Hadoop Distributed File System (HDFS) is a distributed file system designed to store and manage large data sets across multiple commodity hardware servers. It is a key component of the Hadoop ecosystem and provides fault-tolerant storage for big data applications.
Some of the key characteristics of HDFS are:
Scalability: HDFS is designed to scale to petabytes of data and can easily handle a large number of nodes.
Fault-tolerance: HDFS is designed to be fault-tolerant and can handle node failures without any data loss.
High throughput: HDFS provides high throughput for read and write operations by parallelizing data across multiple nodes.
Low cost: HDFS runs on commodity hardware, which makes it a cost-effective solution for big data storage.
Data locality: HDFS stores data in a distributed manner across multiple nodes, ensuring that data is stored near the processing nodes, which improves performance.
The following are the main operations that can be performed on HDFS:
Write operation: Data can be written to HDFS using the HDFS API or Hadoop command line tools such as Hadoop fs.
Read operation: Data can be read from HDFS using the HDFS API or Hadoop command line tools.
Replication: HDFS provides replication of data across multiple nodes to ensure fault-tolerance and high availability.
File system metadata operations: HDFS stores metadata such as file names, permissions, and directory structures, which can be accessed using HDFS API or Hadoop command line tools.
Administration and monitoring: Hadoop provides a number of command line tools to monitor and manage HDFS, including hdfs dfsadmin and hdfs fsck. These tools can be used to manage the HDFS namespace, monitor the health of the cluster, and identify and fix issues.
In summary, HDFS is a distributed file system that provides fault-tolerant storage for large data sets. It is designed to be scalable, fault-tolerant, and cost-effective, and provides high throughput and data locality for improved performance. HDFS supports a number of operations for reading, writing, replication, and managing file system metadata, as well as administration and monitoring tools for managing the cluster.
