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WAGmob brings you Simple ‘n Easy, on-the-go learning ebook for “Big Data and Hadoop”.
The ebook provides:
Snack sized chapters for easy learning.
Designed for both students and adults.
This ebook provides a quick summary of essential concepts in Big Data and Hadoop by following snack sized chapters:
Introduction to Big Data:
• Introduction to Big Data
• Sources of Big Data
• Big Data Characteristics
• Big Data Analytics
• The Importance of Big Data
Big Data in the Enterprise:
• Big Data in the Enterprise
• Data Processing and Analytics: The Old Way
• Big Data Enterprise Model
• Building a Big Data Platform
Hadoop and Hadoop Infrastructure:
• Why Hadoop?
• How does Hadoop help?
• Hadoop Infrastructure
• How Data Model is Different?
• How Computing Model is Different?
• Hadoop framework
Hadoop Distributed File System (HDFS):
• HDFS: Hadoop Distributed File System
• HDFS: Files and Blocks
• Hadoop: A master-slave architecture
• HDFS: Data Placement and Replication
• Typical large –data problem
• MapReduce Paradigm – I
• Word count example
• MapReduce Paradigm – II
• MapReduce – Jobs and tasks
• MapReduce: A master-slave architecture
• MapReduce Programming Model
• MapReduce – word count mapper
• MapReduce – word count reducer
• MapReduce – word count main
• MapReduce – running a job
Relationship between MapReduce and HDFS:
• Relationship between MapReduce and HDFS
• Clients, Data Nodes, and HDFS Storage
• MapReduce workloads
• Hadoop Fault Tolerance
• Reading/Writing Files
Hadoop and Databases:
• Hadoop and Databases
• Typical Datacenter Architecture
• Adding Hadoop to the Mix
• The Key Benefit
• Flexibility: Complex Data Processing
The Hadoop Implementation:
• Job Execution
• Hadoop Data Types
• Job Configurations
• Input and Output Formats
Scenarios for Using Hadoop and Hadoop Live Use Cases:
• Scenarios for Using Hadoop
• Orbitz: Major Online Travel Booking Service
• Major National Bank
• Leading North American Retailer
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