📄️ Installation & Setup
This guide walks you through installing Apache Hadoop in pseudo-distributed mode on a single machine — the fastest way to learn Hadoop before deploying to a real cluster.
📄️ HDFS Deep Dive
HDFS (Hadoop Distributed File System) is the primary storage layer of Hadoop. It is designed to run on commodity hardware and reliably store very large files — from gigabytes to petabytes.
📄️ MapReduce Fundamentals
MapReduce is Hadoop's built-in programming model for processing large datasets in parallel. A job is divided into two phases: Map and Reduce.
📄️ YARN & Resource Management
YARN (Yet Another Resource Negotiator), introduced in Hadoop 2.x, decouples resource management from data processing. This allows Hadoop clusters to run MapReduce, Apache Spark, Flink, Tez, and other frameworks side-by-side.
📄️ The Hadoop Ecosystem
Hadoop's core (HDFS, MapReduce, YARN) is just the foundation. A rich ecosystem of open-source tools has grown around it.
📄️ Next Steps
You now understand the four pillars of Apache Hadoop — HDFS, MapReduce, YARN, and the Ecosystem. Here’s how to continue your journey: