Help Center/ MapReduce Service/ Developer Guide (Normal_3.x)/ HDFS Development Guide (Normal Mode)/ HDFS Application Development Overview
Updated on 2024-10-23 GMT+08:00
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HDFS Application Development Overview

Introduction to HDFS

Hadoop distribute file system (HDFS) is a distributed file system with high fault tolerance. HDFS supports data access with high throughput and applies to processing of large data sets.

HDFS applies to the following application scenarios:

  • Massive data processing (higher than the TB or PB level).
  • Scenarios that require high throughput.
  • Scenarios that require high reliability.
  • Scenarios that require good scalability.

Introduction to HDFS Interface

HDFS can be developed by using Java language. For details of API reference, see HDFS Java APIs.

HDFS Basic Concepts

  • Colocation

    Colocation is used to store associated data or the data to be associated on the same storage node. The HDFS Colocation stores files to be associated on a same data node so that data can be obtained from the same data node during associated operations. This greatly reduces network bandwidth consumption.

  • Client

    The HDFS can be accessed from the Java application programming interface (API), C API, Shell, HTTP REST API and web user interface (WebUI).

    For details, see Common API Introduction and HDFS Shell Command Introduce.

    • JAVA API

      Provides an application interface for the HDFS. This guide describes how to use the Java API to develop HDFS applications.

    • C API

      Provides an application interface for the HDFS. This guide describes how to use the C API to develop HDFS applications.

    • Shell

      Provides shell commands to perform operations on the HDFS.

    • HTTP REST API

      Additional interfaces except Shell, Java API and C API. You can use the interfaces to monitor HDFS status.

    • WEB UI

      Provides a visualized management web page.