Apache Ranger : Fine-Grained Access Control (Udemy.com)
Integrate Apache Ranger with Hive, HDFS, Presto, Tagsync from Apache Atlas etc
Created by: Ganesh Dhareshwar
Last updated August 2024
What you will learn
- Apache Ranger Components & Architecture
- Complete Ranger Hive Integration with real usecases
- Understanding end-to-end Ranger Hive, HDFS, Presto Plugin
- Ranger Tag-sync from Apache Atlas
How it compares
Against the other 1,182 rated Udemy courses in IT & Software on CourseDuck:
- Rating4.3 out of 5higher than 20% of them
- Reviews74#1,050 of 1,183 by number of reviews
- Length1.9 hoursshorter than 85% of them
- Last updatedAugust 2024earlier than 62% of them
Course Description
What do you Learn From this Course ?
In this course, we study end-to-end Apache Ranger authorisation policies and integration with Hadoop components like Hive, HDFS, Apache Atlas, Presto etc.
First we learn Ranger Components and Architecture.
Next, we install Apache Ranger 2.1.0 which is the latest stable version. Ranger installation looks pretty straightforward.
However, ranger requires Solr and Mysql infrastructure. Ranger supports Mysql version 5.6 or 5.7. It won't support beyond these versions. These constraints complicates ranger installation. I spent many days while installing ranger. I consolidated all the steps into a single shell script. Users can download it and run it as it is without any issues. After that, we navigate to apache ranger user interface and explore salient features.
In the 3rd section, we achieve Ranger Hive integration. At first, we acquire hive cluster and install ranger hive plugin.
We load sample data into hive. We define policies on apache ranger for different users and validate the policies by querying on hive. We also examine Masking and Row Level Filters.
In the 4th section, we dig deeper into Ranger HDFS integration. At first, we acquire hive cluster and install HDFS ranger plugin.
We dig deeper into the hive Managed Tables and load sample data into HDFS.
Lastly, we define HDFS policies and verify it by querying on hive tables.
Instructor Details
- 4.3 Rating
74 Reviews
Ganesh Dhareshwar
8 years working experience from many fast growing companies like Myntra Designs Pvt. Ltd, Swiggy, Lendingkart Technologies Private Limited, Sprinklr. Currently working as Senior Data Engineer at Delivery Hero, Berlin. Highly dedicated, self-motivated and confident person. Hands-on experience in developing large scale web application, writing Spark Jobs, developing Api’s etc.
Coding is my passion and I love exploring new programming methodologies.
I am a self motivated, highly enthusiastic and dedicated person. I keep myself occupied with learning and practising it. I own a blog and publish wonderful articles on this. I worked on multiple tech stacks. I love to conduct experiments by comparing each other and publish the results on my blog.
I excel in Apache Airflow, Spark, Hadoop, Hive, Presto, Kafka, Spark Streaming etc Big data technologies. I worked on Mysql, MongoDB, Memsql, PostgreSQL, Redis databases.
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Reviews
By Ulises Rangel on 9/4/2026
It was a good basic course
By Sujeet Panda on 1/5/2025
Short,crisp course. Excellent.
By Anonymized User on 1/17/2024
One of the best hands-on experiences I've ever had.
By Max Kieselbach on 1/5/2024
Video spielen nicht ab Kurse hab schon einmal gemacht hab kein Zertifikat mehr muss jetzt ganzen kurz nochmal von vorne machen. https://www.udemy.com/course/hands-on-guide-fur-argo-workflows-in-kubernetes/learn/lecture/24515610#overview Diese Video Spiel auch nicht ab. Was ist hier los???
By Ahmed mohamed mahmoud gomaa on 4/6/2023
exactly what I search for , if you have course on apache atlas and apache knox
By Pedro de Jesus Bermejo Guerrero on 4/4/2022
Short but good to have an overview. I wish It would explain more about how Ranger works on the inside.
By Shahid Iqbal on 1/17/2022
Overall its a good hands on course based on its title.
By Anne Tall on 10/28/2021
Excellent class and instructor providing detailed technical information!
By Aditya S on 7/23/2021
This is a great course to understand the components of Apache Ranger and also covers very well how to use ranger
Quality Score
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Overall Score : 86 / 100







