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Hadoop

Hadoop

Module 1: Introduction to Big Data and Hadoop

  • Definition and characteristics of Big Data
  • Importance and challenges
  • Introduction to Apache Hadoop
  • Hadoop’s role in handling Big Data
  • Components of the Hadoop ecosystem (HDFS, MapReduce, etc.)
  • Hadoop distributions and versions

Module 2: Hadoop Distributed File System (HDFS)

  • Overview of the HDFS architecture
  • Data storage and retrieval in HDFS
  • Interacting with HDFS using command-line tools
  • Managing files and directories in HDFS

Module 3: MapReduce Programming Model

  • Understanding the MapReduce programming model
  • Key components: Mapper, Reducer, and Shuffling
  • Developing and running MapReduce applications
  • Debugging MapReduce programs

Module 4: Hadoop Programming Languages

  • Basics of Java programming for Hadoop
  • Writing MapReduce programs in Java
  • Overview of using Python with Hadoop
  • Developing MapReduce applications in Python

Module 5: Hadoop Ecosystem – Beyond MapReduce

  • Introduction to Hive for data warehousing
  • Querying data using HiveQL
  • Overview of Pig for high-level scripting
  • Writing Pig Latin scripts

Module 6: Apache Spark and Hadoop Integration

  • Overview of Spark and its advantages
  • Spark’s relationship with Hadoop
  • Basics of Scala programming for Spark
  • Developing Spark applications

Module 7: Hadoop Cluster Setup and Administration

  • Planning and setting up a Hadoop cluster
  • Configuring nodes and services
  • Tools for monitoring Hadoop clusters
  • Performing maintenance tasks

Module 8: Hadoop Security

  • Authentication and authorization in Hadoop
  • Implementing Hadoop security features
  • Ensuring data privacy and compliance
  • Securing Hadoop applications

Module 9: Hadoop Case Studies and Real-World Applications

  • Analyzing successful Hadoop implementations
  • Case studies from various industries
  • Applying Hadoop skills to real-world scenarios
  • Developing and presenting Hadoop projects

Module 10: Future Trends in Hadoop and Big Data

  •  Evolving Technologies – Exploring emerging technologies in Big Data – Trends in the Hadoop ecosystem
  •  Career Opportunities and Continuous Learning – Career paths and opportunities in Big Data and Hadoop – Strategies for continuous learning and professional growth