This document is intended for only AVEA İletişim Hizmetleri A.Ş.("AVEA"), its dealers, employees and/or others specifically authorised. The contents of this document are confidential and any disclosure, copying, distribution and/or taking any action in reliance with the content of this document is prohibited. AVEA is not liable for the transmission of this document in any manner to any third parties that are not authorised to receive. Big Data – Hadoop - NoSQL and Graph Database Ramazan FIRIN 20.11.2012
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This document is intended for only AVEA İletişim Hizmetleri A.Ş.("AVEA"), its dealers, employees and/or others specifically authorised. The contents of this document are confidential and any disclosure, copying, distribution and/or taking any action in reliance with the content of this document is prohibited. AVEA is not liable for the transmission of this document in any manner to any third parties that are not authorised to receive.
Big Data – Hadoop - NoSQL and Graph DatabaseRamazan FIRIN20.11.2012
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AGENDA
• Big Data
• Hadoop
• NoSQL
• Graph DB and Neoj
• Possible Usage in Tellco
• Demo
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Executive Summary
R&D /MW DevelopementAVEA
• Big Data is a new IT trend
• Hadoop and NoSQL can used to process Big Data
• Possible usage area in Tellco : - Prevent Churn - to offer customer spesific campaign - to get more customer
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What is Big Data?
Datasets that are too awkward to work with using traditional,
hands-ondatabase management tools.
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Big Data- 3V Concept
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Big Data Sources
1. Social network profiles -Facebook, LinkedIn, Yahoo, Google
2. Social influencers - blog comments, user forums, review sites,
3. Activity-generated data - application logs, sensor data
4. Public—Wikipedia, IMDb, etc
5. Data warehouse appliances - transactional data
6. Network and in-stream monitoring
7. Legacy documents—
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Big Data To Smart Data
Cover of The Economist
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Volume
/
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New Data Sources - Internet
• 2 Billion internet users by 2011
• Twitter processes 7 terabytes data of every day
• Facebook processes 10 terabytes data of every day
• 4.6 billion mobile phone
• Google processes 24 petabytes data of every day
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Big Data Approach
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Big Data Design
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Big Data Usage Sector
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Sample Usage - 360°Degree View of the Customers
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Sample Usage – Customer Sentiment
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Sample Usage – Detect Churn Pattern
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Sample Usage - Healty
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Big Data Market
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Big Data Solutions – Oracle Big Data Appliance
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Big Data Solutions – IBM Pure Data
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TOP 10 Tecnology Trend 2012 from CSC
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Gartner: Top 10 IT Trends for 2013
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Gartner:10 Critical IT Trends For The Next Five Years
• Third trend is Bigger data and storage:
• By 2015, big data demand will generate 1 million jobs in the Global 1000,
• but only a one-third of jobs will get filled due to shortage of talent.
• Analytics and pattern recognition are key.
• Seeing new specialized ARM-based servers to do specialty analytics.
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HADOOP
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What is HADOOP?
The Apache Hadoop software library is a framework that
allows for the distributed processing of large data sets
across clusters of computers using simple programming models
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History
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Hadoop Components
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Hadoop Ecosystem
Pig - simplifies hadoop programming, data processing language
Hive - SQL like queries
HBase - Random read/write, billions of row and millions of colums (NoSQL)
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Other Google Research
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NoSQL
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RDBMS PERFORMANCE
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Join is killer...
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What is NoSQL?
• Stands for Not Only SQL
• Non relational
• Cheap, Easy to implement
• Scalability
– Vertically - Add more data
– Horizontally - Add more storage
• No pre-defined schema
• No join operations
• Not ACID, support CAP threom
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NoSQL DB Types
1. Key-values Stores
2. Document Databases
3. Column Family Stores
4. Graph Databases
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Key-Value Stores
- Redis, Voldemort
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Document Database
- CouchDB, MongoDB
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-Cassandra, HBase
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Graph Database
- Neo4J, InfoGrid, Infinite Graph
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RMDBS Support ACID
• Atomicity - a transaction is all or nothing
• Consistency - only valid data is written to the database
• Isolation - pretend all transactions are happening serially and the data is correct
• Durability - what you write is what you get
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NoSQL Support CAP Threom
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NoSQL Support CAP Theorem
• Consistency - each client always has the same view of the data.
• Availability - all clients can always read and write.
• Partition tolerance - if one or more nodes fails the system still works
You can pick only two...
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Visual Guide to NoSQL Systems
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NoSQL Complexity
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NoSQL Performance
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Job Trends
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Graph DB and Neo4j
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Graph DB
Graph database uses graph structures with nodes, edges, and properties to represent and store data.
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Graph DB Usage Area
• Recommendations
• Business Inteligence
• Social networking
• MDM
• System Management
• Time Series data
• Product Catalogue
• Web Analitics
• Scientific Computing
• Indexing your slow RMDBS
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Relational Databases are Graphs!
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Neo4j
• Leading Graph Database
• Transaction support (ACID)
• Indexing
• Querying
• REST support
• Disk Based
• Opensource
• Traversal framework
• High Performance (traverse 1.000.000 + relationship/seconds)
• Robust (in 7/24 operation since 2003)
• Massive scalability
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Neo4j Data Model
Neo4j has Nodes and Relationship.
Nodes and realtionships have properties.
Node1
Node2
Property:name
Property:surname
Property:name
Property:surname
Relationship
Relationship type : knowsProperty : Date of meeting
