Part A: Introduction to Hadoop

1. Introduction to Big Data Hadoop
   • Hadoop Overview and History
   • Exploring Hadoop Ecosystem
   • Introduction to Cloudera Manager and CDH
2. Introduction to Hadoop Core Components: HDFS and YARN
   • HDFS Distributed File System
     • Understanding HDFS Architecture and Components
     • Hands on HDFS basics shell commands
   • YARN Resource Management
     • Understanding YARN Architecture and Components
   • Exploring Hadoop file formats (Which file format is better)
3. Using relational data stores with Hadoop
   • Introduction to Hive (Hive Architecture and how it works)
   • Overview of Hive supported file formats and Hive partition
   • Hands on HiveQL through Hue interface & Hive Client
   • Integrating MySQL with Hive using Sqoop
   • Use Sqoop to import data from MySQL to HDFS/Hive
   • Use Sqoop to export data from Hadoop to MySQL
4. Large Scale Data Processing Frameworks
   • Introduction to Hadoop MapReduce
     • What is it & How it works?
     • Practical MapReduce example
   • Introduction to Apache Spark
     • Overview of Spark Core Concepts and Architecture
       • Spark Clusters and the Resource Management System
       • Spark Application
       • Spark Driver and Executor
     • Introducing to Spark data structures: The Resilient Distributed Dataset (RDD) & RDD Operations
     • Hands On simple Spark jobs

Part B: Introduction to Radoop

1. Introduction to Radoop
   • Hadoop Integration with RapidMiner: Radoop
   • Introduction to the Radoop GUI
   • Connecting to a Hadoop Cluster
2. Data Exploration
   • Browsing Tables
   • Viewing Statistics and High-Level Information
3. Data Extraction and Loading
   • Formulation of Queries
   • Pushing Data into Hadoop
   • Clustering
4. Integration of In cluster Analyses into
   RapidMiner Processes
   • Modeling Algorithms
   • Natural Aggregation
   • In memory Training, in Hadoop Scoring
5. Beyond Natural Aggregation
   • Chunking
   • Voting
   • In Hadoop Modelling
   • Clustering