SF MySQL meetup June 2012

1. Caching
Memcached vs. Redis
San Francisco MySQL Meetup
Ryan Lowe
Erin O’Neill
1

2. Databases
WE LOVE THEM
...
Except when we don’t
2

3. When Databases Rule
• Many access patterns on the same set of
data
• Transactions (both monetary and isolated
units of work)
• Don’t know what the end state access
patterns will be
• Always :)
3

4. When Databases Suck
• Lots of concurrent users
• ORMs
• Big Data Sets
• Small Pockets of VERY hot data
4

5. How Caching Works
• External vs. built-in caching
• MySQL Query Cache
• InnoDB Buffer Pool
• Rails SOMETHING
5

6. Caching Architecture
Becomes
6

7. Why Caching Works
7

8. 8

9. 9

10. There are only two hard
problems in Computer
Science: cache invalidation,
naming things, and off-by-
one errors.
-- Martin Fowler
10

11. Problems with Caching
• Cache Misses
• Thundering Herd
• Stale Data
• Warm-Up Times
• Overly-Aggressive Caching
• Poor Cache Design
11

12. Cache Misses
Cache Hit: 1 Operation
Cache Miss: 3 Operations
12

13. Thundering Herd
• Key TOP_10_VIDEOS expires @ 9:00
• Generating the K/V takes three seconds
• Page gets 100 req/s = 100*3 = 300 threads!
13

14. Stale Data
• Must maintain consistency between the
database and the cache from within the
application
• Extremely difficult to validate correctness
14

15. Cache Warm-Up
• All attempts to read from the cache are
CACHE MISSES, which require three
operations.
• This can result in a significant degradation
of response time.
• Usually accompanied by a Thundering Herd
15

16. Use Cases
• Sessions • Tag Clouds
• Popular Items • Auto-suggest lists
• Full Page Cache • Relationships
• Profile • User Information
Information
• Online Users
• User Preferences • Statistics
16

17. Memcached
Memcached is an in-memory key-
value store for small chunks of
arbitrary data (strings, objects) from
results of database calls, API calls,
or page rendering.
17

18. Redis
Redis is an open source, advanced
key-value store. It is often referred
to as a “data structure server” since
keys can contain strings, hashes,
lists, sets and sorted sets.
18

19. In-Memory Means
We’re Bound By RAM
19

20. Consistent Hashing
• Each Key deterministically goes to a
particular server. Think (KEY % SERVERS)
20

21. Memcached
• Dead Simple & Battle Tested
• Fast
• Non-Blocking get()/set()
• Multi-Threaded
• Consistent Hashing
21

22. Memcached Example
employee_id = 1234
employee_json = {
name => ‘Ryan Lowe’,
title => ‘Production Engineer’ }
set(employee_id, employee_json)
get(employee_id) [Returns employee_json]
22

23. But I don’t want all the
data
• What if I just want the name?
• 64 Bytes for the object vs. 10 for just the
name :-(
• 6x network traffic
• More work for the application
• Fatter applications
23

24. Redis
• Advanced Data Types
• Replication
• Persistence
• Usually Fast
• Very Cool Atomic Operations
24

25. Redis: The Bad
• Single-Threaded
• Limited client support for consistent
hashing
• Significant overhead for persistence (do be
discussed later)
• Not widely deployed (compared to
Memcached)
25

26. Redis: Datatypes
• Strings (just like Memcached)
• Lists
• Sets
• Sorted Sets
• Hashes
26

27. Redis: Lists
• Stored in sorted order
• Can push/pop
• Fast head/tail access
• Index access (yay)
27

28. Redis: Lists
r.lpush(‘employees’, ‘Ryan Lowe’)
r.lpush(‘employees’, ‘Dave Apgar’)
r.lrange(‘employees’, 0, -1)
(‘Dave Apgar’, ‘Ryan Lowe’)
r.rpush(‘employees’, ‘Evan Miller’)
r.lrange(‘employees’, 0, -1)
(‘Dave Apgar’, ‘Ryan Lowe’, ‘Evan Miller’)
28

29. Redis: Sets
• Un-ordered collections of strings
• Unique (no repeated members)
• diff, intersect, merge
29

30. Redis: Sets
sadd(‘employees’, ‘Ryan Lowe’)
sadd(‘former_employees’, ‘Bryan Lowe’)
sdiff(‘former_employees’, ‘employees’)
(‘Ryan Lowe’,‘Bryan Lowe’)
30

31. Redis: Sorted Sets
• Same as Sets but ordered by a score
31

32. Redis: Hashes
r.hset(‘employees’, ‘count’, 1234)
r.hset(‘employees’,‘females’, 1000)
r.hset(‘employees’,‘males’, 234)
hget(‘employees’,‘count’)
“1234”
hgetall(‘employees’)
{ ‘count’ => 1234,
‘females’ => 1000,
‘males’ => 234 }
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33. Memcached vs. Redis
Memcached Redis
(multi)get ✓ ✓
(multi)set ✓ ✓
incr/decr ✓ ✓
delete ✓ ✓
Expiration ✓ ✓
prepend/append ✓
Range Queries ✓
Data Types! ✓
Persistence (sorta) ✓
Multi-Threaded ✓
Replication (sorta) ✓
33

34. Instrumentation
• Redis: info
• Memcached: stats
• Both give system information, connections,
hits, misses, etc.
• Graphite most of the metrics!!!
34

35. Benchmarks
35

36. About the Benchmarks
• 1 Hour
• Redis 2.6 & Memcached 1.4.5
• 64,000,000 Keys
"KEY_#{i.to_s}"
• 51-Character Values
(0...50).map{ ('a'..'z').to_a[rand(26)] }.join
36

37. Redis Benchmarks
37

38. Redis Set (1 Server)
1 Client 2 Clients 4 Clients 8 Clients
12 Clients 16 Clients 24 Clients 32 Clients
12000
10500
9000
7500
6000
4500
3000
1500
0
38

39. Redis Set (1 Server)
1 Client 2 Clients 4 Clients 8 Clients
12 Clients 16 Clients 24 Clients 32 Clients
12000
WTF?!
10500
9000
7500
6000
4500
3000
1500
0
39

40. Redis Set (1 Server)
1 Client 2 Clients 4 Clients 8 Clients
12 Clients 16 Clients 24 Clients
10000
8000
6000
4000
2000
0
40

41. Redis Set (2 Servers)
1 Client 2 Clients 4 Clients 8 Clients
12 Clients 16 Clients 24 Clients 32 Clients
16000
12000
8000
4000
0
41

42. Redis Set (2 Servers)
1 Client 2 Clients 4 Clients 8 Clients
12 Clients 16 Clients 24 Clients 32 Clients
16000
12000
8000 WTF?!
4000
0
42

43. Redis Set (4 Servers)
1 Client 2 Clients 4 Clients 8 Clients
12 Clients 16 Clients 24 Clients 32 Clients
16000
12000
8000
4000
0
43

44. Redis Set (8 Servers)
1 Client 2 Clients 4 Clients 8 Clients
12 Clients 16 Clients 24 Clients 32 Clients
16000
12000
8000
4000
0
44

45. Hash Ring Balance (%)
Server 1 Server 2
100
50
0
Redis Memcached
45

46. Hash Ring Balance (%)
Server 1 Server 2 Server 3 Server 4
50
25
0
Redis Memcached
46

47. Hash Ring Balance (%)
Server 1 Server 2 Server 3 Server 4 Server 5
Server 6 Server 7 Server 8
25
12.5
0
Redis Memcached
47

48. Redis Get (1 Server)
1 Client 2 Clients 4 Clients 8 Clients
12 Clients 16 Clients 24 Clients 32 Clients
125000
100000
75000
50000
25000
0
48

49. Redis Get (2 Servers)
1 Client 2 Clients 4 Clients 8 Clients
12 Clients 16 Clients 24 Clients 32 Clients
125000
100000
75000
50000
25000
0
49

50. Redis Get (4 Servers)
1 Client 2 Clients 4 Clients 8 Clients
12 Clients 16 Clients 24 Clients 32 Clients
125000
100000
75000
50000
25000
0
50

51. Redis Get (8 Servers)
1 Client 2 Clients 4 Clients 8 Clients
12 Clients 16 Clients 24 Clients 32 Clients
125000
100000
75000
50000
25000
0
51

52. The Cost of
Persistence
Redis No Persistence Redis BGSAVE (FIO) Redis AOF
12000
10000
8000
6000
4000
52

53. Redis & Memcached
Benchmarks
53

54. Set Operations
(1 Server, 24 Clients)
Memcached Redis
10000
9825
9650
9475
9300
54

55. Get Operations
(1 Server, 24 Clients)
Memcached Redis
130000
117500
105000
92500
80000
55

56. Set Operations
(2 Servers, 24 Clients)
Memcached Redis
13000
11750
10500
9250
8000
56

57. Get Operations
(2 Servers, 24 Clients)
Memcached Redis
140000
107000
74000
41000
8000
57

58. Set Operations
(4 Servers, 24 Clients)
Memcached Redis
13000
11750
10500
9250
8000
58

59. Get Operations
(4 Servers, 24 Clients)
Memcached Redis
140000
107000
74000
41000
8000
59

60. Set Operations
(8 Servers, 24 Clients)
Memcached Redis
12000
11000
10000
9000
8000
60

61. Get Operations
(8 Servers, 24 Clients)
Memcached Redis
150000
114500
79000
43500
8000
61

62. Conclusions
• Redis inconsistent under heavy load
• We need more benchmarks!
• (Redis) Datatype-specific
• Big Memory
• (Redis) Big Keys
62

63. Questions?
63