캐시 분산처리 인프라

1. 분산 캐시
Park Chunduck. Hallym univ.

2. What is cache?
• Cache is a component that transparently stores
data so that future requests for that data can
be served faster –wikipedia
• Cache 는 나중에 요청 받을 데이터를 미리 저장해두었다가 빠르게
서비스 해 주는 것

3. Data and Cache
• Lots of Data
• cache

4. CPU cache

5. CPU cache

6. Brower cache 1)

7. Brower cache 2)

8. Cache use case : Login
• Common case
– Read from DB
• Select * from users where id=‘sogangori’;

9. Normal DB composition
일반적인 DB구성
• All traffic processed by Master 모든 트래픽 담당
– Overhead!
• Slave for emergency prepare 장애 대비

10. How Reduce Overhead?
• Scale UP vs Scale Out
– No Scale Down 이런 거 없다
scale Up!

11. Scale up

12. Scale out

13. Scale up/Scale down
• Simpleness
– High / Low
• Prices
– High / Low
• Expandability 확장성
– Low / High
• OK! Let’s Go Scale Down

14. Request analysis
• Read 70%, Write 30%
– Let’s distribute Read Request!!
• One Write Master + Multi Read Slave

15. Composition
• At early stage… 초기에는 좋았다

16. Performance Decrease
• Further Workload bigger, performance decreased.
– 부하가 더 커지니 성능 향상 효과가 미비해지다.
• Databases eventual consumed by writing.

17. Solution 1 : SSD
• Performance !
• Money ?

18. Solution 2 : Partitioning
• Let’s go Scalable Partitioning
– Performance Up!
– Management Issue Up!!??
– Cost Up??

19. Use Case Detail
• Login
– Read from cache

20. General Cache Layer

21. Cache Type
• 1 key – N Items
• 1 key – 1 Item

22. Cache Type Pros&Cons 장단점
• 1 key – 1 Item
– Pros : if 1 item is changed, just change that
item.
– Cons : some items can be removed
• 1 key – N Items
– Pros : just 1 get
– Cons :
• if 1 item is changed, need cache update
• Race codition 경합 조건

23. Divide Data
Changeable Data
Divide
Constable data

24. Memcache Performance
• Memcache vs Mysql
– 136 vs 1,613 (seconds)

25. Memcached in Facebook
• Facebook has a billion(10억) users in a
single day, says Mark Zuckerberg
– 28 August 2015
– 1 in 7 people on Earth used Facebook

26. Memcached in Facebook
• 2010. 4 When day user was half of billion(Today
is billion 10억명)
– Active User 70 million
– Web Request 40 million
– Web Server 10,000 Memcached Server 800 -> 15TB
– Mysql Server 1,800 Mater/slave(900+900)
• Mem:25TB, SQL Query 500,000 on second

27. Naver Datacenter 각
• IDC(Internet Data Center) in ChunCheon city

28. NAS vs 1 unit size Server
• NAS(network attached storage)
– Price High
– Performance High
– Extention?
• Buy one more..

29. NAS vs 1 unit size Server
• 1 unit size server
– Price low
– Performance low
– Extention High

30. • http://datacenter.navercorp.com/ko/index.html

32. Naver Owner-based File System
• Use multy cheap servers, multy cheap disks
• 3 copy Policy(back up) for Safety