new approach to provide durability for in-memory databases with high performance and low cost

1. Durability for Memory-Based
Key-Value Stores
Kiarash Rezahanjani
July 4, 2012
1

2. Durability
Data Store
(university , KTH )
set(university , UPC)
Ack
get(university )
UPC
2

3. Durability
Data Store
set(university , UPC )
Commodity
Ack
Non Volatile
3

4. Durability
Data Store
set(myKey, U)
Commodity
Ack
4

5. Durability
Seek time
+
SLOW
Rotational time
+ Write Read
Transfer time
Disk
5

6. Cache in memory
Slow Writes Reads Fast
Cached Objects
Consistency ?
Primary copy of objects
6

7. Cache in memory
Stale data
Application Servers
Set ObjA Read ObjA - > Cache Miss
Spending resouces
Read Obj A Memcache servers
Complicates development Delete Obj A
Update Obj A
Writes are still Slow
MySQL Servers
7

8. Memory-Based Databases
No inconsistency Writes Reads
No stale data
Reads are fast Primary Copy of Objects
Durability?
Writes latency?
Back up
8

9. Approaches towards durability
State A State B Periodic Snapshots Data loss
Snapshot Snapshot
Synchronous logging Slow
Log Log Log
Asynchronous logging Data loss
Logs Logs
9

10. Approaches towards durability
Replica
Expensive
Data
Catastrophic Failure , All gone
Replica Replica
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11. Project Goals
Durable write
Low latency
Availability, able to recover quickly
Cheap, commodity hardware
11

12. Target systems
• Data is big = many machines
• Read dominant workload
• Simple key-value store
• Small writes
– Example: Facebook
• Tera bytes of data = 2000 memcache servers
• Write/read ratio < 6%
• Memcache is a key-value store
• Status update, tag photo, profile update, etc
12

13. Solution
13

14. Design decisions
Periodic snapshot
vs.
Message logging 
14

15. Design decisions
Local disk
vs.
Remote location 
15

16. Design decisions
Remote file server
vs.
Local disks of database cluster 
16

17. Design Decision
write
Database
client
Ack Log
Remote storage
17

18. Design Decision
write
Two Problems
Database
client 1) Synchronous logging
Ack Log Must
Asynchronous logging
Problems: Data loss
2) Data availability
Replication
18

19. Replication
Ack Log
Ack Log
Log Log Log
Replication
19

20. Replication
Broadcast Chain replication
Ack Log Ack Log
mast
er tail head
slave slave
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21. Replication
Broadcast
Ack Log
mast
er
slave slave
slave
21

22. Replication
Chain replication
Ack Log
tail head
22

23. Replication
Chain replication
Log
Ack
tail head
23

24. Chain Replication
write
Database
Ack client Log
Log Log Log
24

25. Chain Replication
Synchronous logging abstraction
write
Low latency Database
Ack client Log
Available Logs
Log Log Log
Stable Storage Unit
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26. Log Server
Log
26

27. Log Server
3 2 1
Reader
7
Receiver 6 5 3
Persister
Sequential Write
Seek time
2 1
27

28. Forming storage units
1. Query zookeeper
Zookeeper
2. Get list of servers
3. Leader send request
4. Leader send list of
members
ID1 ID2 ID3
5. Upload storage unit data
6. Start the service
28

29. Storage System
Zookeeper
Client
Client Stable storage unit Stable storage unit
Client
Stable storage unit Stable storage unit
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30. Failover
Cient
ID 1 ID 2 ID 3
50% 20% 30%
ID 4 ID 5 ID 6
40% 45% 20%
Stable Storage Unit Stable Storage Unit 30

31. Failover
Cient
ID 1 ID 2 ID 3
50% 20% 30%
ID 4 ID 5 ID 6
40% 45% 20%
Stable Storage Unit Stable Storage Unit 31

32. Failover
Cient
ID 1 ID 2 ID 3
50% 20% 30%
ID 4 ID 5 ID 6
40% 45% 20%
Stable Storage Unit Stable Storage Unit 32

33. Evaluation
• Throughput and latency of stable storage unit
– Log entry sizes
– Replication factors
• Comparison with WAL into local disk
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34. Single synchronous client
Replication factor of 3
Entry Size Latency(ms) Throughput(entries/sec)
(bytes)
200 0,45 2200
1024 0,62 1600
4096 0,99 1000
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35. Throughput vs. Latency
Replication factor of 3
3500
3000
2500
Latency (ms)
2000
5B
200 B
1500 1 KB
5000 4 KB
1000 14000 28000 10 KB
34000
500
0
0 5000 10000 15000 20000 25000 30000 35000 40000 45000
Throughput (entries/sec)
35

36. Additional replica
Entry size of 200 bytes
2000
1800
1600
1400
Latency (microsecond)
1200
1000
800 RF 3
RF 2
600
400
200
0
0 5000 10000 15000 20000 25000 30000 35000 40000
Throughput (entries/sec)
36

37. Sustained load
37

38. ‹#›

39. Resource utilization
• Throughput of 6,000 entries/sec
• Log entries of 200 bytes
– CPU utilization = 9%
– Bandwidth = 29 Mb/s
– Dedicated disk
– Small memory requirement
39

40. Summary
 Durable write
 Low latency
 High availability
 Scalable
 No additional resources
 Avoid dependencies 40