YARN command proxyserver and YARN command resourcemanager

This recipe explains YARN command proxyserver and YARN command resourcemanager

Recipe Objective: YARN command: proxyserver & YARN command: resourcemanager

YARN (Yet Another Resource Negotiator) effectively distributed the work of the Job Tracker to the Resource Manager and the Application Masters and focused only on resource management. This helped overcome the problem of the Job Tracker being a single point of failure in Hadoop 1.x. Additionally, YARN also helped improve the system's scalability as the number of possible Maps and Reduce slots depended directly on the Job Tracker. YARN also allowed other data processing frameworks, such as Tez and Spark to process data. After Hadoop v2.4, a standby Resource Manager was added with automatic failover support, making YARN fault-tolerant.

In this recipe, we work with the YARN commands: proxyserver and resourcemanager.

Prerequisites:

Before proceeding with the recipe, make sure Single node Hadoop is installed on your local EC2 instance and YARN is set up. If not, follow the below links to do the same.

Steps to set up an environment:

  • In the AWS, create an EC2 instance and log in to Cloudera Manager with your public IP mentioned in the EC2 instance. Login to putty/terminal and check if Hadoop is up and running. Type "&ltyour public IP&gt:7180" in the web browser and log in to Cloudera Manager, where you can check if HDFS and YARN services are active in your CDH cluster.
  • If they are not visible in the Cloudera cluster, you may add them by clicking on the "Add Services" in the cluster to add the required services in your local instance.

YARN command: proxyserver

The command yarn proxyserver starts the web proxy server. Sample output for the same is given below.

bigdata_1

YARN command: resourcemanager

The command yarn resourcemanager [options] is to start the resource manager. This command takes the following options.

-format-state-store: Formats the RMStateStore. This will clear the RMStateStore and is useful if past applications are no longer needed. This should be run only when the ResourceManager is not running.
-remove-application-from-state-store&ltapp ID&gt: Removes the application from RMStateStore. This should be run only when the ResourceManager is not running.
-format-conf-store: Formats the YarnConfigurationStore. This will clear the persistent scheduler configuration under YarnConfigurationStore. This should be run only when the ResourceManager is not running.

Download Materials

What Users are saying..

profile image

Ameeruddin Mohammed

ETL (Abintio) developer at IBM
linkedin profile url

I come from a background in Marketing and Analytics and when I developed an interest in Machine Learning algorithms, I did multiple in-class courses from reputed institutions though I got good... Read More

Relevant Projects

AWS Project - Build an ETL Data Pipeline on AWS EMR Cluster
Build a fully working scalable, reliable and secure AWS EMR complex data pipeline from scratch that provides support for all data stages from data collection to data analysis and visualization.

Hive Mini Project to Build a Data Warehouse for e-Commerce
In this hive project, you will design a data warehouse for e-commerce application to perform Hive analytics on Sales and Customer Demographics data using big data tools such as Sqoop, Spark, and HDFS.

AWS CDK Project for Building Real-Time IoT Infrastructure
AWS CDK Project for Beginners to Build Real-Time IoT Infrastructure and migrate and analyze data to

Talend Real-Time Project for ETL Process Automation
In this Talend Project, you will learn how to build an ETL pipeline in Talend Open Studio to automate the process of File Loading and Processing.

How to deal with slowly changing dimensions using snowflake?
Implement Slowly Changing Dimensions using Snowflake Method - Build Type 1 and Type 2 SCD in Snowflake using the Stream and Task Functionalities

Build a Real-Time Spark Streaming Pipeline on AWS using Scala
In this Spark Streaming project, you will build a real-time spark streaming pipeline on AWS using Scala and Python.

AWS Snowflake Data Pipeline Example using Kinesis and Airflow
Learn to build a Snowflake Data Pipeline starting from the EC2 logs to storage in Snowflake and S3 post-transformation and processing through Airflow DAGs

Streaming Data Pipeline using Spark, HBase and Phoenix
Build a Real-Time Streaming Data Pipeline for an application that monitors oil wells using Apache Spark, HBase and Apache Phoenix .

Learn How to Implement SCD in Talend to Capture Data Changes
In this Talend Project, you will build an ETL pipeline in Talend to capture data changes using SCD techniques.

Airline Dataset Analysis using PySpark GraphFrames in Python
In this PySpark project, you will perform airline dataset analysis using graphframes in Python to find structural motifs, the shortest route between cities, and rank airports with PageRank.