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
English [Auto]
Current price: $11.99 Original price: $19.99 Discount: 40% off
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This course includes
  • 6 hours on-demand video
  • 1 article
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
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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
10:59
How Kylin Works. II
10:51
How Kylin Works. III
04:53
Our First Taste of a Kylin Cube
11:03
Exploring the web console
04:14
Resources
00:02
+ Use Case 1: AdventureWorks DW
8 lectures 01:10:24
AdventureWorks Dataset Preparation
12:19
Create Your Data Sources
05:53
Implementing The Data Model
08:29
Create The Cube
14:30
Building The Cube
04:57
Querying the Cube
08:14
Troubleshooting tips
12:22
+ Use Case 2: Analyzing Flight Delays
8 lectures 01:18:15
Dataset Preparation
07:25
Incremental Build
20:54
Running Incremental Cube Building
06:23
Single Fact/Dimension Table Model
10:57
Cube Optimization/Tuning I
16:32
Cube Optimization/Tuning II
08:56
Summary
03:50
+ Use Case 3: Access Log Files
7 lectures 59:56
How Kylin with Streaming Tables work?
06:25
Data Preparation & Kafka Setup
10:04
Implementing OLAP Cube Over Streaming Dataset in Kafka
19:13
Building The Cube With Streaming Logs
06:30
Query the Cube
06:21
Troubleshooting
08:12
+ Kylin Client Integration
5 lectures 42:53
Introduction to Kylin Client Integration
02:23
Rest API Integration
12:26
ODBC Integration (MS Excel)
07:29
JDBC Integration (Sample Java application)
06:32
Integrate with Apache Zeppelin
14:03
+ Other Features
3 lectures 25:41
Query Routing
09:41
Security
11:36
Storage Cleanup
04:24
Requirements
  • 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
Description

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.