Big Data Hadoop Course

  • What is Big Data
  • Data Facts
  • Aspects / Principle of Big Data
  • Difference b/w Big Data & Traditional BI
  • Examples: Where to use Big Data
  • Big Data Business Opportunities
  • Distributed File System computation with Facebook Example
  • Understanding File System working
  • Basic commands of LINUX
  • Shell scripting
  • Use Cases – Assignments
  • Introduction to OOP’s concept
  • Understanding on Data types
  • Functions
  • Methods
  • Setup of Eclipse
  • Coding examples
  • Use Cases : Assignments
  • Concepts of Python
  • Data Types in Python
  • Exception Handling in Python
  • File Handling in Python
  • Introduction to Flume
  • Setup of Flume Components
  • Source
  • Sink
  • Channel
  • Agents
  • Use Cases – Assignments
  • Introduction to SPARK
  • Understanding of RDD, Contexts
  • Developing Application in SPARK
  • Use Cases – Assignments
  • Understanding Hadoop Architect
  • Basic Understanding of Hadoop core components
  • In depth understanding of HDFS
  • Understanding HDFS services – NameNode & DataNode
  • Understanding on File System Read & Write
  • Real-time Cluster setup based on requirement
  • Understanding YARN Architect
  • Architect Difference b/w Hadoop 1.x & Hadoop 2.x
  • Understanding File System Read & Write
  • Hadoop 1.x
  • Environment Settings
  • Pseudo Mode Installation
  • Distributed Mode Installation
  • Basic configuration of Hadoop properties
  • Understanding in-built scripts
  • Running Basic Map Reduce code
  • Hadoop 2.x
  • Environment Settings
  • Distributed Mode Installation
  • Configuration of Hadoop properties
  • Running Basic Map Reduce Code
  • Hadoop File system commands
  • Introduction to Sqoop
  • Setup of Sqoop
  • Sqoop Import commands
  • Sqoop Export commands
  • Formats in Sqoop
  • Use Cases – Assignments
  • Introduction to PIG Latin
  • Setup of Pig
  • Independent Mode
  • Map Reduce Mode
  • Basic commands in Pig
  • Functions in Pig
  • Developing UDF’s in Java
  • Use Cases – Assignments
  • Understanding of Map Reduce services – JobTracker &
    TaskTracker
  • Map Reduce Flow Chart
  • Map Reduce Phases
  • Mapper
  • Reducer
  • Splitting
  • Sorting
  • Shuffling
  • Combiner
  • Partitioning
  • Developing Map Reduce applications – JAVA Code
  • Developing Map Reduce applications – Python Code
  • Discussion on Input File Formats
  • Difference b/w Old MR API & New MR API
  • Use Cases – Assignments
  • Introduction to HIVE Architecture
  • Setup of Hive
  • Basic queries in HIVE
  • Advance Features of HIVE
  • Partitioning
  • Bucketing
  • Serialize & De-serialize
  • Query optimization in Hive
  • Use Cases – Assignments
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