How to scale Hadoop YARN cluster by adding or removing nodes

Introduction

Hadoop YARN is a powerful framework for distributed data processing, but as your data and processing needs grow, you may need to scale your Hadoop cluster accordingly. This tutorial will guide you through the process of scaling your Hadoop YARN cluster by adding or removing nodes, ensuring your infrastructure can handle the changing demands of your data-driven applications.

Skills Graph

%%%%{init: {'theme':'neutral'}}%%%% flowchart RL hadoop(("`Hadoop`")) -.-> hadoop/HadoopYARNGroup(["`Hadoop YARN`"]) hadoop/HadoopYARNGroup -.-> hadoop/yarn_setup("`Hadoop YARN Basic Setup`") hadoop/HadoopYARNGroup -.-> hadoop/apply_scheduler("`Applying Scheduler`") hadoop/HadoopYARNGroup -.-> hadoop/yarn_app("`Yarn Commands application`") hadoop/HadoopYARNGroup -.-> hadoop/yarn_container("`Yarn Commands container`") hadoop/HadoopYARNGroup -.-> hadoop/yarn_node("`Yarn Commands node`") hadoop/HadoopYARNGroup -.-> hadoop/resource_manager("`Resource Manager`") hadoop/HadoopYARNGroup -.-> hadoop/node_manager("`Node Manager`") subgraph Lab Skills hadoop/yarn_setup -.-> lab-417687{{"`How to scale Hadoop YARN cluster by adding or removing nodes`"}} hadoop/apply_scheduler -.-> lab-417687{{"`How to scale Hadoop YARN cluster by adding or removing nodes`"}} hadoop/yarn_app -.-> lab-417687{{"`How to scale Hadoop YARN cluster by adding or removing nodes`"}} hadoop/yarn_container -.-> lab-417687{{"`How to scale Hadoop YARN cluster by adding or removing nodes`"}} hadoop/yarn_node -.-> lab-417687{{"`How to scale Hadoop YARN cluster by adding or removing nodes`"}} hadoop/resource_manager -.-> lab-417687{{"`How to scale Hadoop YARN cluster by adding or removing nodes`"}} hadoop/node_manager -.-> lab-417687{{"`How to scale Hadoop YARN cluster by adding or removing nodes`"}} end

Introduction to Hadoop YARN

Hadoop YARN (Yet Another Resource Negotiator) is a key component of the Hadoop ecosystem, responsible for resource management and job scheduling. It was introduced in Hadoop 2.0 to address the limitations of the previous resource management system, the Hadoop MapReduce v1 (also known as MRv1 or Classic MapReduce).

YARN introduces a two-layer architecture, separating the resource management and job scheduling/monitoring functions of the previous Hadoop MapReduce framework. This separation of concerns allows YARN to support a wide range of distributed processing frameworks, including batch processing, interactive processing, real-time processing, and machine learning.

The main components of Hadoop YARN are:

Resource Manager (RM): The central authority that allocates resources to various applications running in the Hadoop cluster.
Node Manager (NM): The per-node agent that is responsible for launching and monitoring containers, as well as reporting resource usage and status to the Resource Manager.
Application Master (AM): The per-application master responsible for negotiating resources from the Resource Manager and working with the Node Managers to execute and monitor the application's tasks.

YARN provides several key benefits over the previous Hadoop MapReduce framework:

Scalability: YARN can support a larger number of concurrent applications and tasks, making it more scalable.
Flexibility: YARN can support a wide range of distributed processing frameworks, not just MapReduce.
Efficiency: YARN can better utilize cluster resources by allowing multiple applications to run concurrently.

To demonstrate the basic setup of a Hadoop YARN cluster, let's consider the following example using Ubuntu 22.04:

## Install Hadoop
sudo apt-get update
sudo apt-get install -y openjdk-8-jdk
wget https://downloads.apache.org/hadoop/common/hadoop-3.3.4/hadoop-3.3.4.tar.gz
tar -xzf hadoop-3.3.4.tar.gz
cd hadoop-3.3.4

## Configure Hadoop environment
export HADOOP_HOME=$(pwd)
export PATH=$PATH:$HADOOP_HOME/bin:$HADOOP_HOME/sbin

## Start the Hadoop YARN cluster
hdfs namenode -format
start-dfs.sh
start-yarn.sh

This setup will start a basic Hadoop YARN cluster with a single node. You can then use the yarn command to interact with the cluster and submit applications for execution.

graph TD A[Client] --> B[Resource Manager] B --> C[Node Manager] C --> D[Container] D --> E[Application Master] E --> F[Task Tracker]

Scaling Hadoop YARN Cluster by Adding Nodes

Scaling a Hadoop YARN cluster by adding nodes is a common operation to increase the cluster's processing capacity and handle growing data and workload demands. Here's how you can scale your Hadoop YARN cluster by adding new nodes:

Prepare the New Nodes

Install the required software on the new nodes:

sudo apt-get update
sudo apt-get install -y openjdk-8-jdk
wget https://downloads.apache.org/hadoop/common/hadoop-3.3.4/hadoop-3.3.4.tar.gz
tar -xzf hadoop-3.3.4.tar.gz

Configure the Hadoop environment on the new nodes:

export HADOOP_HOME=$(pwd)/hadoop-3.3.4
export PATH=$PATH:$HADOOP_HOME/bin:$HADOOP_HOME/sbin

Update the Hadoop configuration files (e.g., core-site.xml, hdfs-site.xml, yarn-site.xml) on the new nodes to match the existing cluster configuration.

Add the New Nodes to the Cluster

Update the slaves file in the Hadoop configuration directory to include the hostnames or IP addresses of the new nodes.
Copy the updated Hadoop configuration to all the nodes in the cluster, including the new nodes:
```
scp -r $HADOOP_HOME/etc/hadoop/* user@newnode:$HADOOP_HOME/etc/hadoop/
```

Start the new Node Managers on the new nodes:

ssh user@newnode "$HADOOP_HOME/sbin/yarn-daemon.sh start nodemanager"

Verify that the new nodes have been added to the Hadoop YARN cluster:
```
yarn node -list
```

Monitor the Cluster Expansion

After adding the new nodes, you can monitor the cluster expansion and resource utilization using the following commands:

## Check the cluster's overall status
yarn cluster --status

## View the list of active nodes in the cluster
yarn node -list

## Monitor the resource utilization of the cluster
yarn top

By following these steps, you can easily scale your Hadoop YARN cluster by adding new nodes to increase the overall processing capacity and handle growing data and workload demands.

Scaling Hadoop YARN Cluster by Removing Nodes

Scaling a Hadoop YARN cluster by removing nodes is a common operation when you need to downsize the cluster or decommission underutilized or faulty nodes. Here's how you can scale your Hadoop YARN cluster by removing nodes:

Identify Nodes to Remove

Before removing nodes from the cluster, you should identify the nodes that are suitable for decommissioning. You can use the following commands to gather information about the cluster's nodes and their resource utilization:

## List all the nodes in the cluster
yarn node -list

## Check the resource utilization of each node
yarn top

Based on the information gathered, you can decide which nodes to remove from the cluster.

Decommission the Nodes

To safely remove nodes from the Hadoop YARN cluster, you need to decommission them. This process ensures that any running applications or containers on the nodes are gracefully terminated and the resources are released.

Update the slaves file in the Hadoop configuration directory to remove the hostnames or IP addresses of the nodes you want to decommission.
Copy the updated Hadoop configuration to all the nodes in the cluster:
```
scp -r $HADOOP_HOME/etc/hadoop/* user@node:$HADOOP_HOME/etc/hadoop/
```
Initiate the decommissioning process on the Resource Manager:
```
yarn rmadmin -refreshNodes
```
Monitor the decommissioning process using the following command:
```
yarn node -list
```
Wait until the decommissioned nodes are no longer listed as part of the cluster.

Remove the Decommissioned Nodes

After the decommissioning process is complete, you can safely remove the decommissioned nodes from the cluster. This may involve physical removal of the nodes or simply powering them down, depending on your infrastructure setup.

By following these steps, you can scale your Hadoop YARN cluster by removing nodes in a controlled and safe manner, ensuring that the cluster's overall performance and stability are maintained.

Summary

In this Hadoop tutorial, you have learned how to scale your Hadoop YARN cluster by adding or removing nodes. By understanding the steps involved in expanding or contracting your Hadoop infrastructure, you can optimize your Hadoop cluster for performance and cost-efficiency, ensuring your data processing needs are met as your business requirements evolve.