Apache Kylin: Real-Time OLAP on Big Data

• An understanding of Hadoop and big data ecosystems
• Familiarity with SQL and data warehousing concepts
• Basic knowledge of streaming data platforms like Kafka

Audience

• Big data engineers seeking to implement real-time analytics solutions
• Data analysts aiming to leverage OLAP capabilities on large datasets
• Data warehouse architects interested in modernizing their infrastructure

Apache Kylin is a distributed analytics engine designed to provide OLAP (Online Analytical Processing) capabilities on big data. With the release of version 5.0, Kylin introduces real-time streaming support, enabling sub-second query responses on streaming data sources like Kafka. The platform offers a powerful SQL interface, seamless integration with BI tools, and a redesigned web UI for intuitive modeling and analysis.

This instructor-led, live training (online or onsite) is aimed at intermediate-level big data professionals who wish to utilize Apache Kylin for building real-time data warehouses and performing multidimensional analysis on large-scale datasets.

By the end of this training, participants will be able to:

• Set up and configure Apache Kylin with real-time streaming data sources.
• Design and build OLAP cubes for both batch and streaming data.
• Perform complex queries with sub-second latency using Kylin's SQL interface.
• Integrate Kylin with BI tools for interactive data visualization.
• Optimize performance and manage resources effectively in Kylin.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Introduction to Apache Kylin

• Overview of OLAP and its significance in big data analytics
• Evolution of Apache Kylin and its architecture
• Key features and capabilities of Kylin 50

Setting Up Apache Kylin

• Installation prerequisites and environment setup
• Configuring Kylin with Hadoop, Spark, and Kafka
• Understanding Kylin's web UI and command-line tools

Data Modeling in Kylin

• Designing star and snowflake schemas for OLAP cubes
• Defining dimensions and measures
• Creating and managing data models in Kylin's web UI

Building and Managing Cubes

• Cube building process and job management
• Incremental builds and auto-merge strategies
• Monitoring cube health and performance

Real-Time Streaming with Kylin

• Integrating Kafka as a streaming data source
• Setting up real-time cubes and fusion models
• Achieving low-latency analytics with streaming data

Querying and Analysis

• Executing SQL queries using Kylin's query interface
• Connecting BI tools (eg, Tableau, Power BI) to Kylin
• Performing multidimensional analysis and drill-downs

Performance Optimization

• Best practices for cube design and aggregation
• Resource management and tuning for scalability
• Troubleshooting common performance issues

Advanced Topics

• Security and access control in Kylin
• Extending Kylin with custom plugins and integrations
• Exploring Kylin's REST APIs for automation

Summary and Next Steps