HDFS user commands version classname and envvars

This recipe explains HDFS user commands version classname and envvars

Recipe Objective: HDFS user commands: version, CLASSNAME, and envvars

In this recipe, we work with the HDFS user commands version, classname, and envvars.

Access Snowflake Real-Time Project to Implement SCD's

Prerequisites:

Before proceeding with the recipe, make sure Single node Hadoop is installed on your local EC2 instance. If not already installed, follow the below link 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 HDFS is installed. If not installed, please find the links provided above for installations.
  • Type “&ltyour public IP&gt:7180” in the web browser and log in to Cloudera Manager, where you can check if Hadoop is installed.
  • 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.

HDFS user command: version

The command hadoop version prints the version of Hadoop installed in the system.

HDFS user command: CLASSNAME

Hadoop script can be used to invoke any class. The command hadoop CLASSNAME runs the class named CLASSNAME. Please note, the class must be part of a package.

HDFS user command: envvars

The HDFS command hadoop envvars displays the computed Hadoop environment variables. These environment variables can affect the HDFS transparency. Some of these variables include:
HADOOP_HOME
HADOOP_HDFS_HOME
HADOOP_MAPRED_HOME
HADOOP_COMMON_HOME
HADOOP_COMMON_LIB_NATIVE_DIR
HADOOP_CONF_DIR
HADOOP_SECURITY_CONF_DIR

What Users are saying..

profile image

Ray han

Tech Leader | Stanford / Yale University
linkedin profile url

I think that they are fantastic. I attended Yale and Stanford and have worked at Honeywell,Oracle, and Arthur Andersen(Accenture) in the US. I have taken Big Data and Hadoop,NoSQL, Spark, Hadoop... Read More

Relevant Projects

Explore features of Spark SQL in practice on Spark 2.0
The goal of this spark project for students is to explore the features of Spark SQL in practice on the latest version of Spark i.e. Spark 2.0.

SQL Project for Data Analysis using Oracle Database-Part 1
In this SQL Project for Data Analysis, you will learn to efficiently leverage various analytical features and functions accessible through SQL in Oracle Database

Hadoop Project to Perform Hive Analytics using SQL and Scala
In this hadoop project, learn about the features in Hive that allow us to perform analytical queries over large datasets.

Build an ETL Pipeline with Talend for Export of Data from Cloud
In this Talend ETL Project, you will build an ETL pipeline using Talend to export employee data from the Snowflake database and investor data from the Azure database, combine them using a Loop-in mechanism, filter the data for each sales representative, and export the result as a CSV file.

GCP Project-Build Pipeline using Dataflow Apache Beam Python
In this GCP Project, you will learn to build a data pipeline using Apache Beam Python on Google Dataflow.

Build Classification and Clustering Models with PySpark and MLlib
In this PySpark Project, you will learn to implement pyspark classification and clustering model examples using Spark MLlib.

Learn Efficient Multi-Source Data Processing with Talend ETL
In this Talend ETL Project , you will create a multi-source ETL Pipeline to load data from multiple sources such as MySQL Database, Azure Database, and API to Snowflake cloud using Talend Jobs.

Data Processing and Transformation in Hive using Azure VM
Hive Practice Example - Explore hive usage efficiently for data transformation and processing in this big data project using Azure VM.

Retail Analytics Project Example using Sqoop, HDFS, and Hive
This Project gives a detailed explanation of How Data Analytics can be used in the Retail Industry, using technologies like Sqoop, HDFS, and Hive.

Spark Project-Analysis and Visualization on Yelp Dataset
The goal of this Spark project is to analyze business reviews from Yelp dataset and ingest the final output of data processing in Elastic Search.Also, use the visualisation tool in the ELK stack to visualize various kinds of ad-hoc reports from the data.