Tom Wilkie's talk at Progressive NOSQL conference in London on 11/05/12.

1. A tunably consistent, highly-
available, Distributed Database
Tom Wilkie @tom_wilkie
Founder & VP Engineering, Acunu
1

2. • Overview
• Distribution
• Storage
• Datamodel
• Usecases
2

3. • Overview
• Distribution
• Storage
• Datamodel
• Usecases
3

4. • A distributed database for Big Data
• Scale out on commodity servers
• Best of bread performance
• Multi-master architecture, no SPOF
• Powerful multi data centre support
4
4

5. 5
5

6. BigTable, 2006 Dynamo, 2007
Open sourced, 2008
TLP, 2010
Incubator, 2009 v1.0 2011
6

7. BigTable: ...
• Simple but powerful datamodel
• Write-optimised storage system
• Consistent, available but not partition tolerant
• Master-slave distribution system, SPOF
http://goo.gl/7T1Ej
7
7

8. Dynamo: ...
• Sophisticated distribution system with tradable
consistency and availability
• Over-simple datamodel
http://goo.gl/Q80b4
8
8

9. • Overview
• Distribution
• Storage
• Datamodel
• Usecases
9

10. Distribution: Consistent Hashing
→
r1, c1
v1
→
r2, c2
v2
→
r3, c3
v3
10
10

11. Distribution: Scaling
11
11

12. Distribution: Scaling
12
12

13. Distribution: Scaling
• .
13
13

14. Distribution: Scaling
14
14

15. Distribution: Scaling
15
15

16. Distribution: Replication
→
r1, c1
v1
16
16

17. Distribution: Replication
17
17

18. Distribution: Consistency
Tuneable, per-operation consistency
Timestamped values, N > R + W
W R
18
18

19. Distribution: Read Repair
19
19

20. Distribution: Read Repair
20
20

21. Distribution: Read Repair
21
21

22. Distribution: Read Repair
22
22

23. • Overview
• Distribution
• Storage
• Datamodel
• Usecases
23

24. Writing to Cassandra
Row Key Column Column Column Column
24
24

25. Writing to Cassandra
In the JVM
Row Colu Colu Colu Colu
Memtable
On disk Commit
log
25
25

26. Writing to Cassandra
In the JVM
Full Memtable
On disk Commit
log
26
26

27. Writing to Cassandra
In the JVM
New Memtable
On disk Commit
SSTable
log
27
27

28. Writing to Cassandra
On disk Commit
SSTable
log
SSTable
SSTable
SSTable
SSTable
SSTable
28
28

29. Writing to Cassandra
On disk Commit
log
SSTable
29
29

30. Reading from Cassandra
30

31. 2
Off-heap Row cache
(no GC)
1
In the JVM Memtable
3 4 5
SSTable
Bloom filter Key cache
index
6
On disk Commit log SSTable
31
31

32. • Overview
• Distribution
• Storage
• Datamodel
• Usecases
32

33. SQL Cassandra
Database row/key col_1 col_2
Keyspace
row/key col_1 col_1
row/ col_1 col_1
Table Column Family
33
33

34. col1 col2 col3 col4 col5 col6 col7
row1 x x x
row2 x x x x x
row3 x x x x x
row4 x x x x
row5 x x x x
row6 x
row7 x x x
34
34

35. alice: {
m2: {
Sender: bob,
Subject: ‘paper!’, ...
}
}
bob: {
m1: {
Sender: alice,
Subject: ‘rock?’, ...
}
}
charlie: {
m1: {
Sender: alice,
Subject: ‘rock?’, ...
},
m2: {
Sender: bob,
Subject: ‘paper!’, ...
}
}
35
35

36. • Overview
• Distribution
• Storage
• Datamodelling
• Usecases
36

37. Perfect for high velocity data
Web, SCM, Retail Location Services Cloud Monitoring
Social Gaming Social Media Ad Marketplaces
Fraud Detection Smart Metering Oil/Gas Sensors
37
Confidential 6
Wednesday, 25 April 12
37

38. Not Covered...
• Distribution: Hinted Handoff, Anti-entropy repair,
Counter distribution
• Storage: Counter storage, different compaction
strategies, partitioning etc
• Datamodel: de-normalisation, TTLs, secondary
indexes, CQL, super-columns, schema optional
• Operations: backup, nodetool, performance tuning
• Integration: Hadoop, Client Libraries etc
38
38

39. • Distributed, scalable database
• Opensource, widely used
• Tunably consistent
• Highly-available
• Partition tolerant
• Write-optimised
• Schema-optional
39

40. Data Platform
40

41. Data Platform
Data driven applications Web UI
Acunu Analytics
Control
Apache Cassandra
Center
Acunu Storage Engine
Configured and tuned OS
Commodity Hardware
41

42. Control Center
“I've had the EC2 instance running for a little while and I
have to say, I'm impressed. You guys have done well with
this product.”
- Lloyd, JustDevelopIt
42

43. Control Center
“The new UI has been critical in helping us work out
what is wrong in our code”
- Matt, TellyBug
43

44. Castle: Built for Big Data
• Storage engine optimized for large slow disks,
many cores, Big Data workloads
• Enterprise density on commodity hardware
• Lightning disk rebuilds:10x faster than RAID
Shared memory interface
Castle
keys
Userspace
Acunu Kernel
userspace
interface
values
In-kernel
async, shared
memory ring workloads
shared buffers
kernelspace
Streaming interface
interface
range key buffered key buffered
queries insert value insert get value get
Doubling Arrays • Opensource (GPLv2, MIT
doubling array
mapping layer
for user libraries)
insert Bloom filters
queues key
get
arrays x
range arrays
queries management
http://goo.gl/gzihe
key
•
insert merges
http://bitbucket.org/acunu
Arrays
mapping layer
•
modlist btree
key Version tree
Loadable Kernel Module,
insert btree
key
get
btree
targeting CentOS’s 2.6.18
range
queries value arrays
44
•
Cache
block mapping &
http://www.acunu.com/
cacheing layer
"Extent" layer
prefetcher
extent block
extent cache
blogs/andy-twigg/why-
freespace
allocator
manager
44
flusher

45. 45

46. Rebuild time
5
4
Rebuild Time (Hours)
3
2
1
0 RAID10, 8 Disks RAID5, 8 Disks RDA, 8 Disks RDA, 15 Disks
46
46

47. Analytics
counter
updates
Click stream events
Acunu
Sensor data
Analytics
etc
• Simple, real-time, incremental analytics
• Push processing into ingest phase
47

48. Questions?
tom@acunu.com
@tom_wilkie
www.acunu.com
48

49. Introduction
Live & historical
aggregates...
49
49

50. Realtime trends...
50
50

51. Drill downs
and roll ups
51
51

52. Solution Con
Scalability
$$$
Not realtime
Inefficient Recomputation
Spartan query semantics =>
complex, DIY solutions
52
52