Hadoop Git

The Apache Hadoop project’s source code and development activities are managed through Git repositories hosted on Apache’s Git infrastructure. Git is a distributed version control system that allows developers to collaborate on code, track changes, and manage the project’s source code efficiently. Here’s an overview of Hadoop’s Git repositories and how they are used:

1. Apache Hadoop Git Repositories:

   • The Apache Hadoop project maintains several Git repositories for different components and subprojects. Some of the primary repositories include:
     
     • hadoop-common: This repository contains code related to the common utilities and libraries used across various Hadoop components.
     • hadoop-hdfs: The Hadoop Distributed File System (HDFS) repository contains the code for Hadoop’s distributed storage system.
     • hadoop-mapreduce: This repository contains the code for Hadoop’s MapReduce framework.
     • hadoop-yarn: The Yet Another Resource Negotiator (YARN) repository contains the code for Hadoop’s cluster resource management framework.
     • hadoop-tools: Various Hadoop-related tools and utilities are developed and maintained in this repository.

2. Git Branches:

   • Within each repository, development work is organized into branches. The main branches often include master for the latest stable release and trunk or main for the ongoing development version.
   • Feature branches or topic branches are created for specific development tasks, bug fixes, or new features. These branches are later merged back into the main branches.

3. Contributions and Commits:

   • Developers contribute to the project by creating branches, making code changes, and committing their changes to the Git repositories.
   • Commit messages often follow a specific format that includes a brief description of the change, the JIRA issue (if applicable), and additional details about the commit.

4. Code Review:

   • Code contributions to Hadoop are subject to code review by other project members. The review process ensures code quality, adherence to coding standards, and compatibility with the project’s goals.
   • Reviews are typically conducted on the project’s mailing lists and issue tracker, with discussions about proposed changes and improvements.

5. Integration and Testing:

   • Continuous integration (CI) and automated testing are crucial aspects of Hadoop’s development process. Jenkins and other CI tools are used to automatically build, test, and validate code changes.
   • A comprehensive suite of unit tests and integration tests help maintain code quality and reliability.

6. Release Process:

   • When a new version of Hadoop is ready, a release manager coordinates the release process, which involves creating release branches, performing final testing, and publishing official releases.
   • Released versions are tagged in the Git repositories for reference.

7. Community Collaboration:

   • Apache Hadoop has an active and diverse developer community, and Git plays a crucial role in enabling collaboration among contributors from different organizations and locations.