This presentation includes information that is confidential and proprietary to Basho Technologies and should not be forwarded or distributed without Basho's prior written consent. © 2014. Basho Technologies, Inc. All Rights Reserved. This presentation includes information that is confidential and proprietary to Basho Technologies and should not be forwarded or distributed without Basho's prior written consent. © 2014. Basho Technologies, Inc. All Rights Reserved. Matt Brender Developer Advocate From Relational to Riak
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This presentation includes information that is confidential and proprietary to Basho Technologies and should not be forwarded or distributed without Basho's prior written consent. © 2014. Basho Technologies, Inc. All Rights Reserved.
This presentation includes information that is confidential and proprietary to Basho Technologies and should not be forwarded or distributed without Basho's prior written consent. © 2014. Basho Technologies, Inc. All Rights Reserved.
Matt Brender Developer Advocate
From
Relational to Riak
Relational databases give us a lot
Relationships Transactions Schemas Ad-hoc queries (SQL)
RDBMS BE LIKE
4
=>
RDBMS BE LIKE
5
OR
It’s not about NoSQL
What we really need..
is a database that makes my app faster
Enter Riak
Scalable Key => Value Schema-less Eventually Consistent Highly Available
Key => Value Masterless Schema-less Fault Tolerant High Availability Queries & Search
Scalable
Riak has a masterless architecture in which every node in a cluster is capable of serving read and write requests.
Requests are routed to nodes using standard load balancing appliances or software like Nginx or HAProxy.
Scalable
Data is guaranteed to be evenly distributed. Instead of manually sharding (partitioning) data Riak automatically distributes data evenly across a cluster by hashing keys using the SHA-1 algorithm that converts the key (bucket/key combination) into a number from:
0 - 1,461,501,637,330,902,918,203,684,832,716,283,019,655,932,542,976
or
0 - 2160
Scalable
Consistent Hashing – The Ring
0 - 2160
• Linear ScalingRiak scales in a near-linear fashion so increasing the number of a nodes in a cluster increases the number of reads and writes a cluster can handle in a predictable fashion.
If 10 nodes can serve: 40,000 Writes/Second
Then 20 nodes should serve: 72,000+ Writes/Second
“To enable rapid iteration at scale, Riot moved to Riak to support millions of concurrent players at any moment.”
Scalable
RELATIONAL SCALABILITY
16
• Designed for vertical scale
• Cost Considerations a key element of vertical scaling
• Sharding or re-distribution is I/O intensive
A - K L - P Q - Z
Key => Value
Riak stores data as a combination of keys and values in buckets
• Keys – simply binary values used to identify Objects.*
• Values – can be numbers, strings, objects, binaries, etc.
• Buckets – used to define a virtual namespace for storing Riak objects.
Key => Value
curl http://127.0.0.1:8098/types/places/buckets/country/keys/US
{
"Alpha2_s": "US”, "Alpha3_s": "USA”, "EnglishName_s": "United States”, "NumericCode_i": 840 }
Riak offers both HTTP and Protocol Buffers APIs. The following HTTP API example uses curl to retrieve a value by key:
Note: Protocol buffers are Google's language-neutral, platform-neutral, extensible mechanism for serializing structured data – think XML, but smaller, faster, and simpler.
There are a diverse group of client libraries for Riak that support both the HTTP and Protocol Buffer APIs:
Key => Value
Basho Supported Libraries:• Java• Ruby• Python• PHP• Erlang• .NET• Node.js
Community Libraries:• C• Clojure• Go• Perl• Scala• R
Schemas are not enforced by Riak, but by your application.
Schema-less
You still:• Design a schema• Denormalize dependent
data types
But get:• Single reads for common
access patterns• Richer, simpler data
structures
curl http://127.0.0.1:8098/types/places/buckets/country/keys/US
{
"Alpha2_s": "US”, "Alpha3_s": "USA”, "EnglishName_s": "United States”, "NumericCode_i": 840 }
Schemas are not enforced by Riak, but by your application.
Schema-less
Application Type Key Value
Session User/Session ID Session Data
Advertising Campaign ID Ad Content Logs Date Log File
Sensor Date, Date/Time Sensor Updates
User Data Login, email, UUID User Attributes
Content Title, Integer Text, JSON/XML/HTTP document, images, etc.
Eventually Consistent
C = ConsistencyA = AvailabilityP = Partition Tolerance
Client Client
DBDBDB
Network Partition
Cap theorem states that a distributed system can at most support 2 out of these 3 properties
Eventually Consistent
Read repair operations take place on every successful read, which updates replicas copy that may be out of sync.
Active anti-entropy (AAE) is a background operation that compares Merkle trees to repair operations.
Nodes periodically send their current view of the ring state to a randomly selected peer over gossip protocol.
get(“bucket/key”)
Eventually Consistent
Dotted Version Vectors are a tool used by Riak to track the logical sequence of updates to a key/value pair (versus the chronological order of events) and manage the process of merging siblings created as one of the side effects of eventual consistency.
A:1 B:1A:1
C:1B:1
C:2B:1 C2
C1
> curl http://127.0.0.1:8098/types/places/buckets/country/keys/US Siblings: 47fGOQwxRzq6wsbM7idvFB 2mJD0DEGoxdxdHUqS3bYt3 7Y68tqVG99xHBDu7AKtmb4
> curl -H "Accept: multipart/mixed" http://127.0.0.1:8098/types/places/buckets/country/keys/US
--RigRoRk6lkPXYIqBOv1jKEacnlr Content-Type: application/json Link: </buckets/country>; rel="up” Etag: 47fGOQwxRzq6wsbM7idvFB Last-Modified: Wed, 05 Nov 2014 22:44:00 GMT {"Alpha2_s":"US","Alpha3_s":"USA","EnglishName_s":"United States","NumericCode_i":840} --RigRoRk6lkPXYIqBOv1jKEacnlr Content-Type: application/json Link: </buckets/country>; rel="up”
...
Eventually Consistent
Riak Data Types (Convergent Replicated Data Types or CRDTs) are a developer-friendly way to keep track of updates in an eventually consistent environment:
• MapSupports the nest of and of the Riak Data Types.
• RegisterA named binary field that can only be used as part of a Map.
• Counter Keeps tracks of increments and decrements on an integer
• FlagValues limited to enable or disable
• SetA collection of unique binary values that supports add and remove operations on one or more values
Eventually Consistent
Hinted handoff allows Riak nodes to temporarily take over storage operations for a failed node and update that node with changes when it comes back online.
put(“bucket/key”)
High Availability
RELATIONAL AVAILABILITY
28
• Master/Replica Architecture
• Assumption of Transactional Consistency
• What happens under failure conditions?
master
replica replica replica
coordination
X X
Write/ Read
Write/ Read
WAIT
master
coordination
Riak automatically replicates between clusters• Configurable number of
remote replicas• Options for real-time sync and
full sync• Spanning tree support for
cascading replication
Geo-Data Locality allows localized data processing
• Reduced latency to end-users
• Allows sub 5ms responses • Active-Active ensures
continuous user experience
High Availability
Riak Multi-Datacenter (MDC) Replication
IN REVIEW
RDBMS BE LIKE
32
OR
CV CV
NoSQL Database
Unstructured Data
No pre-defined Schema
Small and Large Data Sets on Commodity HW
Many Models:
K/V, document store, graph
Variety of Query Methods
RELATIONAL & NOSQL What’s the difference?
Relational Database
Structured Data
Defined Schema
Tables with Rows/Columns
Indexed
w/ Table Joins
SQL
33
Biggest change for dev: reads
Biggest change for ops: administration
THE COST OF DOWNTIME
36
WHAT YOU WILL GAIN
37
More flexible, fluid designs
More natural data representations
Scaling without pain
Reduced operational complexity
RIAK DEPLOYED WORLDWIDE
39
Questions
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