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Distributed Storage Frameworks

Distributed Storage Frameworks

Discipline: Data Engineer | Module: Module 2: Distributed Systems, Storage Engines & Big Data Architecture | Estimated Study Time: 28 Hours

Welcome to Distributed Storage Frameworks. This topic delivers foundational and advanced concepts designed for production engineering and real-world workflows.

Key Learning Objectives

  1. Apache Hadoop Ecosystem (HDFS Architecture, NameNode, DataNode, Secondary NameNode)
  2. Resource Negotiators (YARN - Yet Another Resource Negotiator, Mesos)

Detailed Curriculum Breakdown

Apache Hadoop Ecosystem (HDFS Architecture, NameNode, DataNode, Secondary NameNode)

Explore the fundamental principles, real-world patterns, and best practices for Apache Hadoop Ecosystem (HDFS Architecture, NameNode, DataNode, Secondary NameNode). Practice hands-on implementations to master these concepts.

// Code Example: Apache Hadoop Ecosystem (HDFS Architecture, NameNode, DataNode, Secondary NameNode)
// Implement verified patterns for production use
console.log("Mastering Apache Hadoop Ecosystem (HDFS Architecture, NameNode, DataNode, Secondary NameNode)");

Resource Negotiators (YARN - Yet Another Resource Negotiator, Mesos)

Explore the fundamental principles, real-world patterns, and best practices for Resource Negotiators (YARN - Yet Another Resource Negotiator, Mesos). Practice hands-on implementations to master these concepts.

// Code Example: Resource Negotiators (YARN - Yet Another Resource Negotiator, Mesos)
// Implement verified patterns for production use
console.log("Mastering Resource Negotiators (YARN - Yet Another Resource Negotiator, Mesos)");

Practical Application & Exercises

  1. Architecture Review: Evaluate how Distributed Storage Frameworks integrates with upstream and downstream systems.
  2. Implementation Challenge: Build a functional prototype demonstrating each of the subtopics.
  3. Validation & Testing: Verify performance and error handling under edge-case scenarios.

Summary Checklist