Hadoop Getting Started

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             Hadoop Getting Started

 Here’s a step-by-step guide to help you get started with Hadoop:

Step 1: Prerequisites

Before you begin, ensure that you have the following prerequisites in place:

  • A Linux-based system (such as Ubuntu or CentOS) or access to a virtual machine with Linux.
  • Java Development Kit (JDK) installed (preferably Oracle JDK 8 or later).
  • A user account with administrative privileges (for setting up Hadoop).

Step 2: Download and Install Hadoop

  1. Visit the Apache Hadoop official website: https://hadoop.apache.org.
  2. Navigate to the “Downloads” section and choose the latest stable release.
  3. Download the Hadoop distribution (e.g., “hadoop-x.y.z.tar.gz”).
  4. Extract the downloaded archive to a directory of your choice. You can use the following command:
    shell
    tar -xzvf hadoop-x.y.z.tar.gz

Step 3: Configure Hadoop

  1. Navigate to the Hadoop installation directory:

    shell
    cd hadoop-x.y.z
  2. Edit the Hadoop configuration files located in the etc/hadoop directory. Key configuration files include:

    • core-site.xml: Hadoop core configuration.
    • hdfs-site.xml: Hadoop Distributed File System (HDFS) configuration.
    • yarn-site.xml: YARN (Yet Another Resource Negotiator) configuration.
  3. Set Hadoop environment variables by adding the following lines to your shell profile (e.g., .bashrc or .zshrc):

    shell
    export HADOOP_HOME=/path/to/hadoop-x.y.z
    export PATH=$PATH:$HADOOP_HOME/bin
  4. Save the changes and reload your shell profile:

    shell
    source ~/.bashrc

Step 4: Start Hadoop

  1. Format the HDFS filesystem (do this only once after installing Hadoop):

    shell
    hdfs namenode -format
  2. Start the HDFS service:

    shell
    start-dfs.sh
  3. Start the YARN service (Resource Manager and Node Manager):

    shell
    start-yarn.sh

Step 5: Verify Hadoop Installation

Step 6: Run a Hadoop Example

To test your Hadoop installation, you can run a simple MapReduce example. Hadoop comes with several built-in examples.

  1. Navigate to the Hadoop examples directory:

    shell
    cd $HADOOP_HOME
    cd share/hadoop/mapreduce
  2. Run a MapReduce example, such as the word count example:

    shell
    hadoop jar hadoop-mapreduce-examples-x.y.z.jar wordcount input output

Step 7: Explore Further

Now that you have Hadoop up and running, you can explore more advanced features, such as:

  • Writing your MapReduce programs.
  • Working with Hadoop’s distributed file system (HDFS).
  • Configuring resource management and job scheduling with YARN.
  • Integrating Hadoop with other big data tools like Hive, Pig, or Spark.

Hadoop Training Demo Day 1 Video:

 
You can find more information about Hadoop Training in this Hadoop Docs Link

 

Conclusion:

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