Q18Big Data Analytics

The Apache Hadoop architecture is designed to handle massive volumes of data across clusters of commodity hardware. It consists of four main modules: 1. Hadoop Common: The core libraries and utilities that support the other modules. 2. HDFS (Hadoop Distributed File System): A Java-based file system that provides scalable and reliable data storage. It operates on a Master/Slave architecture, with a single NameNode managing the file system metadata and multiple DataNodes storing the actual data blocks. HDFS replicates blocks to prevent data loss. 3. MapReduce: A software framework for easily writing applications that process vast amounts of data in parallel on large clusters in a fault-tolerant manner. 4. YARN (Yet Another Resource Negotiator): The framework responsible for cluster resource management and job scheduling. It decouples the resource management capabilities from the processing model, allowing multiple processing engines (like Spark and Tez) to run alongside MapReduce.