With the increasing scale of Internet data, the file storage system has higher requirements, requiring more capacity, better performance and more secure file storage system, like the traditional distributed file system,HDFS Distributed File System It is also connected with the node through the computer network, but it also has advantages over the traditional distributed file system.
1. support for oversized files
The hdfs Distributed File system has a large data set that can store terabytes or petabytes of oversized data files that provide high data transfer bandwidth and throughput, with the appropriateHDFs Open up some POSIX must-have interfaces that allow streaming access to the file system's data.
2. High Fault- tolerant Performance
HDFS is for hundreds of server clusters, each server is stored in the file system part of the data, in the cluster environment, hardware failure is a common problem, which means that there is always a part of the hardware for a variety of reasons to work, so, error detection and fast, automatic recovery is HDFs has the most core architectural goals, soHDFs has a high degree of fault tolerance.
3. High data throughput
HDFs uses a "one-time write, multiple read" This simple data consistency model, in HDFS , once a file has been created, written, closed, generally do not need to modify, such a simple consistency model, to improve throughput.
4. Streaming data access
HDFS has a large scale of data processing, applications need to access a large amount of information at a time, and these applications are generally batch processing, rather than user interactive processing, the application can be streamed in the form of access to the dataset.
Hadoophas rapidly grown into the first choice for Big data analytics solutions for unstructured data,
HDFs Distributed File Systemis one of the core components of Hadoop, ensuring the reliable storage of big data, and the use of MapReduce, can be structured and complex big data fast and reliable analysis, so as to make better decisions for enterprises, promote revenue growth, improve services, reduce costs to provide a strong support!
HDFs of common commands for Hadoop