Not Only SQL (NoSQL)
Databases - Riak

SQL is Good

• Relational Databases Management Systems (RDMBSs) – mainstay of business

SQL is good
• Rich language
• Easy to use
• Rich tool set
• Promise: ACID

ACID

• Atomicity: all included statements in a transaction are either executed or  the whole transaction is aborted without affecting the database.
• Consistency: a database is in a consistent state before and after a  transaction. 
• Isolation: transactions can not see uncommitted changes in the database.
• Durability: changes are written to a disk before a database commits a  transaction so that committed data cannot be lost through a power failure.

SQL Challenges

Web­-based applications caused spikes.
• Internet­-scale data size
• High read­-write rates
• Large data

RDBMS were not designed to be distributed.

What is NoSQL

• Class of non­-relational data storage systems.
• All NoSQL offerings relax one or more of the ACID properties.
• Social applications are not banks and they don't need the same level of ACID.

NoSQL History

• It was first used in 1998 by Carlo Strozzi to name his relational  database that did not expose the standard SQL interface.
• The term was picked up again in 2009 when a Last.fm develper, Johan  Oskarsson, wanted to organize an event to discuss open­source  distributed databases.
   
• The name attempted to label the emergence of a growing number of  non­relational, distributed data stores that often did not attempt to  provide ACID

Consistency

• Strong consistency
• Single storage image. Informally, after an update completes,
   any subsequent  access will return the updated value.
  

southern-sun.blogfa.com

Consistency

• Eventual consistency
• The system does not guarantee that subsequent accesses will return the 
  updated  value.
• Inconsistency window
• If no new updates are made to the object, eventually all accesses
   will return the last updated value.
  

Quorum Model

• Quorum: the minimum number of members of an assembly or society that must be present at any of its meetings to make the proceedings of that meeting valid.
• N, R and W
• user can choose some number W-of-N nodes required for a write to succeed
• user can specify the number of nodes (R-of-N) to be contacted during a read.
• To enforce strong consistency: R + W > N
• N is rarely more than 3: keeping that amount of copy of data gets expensive!
• Basho's Riak (N = 3, R = 2, W = 2 default)
• Linkedin's Voldemort (N = 2 or 3, R = 1, W = 1 default)
• Apache's Cassandra (N = 3, R = 1, W = 1 default)

BASE Properties

• Basically Available: possibilities of faults but not a fault of the whole system.
• Soft state: copies of a data item may be inconsistent.
• Eventually consistent: copies becomes consistent at some later time if
   there are no more updates to that data item.

CAP Theorem

• states that it is impossible for a distributed computer system to simultaneously provide all three of the following guarantees:
• Consistency: All clients always have the same view of the data.
• Availability: Each client can always read and write.
• Partition Tolerance: The system works well despite physical network partition.

CAP Theorem

Riak

• Riak is a distributed, scalable, open source key/value store
• originally developed by Basho Technologies to run a Salesforce automation business
• heavily influenced by Dr. Eric Brewer’s CAP Theorem and Amazon’s Dynamo.
• The Riak APIs
• Storage operations use HTTP PUTs or POSTs and fetches use HTTP GETs
• fully-featured Protocol Buffers API: a simple binary protocol based on the library Google’s open source project of the same name.
• Client Libraries
• Ruby, Java, Erlang, Python, PHP, and C/C++

Buckets, Keys, and Values

• the only way to organize data inside of Riak.
• Data is stored and referenced by bucket/key pairs.
• Each key is attached to a unique value that can be any data type.

Clustering

• Central to any Riak cluster is a 160-bit integer space which is divided into equally-sized partitions.
• Physical servers, referred to in the cluster as “nodes”, run a certain number of virtual nodes, or “vnodes”.
• As a rule, each node in the cluster is responsible for 1/(total number of physical nodes) of the ring
• #vnodes on each node = (number of partitions)/(number of nodes)
• Nodes can be added and removed from the cluster dynamically and Riak will redistribute the data accordingly.

Clustering

Replication

• Riak controls how many replicas of a datum are stored via a setting called “N value”
• All nodes in the same cluster should agree on and use the same N value.
• Riak uses a technique called ‘hinted handoff’ to compensate for failed nodes in a cluster: self-healing

Reading, Writing, and Updating Data

• Using the Riak APIs, Riak objects can be fetched directly if the client knows the bucket and key. This is the fastest way to get data out of Riak.
• R Value: the number of Riak nodes which must return results for a read before the read is considered successful.
• Read Failure Tolerance
• R - N will tell you the number of down or laggy nodes a Riak cluster can tolerate before becoming unavailable for reads.
• For example, an 8 node cluster with an N of 8 and a R of 1 will be able to tolerate up to 7 nodes being down before becoming unavailable for reads.

Reading, Writing, and Updating Data

• Vector Clocks: Each update to a Riak object is tracked by a vector clock.
• Vector clocks allow Riak to determine causal ordering and detect conflicts in a distributed system.
• Conflict Resolution:
• The last update automatically “win”
• Return both versions of the object to the client: client itself resolve the conflict

Map Reduce

• Allows to process data in real-time in parallel
• MapReduce jobs are described in JSON using a set of nested hashes describing the inputs, phases , and timeout for a job.
• A job can consist of an arbitrary number of Map and Reduce phases.
• MapReduce in Riak can be thought of as a real-time “mini-Hadoop”
• A job is submitted via HTTP and the results are returned in JSON-encoded form.

What NOT Covered

• Secondary Indexes
• Links and Link Walking
• Riak Search
• Commit Hooks
• ...

Thanks

References

• [Presentation] NoSQL Databases - Amir H.Payberah, April 2012
• [Web] https://docs.basho.com/riak/1.2.1/references/appendices/concepts/
• [Web] https://en.wikipedia.org/wiki/MapReduce
• [Book] Seven Databases in Seven Weeks - A Guide to Modern Databases and the NoSQL Movement; Eric Redmond and Jim R. Wilson