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Flume- Ingesting Data into Hadoop through Flume
Rating: 4.1 out of 5(52 ratings)
3,605 students
Created byBalaji M
Last updated 7/2019
English

What you'll learn

  • Install Flume on Hadoop
  • Configure Flume on Hadoop
  • Tune Flume to ingest Data on Hadoop
  • Troublehsoot flume related issues

Course content

3 sections11 lectures1h 11m total length
  • Where, What and Why Flume !!!11:01
  • Prerequisites and How to make best out of this course2:44

    Identify prerequisites for the course, including Linux basics and working knowledge of virtual machines, then learn to set up a cloud-based VM and use sample Flume configuration files.

  • How to Install Flume9:58

    Install and configure Flume in a Hadoop cluster, verify installation via shell, and select optimal hosts while ensuring zookeeper and hdfs dependencies.

  • Section 1 Quiz 1

Requirements

  • Basic Idea about HDFS and Hadoop

Description

Flume is a distributed, reliable, and available service for efficiently collecting, aggregating, and moving large amounts of log data. It has a simple and flexible architecture based on streaming data flows. It is robust and fault tolerant with tunable reliability mechanisms and many failover and recovery mechanisms. It uses a simple extensible data model that allows for online analytic application.

And here's my promise to you. I promise that in the next couple of hours I will teach you to build things that might take you weeks to learn on your own and we will create together a Flume Ingestion and configuration experience   It's not going to be a fully advanced and complete application set up, but it will be an amazing start to understand Flume.

Please try to do exercises and configure Flume agent and Once you are comfortable, Please submit them for my review. After couple of months, I will put in couple of more video tutorials for the exercise files.

Who this course is for:

  • Any one interested to learn about Big Data and Data ingestion standards and Loading data into Hadoop
  • Hadoop Administrators, Hadoop Support resources, Hadoop developers, Hadoop Managers