As the scale of Internet data continues to increase, higher requirements are placed on file storage systems, requiring larger capacity, better performance and higher security file storage systems. Like traditional distributed file systems, HDFS Distributed file systems are also connected to nodes through computer networks, but they also have advantages over traditional distributed file systems.
1. Support large files
The HDFS distributed file system has a large data set, can store large data files of TB or PB level, and can provide relatively high data transmission bandwidth and data access throughput. Correspondingly, HDFS opens some POSIX necessary interfaces to allow Streaming access to file system data.
2. High fault tolerance
HDFS is oriented to hundreds or thousands of server clusters. Each server stores part of the data of the file system. In a cluster environment, hardware failure is a common problem, which means that there is always a part of the hardware due to various reasons. Therefore, error detection and fast, automatic recovery are the core architectural goals of HDFS . Therefore, HDFS has a high degree of fault tolerance.
3. High data throughput
HDFS adopts a simple data consistency model of "write once, read many times". In HDFS , once a file is created, written, and closed, it generally does not need to be modified. This simple consistency model, which is beneficial to improve throughput.
4. Streaming data access
The data processing scale of HDFS is relatively large, and applications need to access a large amount of data at a time. At the same time, these applications are generally batch processing, rather than user interactive processing, and applications can access data sets in the form of streams.
Hadoop has rapidly grown into the preferred big data analysis solution for unstructured data. HDFS distributed file system is one of the core components of Hadoop , which ensures reliable storage of big data . Fast and reliable analysis of complex and complex big data, so as to provide strong support for enterprises to make better decisions, promote revenue growth, improve services, and reduce costs!