Hadoop is an open-source software framework used for storing and processing large datasets in a distributed computing environment. It is designed to scale up from single servers to thousands of machines, offering robust and reliable big data analytics.
Distributed Storage: Uses Hadoop Distributed File System (HDFS) to store data across multiple nodes.Parallel Processing: Utilizes MapReduce to process data simultaneously on multiple nodes.Scalability: Easily scales to accommodate growing data volumes.Fault Tolerance: Automatically detects and handles hardware failures.
Hadoop works by dividing large datasets into smaller chunks and distributing them across various nodes in a cluster. HDFS manages the storage, while MapReduce handles the processing by breaking down tasks and executing them in parallel. This ensures efficient data processing even with large volumes.
Data Locality: Store data close to the computation nodes to minimize data transfer times.Cluster Configuration: Optimize the cluster configuration based on workload requirements.Regular Monitoring: Continuously monitor the cluster to identify and resolve performance issues.Security Measures: Implement robust security practices to protect sensitive data.
Hadoop is primarily designed for batch processing. For real-time processing, frameworks like Apache Spark or Storm are recommended.
Industries such as finance, healthcare, retail, and telecommunications use Hadoop for big data analytics and insights.
