The document discusses various database topics like collecting email addresses, using functions in queries, collations, generating API keys, using primary keys, and partitioning tables. It provides code examples and explanations for selecting unique records based on email address with different casing, generating unique IDs, and configuring partitions in MySQL tables.

1. SELECT RAND() FROM
MYSQL_BITS
devops meetup - Toronto
1 of 35

2. Collecting email addresses
meOw@email.com
meow@email.com
MEOW@email.com
!

3. Let’s use a function !
mysql> explain SELECT id FROM users WHERE LOWER(email) =
'lucas@uken.com' G!
*************************** 1. row
***************************!
id: 1!
select_type: SIMPLE!
table: users!
type: index!
possible_keys: NULL!
key: uu!
key_len: 302!
ref: NULL!
rows: 4000!
Extra: Using where; Using index!
1 row in set (0.00 sec)

4. Collation Now you have N problems
!
Default: utf8_general_ci
!
select * from users where email='lucas@uken.com'
+----------------+
| LUCAS@uken.com |
| LuCaS@uken.com |
+----------------+

5. And it gets better..
mysql> select * from users where email='LUCAS@uken.com';!
+-----+-----------------+!
| id | email |!
+-----+-----------------+!
| 1 | LUCAS@uken.com |!
| 8 | LuCaS@uken.com |!
| 109 | lücas@uken.com |!
+-----+-----------------+

6. Just fix it
SELECT * FROM users WHERE BINARY email='LUCAS@uken.com';!
!
+----+----------------+!
| id | email |!
+----+----------------+!
| 1 | LUCAS@uken.com |!
+----+----------------+

7. Stop the world
Fix the app (settle on lowercase/uppercase), clean up all records
!
UPDATE users SET email = LOWER(email)!
!
Add unique index
!
CREATE UNIQUE INDEX unique_emails ON users(email)

8. Generating API Keys
Just make sure they are unique

9. I got this !
CREATE TABLE apikeys(apikey BINARY(36) NOT
NULL PRIMARY KEY);!
!
INSERT INTO apikeys(apikey)
VALUES(UUID());!
+--------------------------------------+!
| apikey |!
| 3d0e1678-ffce-11e2-ac86-18576e236284 |!
+--------------------------------------+
unique != unpredictable

10. Why...
RFC 4122 (128bit) timestamp, dce, md5, mac, random
!
SELECT UUID(),UUID(),UUID() G!
*************************** 1. row
************************!
UUID(): 3278447a-ffd0-11e2-ac86-18576e236284!
UUID(): 3278448e-ffd0-11e2-ac86-18576e236284!
UUID(): 3278448f-ffd0-11e2-ac86-18576e236284

11. Just fix it
>>> import uuid!
>>> uuid.uuid4()!
UUID('92d0b870-2336-497b-b310-
e48bdda5938c')!
>>> uuid.uuid4()!
UUID('e3116e9c-318c-4ec3-91c1-64fae7990007')!
!
!
#uuid1 = time based!
#uuid3 = md5 namespace!
#uuid4 = random!
#uuid5 = sha1 namespace

12. Make it meaningful
h =
hmac.new('supersecret',digestmod=hashlib.sha1)!
h.update('192.168.0.1') # ip for this api key!
print(h.hexdigest())!
!
7b8a2ac1bf1e6e1dfae65f957174d830ccb83c8c

13. Primary keys
I like uuids and I cannot lie...

14. It’s a thing !
CREATE TABLE apikeys(apikey BINARY(36) NOT
NULL PRIMARY KEY);!
!
● Storage size
● last_insert_id (it is based on auto increment fields)
● Breaks ORMs (ex: node-orm / ActiveRecord)
● 'PRIMARY KEY' implies 'UNIQUE' key.

15. http://kccoder.com/mysql/uuid-vs-int-insert-performance/

16. Partitions
but..but... shards are webscale!

17. *Most storage engines MyISAM, InnoDB, Archive
!
CREATE TABLE part (id INT PRIMARY KEY
AUTO_INCREMENT)!
PARTITION BY RANGE (id) (!
PARTITION p0 VALUES LESS THAN (10),!
PARTITION p3 VALUES LESS THAN MAXVALUE);!
! Integers: dates, ranges, server_id
Strings get hashed: tags, groups

18. Trying it out
EXPLAIN PARTITIONS SELECT * FROM part WHERE id < 30
G!
partitions: p0,p1!
type: range!
rows: 29!
!
EXPLAIN PARTITIONS SELECT * FROM part WHERE id < 8
G!
table: part!
partitions: p0!
type: range!
rows: 7

19. Thank you !