Course: Working with HDFS training

$129.00
$156.09 incl. vat

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duration: 6 hours |

Language: English (US) |

access duration: 180 days |

Details

HDFS, or while Hadoop, is an open-source software framework that allows applications to process data in a distributed environment. The bottom line is that large data sets are divided into smaller blocks and spread over several computers so that they can be processed in parallel.

In this training, you will explore the concepts of analyzing large data sets. You discover how HDFS makes this process very efficient. Through this training, you will recognize the need to process huge data sets on a large scale.

This training examines how you can offer a Hadoop cluster in the cloud using the Dataproc service from the Google Cloud Platform. You will also explore apps for Hadoop, configure HDFS and learn about working with HDFS shells. You also learn how to copy files from your local file system to HDFS using a put command.

Result

After following this training you will know how to work with HDFS. You have explored the concepts of analyzing large data sets and you have discovered how HDFS makes this process very efficient.

Prerequisites

No specific knowledge is required for this training.

Target audience

Software Developer, Database Administrators

Content

Working with HDFS

6 hours

Hadoop HDFS: Introduction

HDFS is the file system which enables the parallel processing of big data in distributed cluster. Explore the concepts of analyzing large datasets and explore how Hadoop and HDFS make this process very efficient.

Hadoop HDFS: Introduction to the Shell

Discover how to set up a Hadoop Cluster on the cloud and explore the bundled web apps - the YARN Cluster Manager app and the HDFS NameNode UI. Then use the hadoop fs and hdfs dfs shells to browse the Hadoop file system.

Hadoop HDFS: Working with Files

Explore the Hadoop file system using the HDFS dfs shell and perform basic file and directory-level operations. Transfer files between a local file system and HDFS and explore ways to create and delete files on HDFS.

Hadoop HDFS: File Permissions

HDFS is the file system which enables the parallel processing of big data in distributed cluster. When managing a data warehouse, not all users should be given free reign over all the datasets. Explore how file permissions can be viewed and configured in HDFS. The NameNode UI is used to monitor and explore HDFS.

Course options

We offer several optional training products to enhance your learning experience. If you are planning to use our training course in preperation for an official exam then whe highly recommend using these optional training products to ensure an optimal learning experience. Sometimes there is only a practice exam or/and practice lab available.

Optional practice exam (trial exam)

To supplement this training course you may add a special practice exam. This practice exam comprises a number of trial exams which are very similar to the real exam, both in terms of form and content. This is the ultimate way to test whether you are ready for the exam. 

Optional practice lab

To supplement this training course you may add a special practice lab. You perform the tasks on real hardware and/or software applicable to your Lab. The labs are fully hosted in our cloud. The only thing you need to use our practice labs is a web browser. In the LiveLab environment you will find exercises which you can start immediatelyThe lab enviromentconsist of complete networks containing for example, clients, servers,etc. This is the ultimate way to gain extensive hands-on experience. 

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