Transactions and how they work, isolation levels

- Authorization and authentication, client protocol

mysql.user table- Stores user privileges

- Can (but should not) be manipulated directly

- FLUSH PRIVILEGES rereads effective rights from it

- Uses MyISAM storage

GRANT statement- Creates user accounts

- Grants privileges to them

- Is documented at https://goo.gl/zBHTd4

A superuser- Has ALL PRIVILEGES ON *.*

- Has a number of SUPER privileges

A list of privileges- Privileges can be global, database level, table level,

column level, function level and procedure level

- A list is available in GRANT command documentation

Default client credentials- Can be set in ~/.my.cnf file like this:

[client]

user = root

password = Pheexaigee8a

Using views to limit rights- Create a view using a privileged table columns

- Grant privileges to that view

Using stored procedures- Create a stored procedure to perform AAA tasks

- Grant privileges to that stored procedure

MySQL wire protocol- Is encrypted using a session key

- Can’t be easily proxied on L3 because of that

Exercise #5- Grant all privileges on the employees.salaries table to a

user called “manager” with password da5ca9aeNgee%, a

user can connect from any host

- Create a view on a table employees consisting of emp_no

and the first and last names and grant a read privilege on

it to a user called “reader” with password eLegah0aez8a

- Basics of performance monitoring

- Notion of replication, types of replication

- Traditional replication in details

- Galera cluster and how it works

- MMM, PRM and query proxying

MySQL slow queries log- The simplest way to do performance tuning

- Should be enabled in the MariaDB config file

- Slow queries will be written to a file for subsequent

analysis

Slow queries log config vars- slow_query_log = on

- slow_query_log_file = /var/log/mysql/mariadb-slow.log

- long_query_time = 0.1

- log-queries-not-using-indexes

Analyzing the log w/Percona Tools- pt-query-digest

- Documented at https://goo.gl/YCv1ya

- In the simplest case produces a textual report on most

time-consuming queries

Analyzing the log w/Anemometer- Anemometer is a web-based slow query monitor created

at Box (https://github.com/box/Anemometer)

- Anemometer uses pt-query-digest to process the slow

query log internally

- Anemometer requires PHP, a webserver and a number of

other tools

- So, we use an Ansible role to simplify its deployment

Ansible role for Anemometer- Ansible is a popular Configuration Management tool

- Ansible is written in Python and uses YAML as a

configuration description language

- A role for Anemometer is at https://goo.gl/us6V82

- This role works for Ubuntu 14.04 hosts and does not work

for 16.04 yet

- This is trivial to correct, expect a fix in a week

Demo time!- Let’s analyze live queries in our Vagrant box

Partitioning and sharding- Partitioning is a process of splitting a big table in smaller

subset on the same server

- Partitioning works well for time-series data

- Sharding is a process of splitting a big table in a number

of unrelated tables on different servers

- Sharding requires serious modifications of the app code

Partitioning in MariaDB- MariaDB inherits MySQL support for partitioning

- Partitioning is documented at https://goo.gl/1CwIKX

- Certain limitations apply:

- Queries are not parallelized

- Partitioned table can’t contain or be referenced by

foreign keys

Partitioning in the real life- Is tricky to set up properly

- Is often misused (I personally have never seen MySQL

partitioning set up properly)

- I strongly recommend not to use partitioning

Exercise #6- Get familiar with the Anemometer tool

- Read and explain a query plan

- Basics of performance monitoring

- Notion of replication, types of replication

- Traditional replication in details

- Galera cluster and how it works

- MMM, PRM and query proxying

What is replication?- Storing the same data on multiple MariaDB servers

- Establishing a master/slave relationship between the

original and the copies

- Distributing data modifications from a master node to

slave nodes

Master and slave nodes- The master node gets data modification queries

(INSERTs, UPDATEs and DELETEs)

- The master node sends data changes to slaves

- Slave nodes are read-only and get updates from the

master

- Data modification on slave nodes is not prohibited in

MySQL/MariaDB world

Types of replication- Replication can be synchronous or asynchronous

- Replication can also be master-slave or master-master

- All 4 options are possible: “synchronous master-slave”,

“asynchronous master-slave”, “synchronous

master-master” and “asynchronous master-master”

- Asynchronous master-slave is the default MariaDB setting

Master-slave and master-master- There is only a single master in a MS replication topology

- There is more than one master in a MM setup

- A master should propagate data changes to all hosts in

the replication topology

- So, every master is also a slave in a MM setup

Sync or async- Async: a transaction on a master is finished as soon as

it’s written to a transaction log on a master

- Semisync: a transaction on a master is finished only

after it’s written to a transaction log on one of slaves

- Sync: a transaction on a master is finished when it’s

acknowledged and committed on all slaves

Replication lag- Replication lag is a delay between the same operations

on a master and on a slave

- Replication lag is meaningful for async replication only

- Replication lag should be minimized

Multi-master replication scalability- Multi-master replication does not scale on writes!

- It’s a popular belief that it does (because there is more

than one master)

- But every master should perform exactly the same set of

write operations!

Multi-master tips and tricks- Avoid writing to the same table on different masters!

- Split your schema to several non-related table sets

logically bound to different services if possible

- Work with these table sets on different masters

independently

- Basics of performance monitoring

- Notion of replication, types of replication

- Traditional replication in details

- Galera cluster and how it works

- MMM, PRM and query proxying

The binary log- The binary log stores data modification events (both DDL

and DML changes)

- The binary log is storage neutral (works for Aria, InnoDB,

etc.)

- The binary log is not a transaction log

- The binary log can store events in 3 different formats

Binary log formats- SBR (statement-based replication)

- RBR (row-based replication)

- Mixed (stores statements or rows when appropriate)

- Mixed seems to be the best of both worlds

- But it is not, in fact (avoid using it)

Statement-based replication- Stores INSERT/UPDATE/DELETE and

CREATE/DROP/TRUNCATE statements as is

- Requires less space in the log

- Is not 100% accurate for all statements

SBR non-determinism- INSERT INTO t1(c1, mtime) VALUES(1, NOW())

- NOW() can be different on master and slave

- INSERT INTO t2(c1, c2) VALUES(1, RAND())

- RAND() is definitely different on master and slave

- Fixes are trivial - master should send exact values

- DELETE FROM t1 LIMIT 10; - fix is not trivial

SBR is broken (mixed is broken too)- Error 1062 (Duplicate entry NNN for key X)

- But why?..I just inserted a bunch of rows!

- This is a bug somehow related to range locking on a

primary key on slave side

- There is a lot of instructions on the Internet, something

like “set slave-skip-errors to 1062”

Never trust random Internet guys- Don’t do “slave-skip-errors”

- To fix this bug properly…

- NEVER USE SBR OR MIXED LOG FORMATS, USE RBR!

- The only problem is that RBR is broken too

The binary log concept is broken- Correctly implemented binary log stores physical changes

to the storage layer (WAL records)

- MySQL historically used pluggable storage layers, some of

them were non-transactional

- The binary log is on the wrong abstraction layer

- This can’t be easily fixed

RBR is broken (much less than SBR)- DELETE FROM t1; generates a lot of rows to be written to

the binary log

- The slave can begin lagging

- A slave SQL thread uses indexes to apply row deltas

- Having a primary key is inevitable!

- It’s better to use surrogate keys

libslave- A library to mimic a MySQL slave

- https://github.com/tarantool/libslave

- Can be embedded to an app, allows an app to connect to

the MySQL master and read the binlog

Cascading replication topologies- Replication can (and should be)

cascaded (5 slaves on a single master

is a bad idea)

- A slave can be a master for a slave

- Config should be tweaked:

log-slave-updates=1

Replication rings- If you absolutely need

master-master, you can have one

- Every master should have its own

key space

- auto_increment_offset=1

auto_increment_increment=10

Semisync replication- Added since MariaDB 5.5, declared stable since 10.1.3

- Documented at https://goo.gl/wuiKfJ

- If a slave fails to acknowledge before a certain timeout,

a master switches to async automatically and switches

back when a slave catches up

Parallel replication- Traditional MariaDB replication uses a single SQL thread

on the slave side

- Starting with 10.0.5 it’s possible to use several threads

- Documented at https://goo.gl/0p4SH9

Delayed replication- Replication is not a backup!

- Delayed replication is (well, can be)

- Introduced in MariaDB 10.2.3

- Documented at https://goo.gl/BZguD9

- Replication delay can be achieved using pt-slave-delay

tool from Percona Toolkit

GTID- Globally unique binlog events identification

- Introduced in 10.0.2

- Documented at https://goo.gl/xgJ27M

- Has a number of significant benefits: slave server can be

easily reconnected to another master, slave log position

is saved in a transactional way

- Basics of performance monitoring

- Notion of replication, types of replication

- Traditional replication in details

- Galera cluster and how it works

- MMM, PRM and query proxying

WSREP- WSREP is a library for distributing working sets

- The Galera cluster is built around that library

The Galera cluster- Is InnoDB-only

- Is semisync

- Does not use traditional replication at all

A common Galera cluster setup- Two master nodes and one arbiter node

- The arbiter node does not store anything

- Basics of performance monitoring

- Notion of replication, types of replication

- Traditional replication in details

- Galera cluster and how it works

- MMM, PRM and query proxying

Questions?- Please feel free to email me at alex@gitinsky.com

- My Skype ID is demeliorator

Thank you!- Good luck in the wonderful world of MariaDB!