Hadoop

Hadoop

1. Hadoop Architecture

   • Includes
     • HDFS
       • Distributed Storage
       • Fault Tolerance
       • High Scalability
     • MapReduce
       • Distributed Data Processing
       • Parallel Computation
       • Batch Processing
     • YARN
       • Resouces Management
       • Job Scheduling
       • Cluster Coordination

2. Hadoop Evolution

   • inspired by
     • Google File System (GFS)
       • Distributed storage architecture
       • Large-scale data management
   • Hadoop Timeline
     • 2003: Google publishes GFS paper
     • 2004: Google publishes the MapReduce paper
     • 2005: Hadoop project begins under Nutch
     • 2006: Hadoop becomes an Apache project
     • 2008: Hadoop is widelyadopted for Big Data processing
     • Present: Hadoop integrates with Spark, Cloud Computing, and Machine Learning technologies

3. Advantages of Hadoop

   • Scalability
   • Fault Tolerance
   • Cost Effectiveness
   • Distributed Processing

4. Hadoop and ML

   • Applications
     • Predictive Analytics
     • Classification
     • Clustering
     • Recommendation systems
   • Benefits
     • Large-scale model training
     • Data preparation
     • Feature engineering

5. Hadoop and Cloud Computing

   • Examples
     • Cloud Storage
     • Virtual machine
     • Distributed Services
   • Benefits
     • Elastic scalability
     • High availability
     • Reduced infraestructure costs

6. Big Data Relationship

   • Enables
     • Data Collection
     • Data Storage
     • Data Processing
     • Data Analysis