Hadoop is a powerful open-source framework designed for distributed processing of large datasets across clusters of computers. It provides a reliable, efficient, and scalable way to handle big data. Hadoop ensures reliability by maintaining multiple copies of data, which allows it to redistribute tasks in case of node failures. Its efficiency comes from parallel processing, enabling faster computation. Additionally, Hadoop is highly scalable, capable of handling petabytes of data. Being community-driven, it is cost-effective and accessible to anyone.
Setting up the Hadoop development environment involves several steps. First, it's recommended to install a Linux dual-boot system on Windows or run a Linux virtual machine, as Hadoop is primarily developed for Linux environments. This setup ensures better compatibility and performance compared to running Hadoop directly on Windows.
Next, installing the Java Development Kit (JDK) is essential. After downloading JDK 8, you can transfer it to the Linux system using shared folders. Once installed, configure the environment variables by editing the `/etc/profile` file, setting `JAVA_HOME`, `CLASSPATH`, and `PATH`. Restarting the system or sourcing the profile file will apply the changes. Verifying the installation with `java -version` confirms that Java is correctly set up.
Configuring SSH for password-free login is crucial for seamless communication between nodes. Install OpenSSH, generate SSH keys, and add the public key to the `authorized_keys` file. Testing the connection with `ssh localhost` ensures that passwordless access works properly.
To install and run Hadoop in pseudo-distributed mode, modify configuration files such as `hadoop-env.sh`, `core-site.xml`, `hdfs-site.xml`, and `mapred-site.xml`. Set the HDFS address, replication factor, and MapReduce tracker. Formatting the Hadoop filesystem with `hadoop namenode -format` and starting all services with `start-all.sh` completes the setup. You can then verify the installation by accessing web interfaces like `http://localhost:50070` for HDFS and `http://localhost:50030` for MapReduce.
Finally, installing Eclipse on Linux and configuring the Hadoop plugin enhances the development experience. Download and extract Eclipse, move it to the `/opt` directory, and create a desktop shortcut. Install the Hadoop plugin by copying the `.jar` file into the plugins folder. Configure the Hadoop installation path and set up the Map/Reduce perspective to interact with HDFS through the Eclipse interface. This integration simplifies file management and job execution within the Hadoop ecosystem.
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