Apache Kylin : Implementing OLAP on the Hadoop platform
4.4 (95 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
426 students enrolled

Apache Kylin : Implementing OLAP on the Hadoop platform

Building and querying online analytical processing data (OLAP) big data structures in your hadoop platform
4.4 (95 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
426 students enrolled
Created by Michael Enudi
Last updated 6/2018
English [Auto]
Current price: $11.99 Original price: $19.99 Discount: 40% off
3 days left at this price!
30-Day Money-Back Guarantee
This course includes
  • 6 hours on-demand video
  • 1 article
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
Training 5 or more people?

Get your team access to 4,000+ top Udemy courses anytime, anywhere.

Try Udemy for Business
What you'll learn
  • Understand how OLAP Cube structures are created
  • Build and query OLAP Cubes on Hadoop Big Data Platform
  • Perform analytical queries on streaming data
  • Integrate your big data cube with external tools or application
  • Secure your OLAP Cube on the cluster
Course content
Expand all 43 lectures 06:08:52
+ Course Introduction
11 lectures 01:30:15
How Kylin Works. I
How Kylin Works. II
How Kylin Works. III
Our First Taste of a Kylin Cube
Exploring the web console
+ Use Case 1: AdventureWorks DW
8 lectures 01:10:24
AdventureWorks Dataset Preparation
Create Your Data Sources
Implementing The Data Model
Create The Cube
Building The Cube
Querying the Cube
Troubleshooting tips
+ Use Case 2: Analyzing Flight Delays
8 lectures 01:18:15
Dataset Preparation
Incremental Build
Running Incremental Cube Building
Single Fact/Dimension Table Model
Cube Optimization/Tuning I
Cube Optimization/Tuning II
+ Use Case 3: Access Log Files
7 lectures 59:56
How Kylin with Streaming Tables work?
Data Preparation & Kafka Setup
Implementing OLAP Cube Over Streaming Dataset in Kafka
Building The Cube With Streaming Logs
Query the Cube
+ Kylin Client Integration
5 lectures 42:53
Introduction to Kylin Client Integration
Rest API Integration
ODBC Integration (MS Excel)
JDBC Integration (Sample Java application)
Integrate with Apache Zeppelin
+ Other Features
3 lectures 25:41
Query Routing
Storage Cleanup
  • Ability to write a SQL query or use SQL query tool is required to be a Kylin User.
  • A good understanding of the hadoop big data platform is required to be a Kylin developer or adminstrator
  • Knowledge of hadoop technologies like MapReduce, Hive and HBase is necessary but not mandatory

A Comprehensive Course for Learning How to Build and Query Big Data OLAP Cubes Using Apache Kylin.

Apache Kylin is an Apache top-level project that bring OLAP to Big data. This simply means that we can now write complex aggregation queries with different levels of aggregation and expect to get a second or micro-seconds response to our query. 

Online analytical processing (OLAP) has been a common word in traditional business intelligence for years but has not been easy with hadoop platform that has become a data lake solution for many.  These data lake often have hundreds of millions and even billions of records that organizations want to slice and dice for insights. However, the high latency of query execution in SQL on Hadoop technologies like Apache Hive or Apache Drill often meant that data architect opted to transfer their data back to traditional systems that allow for real time response to query.

Kylin solves all of this. 

With Apache Kylin, anyone with the skills can now build OLAP, ROLAP or MOLAP structures using a web UI, deploy it and expect to query these structure with second of response time in mind. Also, one can connect their applications or favorite visualization tools to Kylin to integrate data either for system processing or for visualization. 

In this course, we are going to review 

  • What Kylin is
  • How it works
  • How to build OLAP cubes in batch and streaming model
  • How to deploy the cubes
  • How to query cubes
  • How to connect external tools and applications to Kylin
.. and many more

What is the target audience?

Big Data Engineers/Developers
Data Architects
Data Analysts.
Anyone who wishes to be able to write simple to complex aggregation queries of large dataset and wants a low latency response time.

What are the requirements?

You need access to a Big Data Sandbox like Cloudera quickstart VM, Hortonworks HDP sandbox or a cloud-based Hadoop environment with a least 10GB of Ram.
You should have some familiarity SQL and be able to use ODBC or JDBC based tools.
Some familiarity with Linux will be helpful

What do I need to know to get the best out of this course?

Because Kylin uses other hadoop projects to achieve its design a fair understanding of projects like Apache Hive, Apache Kafka, Apache HBase, MapReduce is great for this course. However, one can still use Kylin without any knowledge of these technologies. 

It is also worth knowing that no prior knowledge of any big data technology is required to query Kylin or use data integration in running report or data visualizations.

Who this course is for:
  • Data Analysts
  • Big Data/Hadoop Data Engineers
  • Data Architects
  • Anyone who wants to be able to perform a complex aggregate/OLAP queries on large dataset.