Hadoop is a powerful open-source framework designed for distributed processing of large datasets across clusters of computers. It ensures reliability by replicating data across multiple nodes, so even if some components fail, the system continues to function without interruption. Hadoop's efficiency comes from its ability to process data in parallel, significantly reducing computation time. Additionally, it is highly scalable, capable of handling petabytes of data with ease. Being community-driven, Hadoop is cost-effective and accessible to anyone who wants to use it.
**Hadoop Development Environment**
**First, install a Linux dual-boot system on Windows**
Hadoop runs natively on Linux, and while it can be configured to run on Windows using tools like Cygwin, this setup is not recommended due to complexity and performance issues. A better approach is to install a Linux virtual machine (VM) on Windows and run Hadoop within that environment. This method provides a more stable and efficient development experience, making it essential to have a Linux system installed.
**Second, install JDK on Linux and configure the Java environment**
Before setting up Hadoop, you need to install Java Development Kit (JDK) 8. You can download it from Oracle’s official website and transfer it to your Linux machine via shared folders or other methods. Once downloaded, extract the file and set the environment variables:
1. Log in as root using `su`.
2. Create a directory `/usr/java` and copy the JDK archive there.
3. Extract the JDK package.
4. Edit the `/etc/profile` file to include the `JAVA_HOME`, `CLASSPATH`, and `PATH` variables.
5. Apply the changes using `source /etc/profile` and verify the installation with `java -version`.
**Third, configure SSH passwordless login**
SSH is required for Hadoop to communicate between nodes. To enable passwordless login:
1. Install OpenSSH using `sudo apt-get install ssh`.
2. Generate an SSH key pair using `ssh-keygen`.
3. Append the public key to the `~/.ssh/authorized_keys` file.
4. Test the connection with `ssh localhost`. If no password is prompted, the configuration is successful.
**Fourth, install and run Hadoop in pseudo-distributed mode**
After installing Java and configuring SSH, proceed with Hadoop setup:
1. Modify configuration files:
- Set `JAVA_HOME` in `hadoop-env.sh`.
- Configure `core-site.xml` with the HDFS address (`hdfs://localhost:9000`).
- Set replication factor in `hdfs-site.xml` to 1 for single-node testing.
- Define the MapReduce JobTracker in `mapred-site.xml` as `localhost:9001`.
2. Format the HDFS filesystem using `./bin/hadoop namenode -format`.
3. Start all Hadoop services with `./bin/start-all.sh`.
4. Verify the installation by accessing the web interfaces at `http://localhost:50030` (MapReduce) and `http://localhost:50070` (HDFS).
**Fifth, install Eclipse on Linux**
Eclipse is a popular IDE for Hadoop development. Follow these steps:
1. Download the Linux version of Eclipse (e.g., `eclipse-java-galileo-SR1-linux-gtk.tar.gz`).
2. Extract the file and move it to `/opt`.
3. Set execution permissions and create a desktop shortcut for easy access.
4. Install the Hadoop plugin by copying the `.jar` file into the `plugins` directory.
5. Configure the Hadoop installation path in Eclipse preferences.
6. Set up the Map/Reduce perspective to interact with HDFS through the graphical interface.
With these steps, you’ll have a fully functional Hadoop development environment ready for big data applications.
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