In this post, I am sharing the Download Link of PasApache Ranger: Fine-Grained Access Control, by complete this course you can learn about the Integrate Apache Ranger with Hive, HDFS, Presto, Tagsync from Apache Atlas, etc. Our all kitfiles content is educational purpose only not for resell.
|Course Name||Apache Ranger: Fine-Grained Access Control|
|The Course is created by:||udemy|
|Category / genre||IT & Software|
Apache Ranger : Fine-Grained Access Control Free Download
What you’ll learnl
- 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 Atla
- Familiar with Hive, HDFS, Presto, Apache Atlas
- Good to have AWS EMR hands-on
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.
Who this course is for:
- Data Engineers
- Data Scientists