Hadoop.so Editorial Team

Apache Hadoop 3.x was a landmark release that brought significant improvements to performance, reliability, and scalability. Here's a quick tour of the most important changes.

As organizations move workloads to the cloud, one of the most common questions is: should I use HDFS or Amazon S3 as my Hadoop storage layer? Both are valid choices, but they have very different performance profiles and operational characteristics.

Apache Spark has largely replaced MapReduce for new Hadoop workloads. But MapReduce is not dead — understanding when each is appropriate will help you build more efficient data pipelines.

Welcome to hadoop.so — your comprehensive resource for learning and mastering Apache Hadoop and the broader big data ecosystem.

Hadoop 3.x introduced erasure coding, YARN Timeline Service v2, multiple NameNode support, and significant performance improvements. If you're still running Hadoop 2.x, this guide walks through a safe, rolling upgrade path — without losing data or taking extended downtime.

The s3a:// filesystem connector in Hadoop lets you use Amazon S3 as a drop-in replacement for HDFS storage. It's the foundation for cost-effective data lake architectures where compute and storage are decoupled. This guide covers configuration, performance tuning, and production best practices.

An unsecured Hadoop cluster is a ticking time bomb. Without authentication, any user on the network can read, write, or delete HDFS data. This guide covers the essential security layers for HDFS DataNodes: Kerberos authentication, data transfer encryption, block access tokens, and OS-level hardening.

Picking the wrong Java version for your Hadoop cluster is one of the most common causes of cryptic build failures, runtime exceptions, and upgrade blockers. This guide maps Hadoop releases to their supported Java versions, explains what changed between Java versions, and offers practical recommendations for 2025.

YARN (Yet Another Resource Negotiator) is Hadoop's cluster resource management layer. Understanding how YARN allocates containers — the fundamental unit of computation — is essential for getting good utilization and avoiding the frustrating "application is waiting for resources" message that plagues many clusters.