HDFS Features and Goals
The Hadoop Distributed File System (HDFS) is a distributed file system. It is a core part of Hadoop which is used for data storage. It is designed to run on commodity hardware.
Unlike other distributed file system, HDFS is highly fault-tolerant and can be deployed on low-cost hardware. It can easily handle the application that contains large data sets.
Let’s see some of the important features and goals of HDFS.
Features of HDFS
- Highly Scalable - HDFS is highly scalable as it can scale hundreds of nodes in a single cluster.
- Replication - Due to some unfavorable conditions, the node containing the data may be loss. So, to overcome such problems, HDFS always maintains the copy of data on a different machine.
- Fault tolerance - In HDFS, the fault tolerance signifies the robustness of the system in the event of failure. The HDFS is highly fault-tolerant that if any machine fails, the other machine containing the copy of that data automatically become active.
- Distributed data storage - This is one of the most important features of HDFS that makes Hadoop very powerful. Here, data is divided into multiple blocks and stored into nodes.
- Portable - HDFS is designed in such a way that it can easily portable from platform to another.
Goals of HDFS
- Handling the hardware failure - The HDFS contains multiple server machines. Anyhow, if any machine fails, the HDFS goal is to recover it quickly.
- Streaming data access - The HDFS applications usually run on the general-purpose file system. This application requires streaming access to their data sets.
- Coherence Model - The application that runs on HDFS require to follow the write-once-ready-many approach. So, a file once created need not to be changed. However, it can be appended and truncate.