HDFS stands for Hadoop Distributed File System. It’s a distributed file system designed to run on commodity hardware. It is a core component of the Apache Hadoop project, an open-source framework for distributed storage and processing of large datasets.
HDFS is highly fault-tolerant and is designed to be deployed on low-cost hardware. It provides high-throughput access to application data and is suitable for applications with large datasets. HDFS works by breaking large files into smaller blocks, typically 128 MB or 256 MB in size, and distributing them across multiple nodes in a cluster. This allows for parallel processing of data across the cluster, which can significantly improve performance.
Some key features of HDFS include:
- Fault tolerance: HDFS replicates data across multiple nodes in the cluster, ensuring that data remains available even if some nodes fail.
- Scalability: HDFS is designed to scale horizontally by adding more nodes to the cluster as needed, allowing it to handle petabytes of data or more.
- High throughput: HDFS is optimized for streaming access to large files, making it well-suited for batch processing and analytics workloads.
- Data locality: HDFS is aware of the underlying hardware topology and tries to place computation close to the data it operates on, reducing network traffic and improving performance.
