In this talk we will take a look at the core concepts of Riak and why you might want to use it for your application, we will then take a look at some customer use cases and how Riak helped them scale with ease. Joel Jacobson is a Technical Evangelist at Basho Technologies where he helps build the Riak community across Europe. Prior to joining Basho, Joel worked closely with Neo Technologies as part of his role at the consultancy OpenCredo.

1. basho
Core Concepts
Introduction to Riak
AKQA
24th July 2013
Friday, 26 July 13

2. WHO AM I?
Joel Jacobson
Technical Evangelist
BashoTechnologies
@joeljacobson
Friday, 26 July 13

3. Distributed computing is
HARD.
Friday, 26 July 13

4. PROBLEMS?
• Concurrency and latency at scale
• Data consistency
• Uptime/failover
• MultiTenancy
• SLA’s
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5. WHAT IS RIAK?
• Key-Value store + extras
• Distributed and horizontally scalable
• Fault-tolerant
• Highly available
• Built for the web
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6. INSPIRED BY AMAZON DYNAMO
• White paper released to describe a database system to be
used for their shopping cart
• Masterless, peer-coordinated replication
• Dynamo inspired data-stores; Riak, Cassandra, Voldemort
etc.
• Consistent hashing - no sharding :-)
• Eventually consistent
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7. RIAK KEY-VALUE STORE
• Simple operations - GET, PUT, DELETE
• Value is opaque, with metadata
• Extras, e.g.
• Secondary Indexes (2i)
• MapReduce
• Full text search
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8. HORIZONTALLY SCALABLE
• Near linear scalability
• Query load and data are spread evenly
• Add more nodes and get more:
• ops/second
• storage capacity
• compute power (for Map/Reduce)
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9. FAULTTOLERANT
• All nodes participate equally - no single point of failure (SPOF)
• All data is replicated
• Clusters self heal - Handoff, Active Anti-Entropy
• Cluster transparently survives...
• node failure
• network partitions
• Built on Erlang/OTP (designed for FT)
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10. HIGHLY AVAILABLE
• Any node can serve client requests
• Fallbacks are used when nodes are down
• Always accepts read and write requests
• Per-request quorums
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11. QUORUMS - N/R/W
• Tunable down to bucket level
• n_val = 3 by default
• w / r = 2 by default
• w = 1 - Quicker response time, read could be inconsistent in
short term
• w = all - Slower response, increased data consistency
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12. CAPTHEOREM
• C = Consistency
• A = Availability
• P = PartitionTolerance
• Cap theorem states that a
distributed shared data
system can at most support
2 out of these 3 properties
DB DB DB
Client Client
Network/Data Partition
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13. THE RING
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14. REPLICATION
• Replicated to 3 nodes by default (n_val =3, which is
configurable)
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15. DISASTER SCENARIO
• Node fails
• Request goes to fallback
• Node comes back
• Handoff - data retuned to
recovered node
• Normal operations resume
automatically
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16. DISASTER SCENARIO
• Node fails
• Request goes to fallback
• Node comes back
• Handoff - data retuned to
recovered node
• Normal operations resume
automatically hash(“user_id”)
Friday, 26 July 13

17. ACTIVE ANTI-ENTROPY
• Automatically repair inconsistencies in data
• Active Anti-Entropy was new in 1.3.0 and uses Merkle trees to
compare data in partitions and periodically ensure consistency
• Active Anti-Entropy runs as a background process
• Can also be configured as a manual process
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18. CONFLICT RESOLUTION
• Network partitions and concurrent actors modifying the
same data cause data divergence
• Riak provides two solutions to manage this that can be set
on bucket level:
• Last Write Wins - an approach used for some use cases
• Vector Clocks - Retain “sibling” copies of data for merging
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19. VECTOR CLOCKS
• Every node has an ID
• Send last-seen vector clock in every “put” request
• Can be viewed as ‘commit history’ e.g Git
• Lets you decide conflicts
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20. SIBLING CREATION
0
32
1
Object
v1
Object
v1
[{a,3}]
[{a,2},{b,1}]
1) 2)
[{a,3}]
[{a,2},{b,1}]
0
32
1
Object
v1
Object v1
Object v1
• Siblings can be created by:
• Simultaneous writes (based on same object version)
• Network partitions
• Writes to existing key without submitting vector clock
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21. STORAGE BACKENDS
• Bitcask
• LevelDB
• Memory
• Multi
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22. BITCASK
• A fast, append-only key-value store
• In memory key lookup table (key_dir) data on disk
• Closed files are immutable
• Merging cleans up old data
• Developed by BashoTechnologies
• Suitable for bounded data, e.g. reference data
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23. LEVELDB
• Key-Value storage developed by Google
• Append-only for very large data sets
• Multiple levels of SSTable-like data structures
• Allows for more advanced querying (2i)
• It includes compression (Snappy algorithm)
• Suitable for unbounded data or advanced querying
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24. MEMORY
• Data is never persisted to disk
• Typically used for “test” databases
(unit tests... etc)
• Definable memory limits per vnode
• Configurable object expiry
• Useful for highly transient data
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25. MULTI
• Configure multiple storage engines for different types of data
• Configure the “default” storage engine
• Choose storage engine on per bucket basis
• No reason not to use it
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26. CLIENT APIS
• Riak supports two main client types:
• REST based HTTP Interface
• Easy to use from command line and simple scripts
• Useful if using intermediate caching layer, e.g.Varnish
• Protocol Buffers
• Optimized binary encoding standard developed by Google
• More performant than HTTP interface
Friday, 26 July 13

27. CLIENT LIBRARIES
• Client libraries supported by Basho:
• Community supported languages and frameworks:
• C/C++, Clojure, Common Lisp, Dart, Django, Go, Grails, Griffon, Groovy,
Erlang, Haskell, Java, .NET, Node.js, OCaml , Perl, PHP, Play, Python, Racket,
Ruby, Scala, Smalltalk
Friday, 26 July 13

28. • Using Riak as datastore for all back-end systems supporting
Angry Birds
• Game-state storage, ID/Login, Payments, Push notifications,
analytics, advertisements
• 9 clusters in use with over 100 nodes
• 263 million active monthly users
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29. • Spine2 project - storing patient data (80 million+)
• 500 complex messages per second
• 20,000 integrated end points
• 0 data loss
• 99.9% availability SLA
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30. • Push to talk application
• Billions of requests daily
• > 50 dedicated servers
• Everything stored in Riak
• https://github.com/mranney/node_riak
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31. MULTI DATACENTER
REPLICATION (MDC)
• Allows data to be replicated between clusters in different data
centers. Can handle larger latencies.
• Two synchronization modes that can be used together: real-
time and full sync
• Set up as uni-directional or bi-directional replication
• Can be used for global load-balancing, business continuity and
back-ups
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32. RIAK-CS
• Built on top of Riak and supports MDC
• S3 compatible object storage
• Supports multi-tenancy
• Per-tenant usage data and statistics on network I/O
• Supports Objects of Arbitrary ContentType Up to 5TB
• Often used to build private cloud storage
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33. PLAY AROUND WITH RIAK?
• https://github.com/joeljacobson/riak-dev-cluster
• https://github.com/joeljacobson/vagrant-riak-cluster
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34. THANKYOU
joel@basho.com
basho
Friday, 26 July 13