Improved clustering and scaling
by Karl Pover, Stephen Redmond, Barry Harmsen, Miguel Angel Garcia
QlikView: Advanced Data Visualization
- QlikView: Advanced Data Visualization
- Table of Contents
- QlikView: Advanced Data Visualization
- Contributors
- Preface
- 1. Performance Tuning and Scalability
- Reviewing basic performance tuning techniques
- Generating test data
- Understanding how QlikView stores its data
- Strategies to reduce the data size and improve performance
- Testing chart performance for different load options
- Optimizing chart calculation times
- The QlikView calculation engine
- Using Direct Discovery
- Testing scalability with JMeter
- Running an example execution
- Summary
- 2. QlikView Data Modeling
- Reviewing basic data modeling
- Dimensional data modeling
- Differentiating between facts and dimensions
- Understanding the grain
- Understanding star schemas
- Summing with facts
- Discovering more about facts
- Dealing with nulls in fact tables in QlikView
- Designing dimension tables
- Defining Kimball's four-step dimensional design process
- Learning some useful reusable dimension methods
- Creating dimensional facts
- Handling slowly changing dimensions
- Dealing with multiple fact tables in one model
- Drilling across with document chaining
- Summary
- 3. Best Practices for Loading Data
- Reviewing data loading concepts
- Understanding why you should use an ETL approach
- Using an ETL approach to create QVD data layers
- Mastering loading techniques
- Using QlikView Expressor for ETL
- Summary
- 4. Advanced Expressions
- Reviewing basic concepts
- Understanding Dollar-sign Expansion
- Using advanced Set Analysis
- Calculating vertically
- Summary
- 5. Advanced Scripting
- Reviewing the basic concepts
- Counting records
- Loading data quickly
- Applying variables and the Dollar-sign Expansion in the script
- Using control structures
- Examining advanced Table File Wizard options
- Looking at data from different directions
- Reusing code
- Summary
- 6. What's New in QlikView 12?
- 7. Styling Up
- 8. Building Dashboards
- User types
- Applying the DAR principle to Airline Operations
- Creating the Analysis sheet
- Creating the new Dashboard sheet
- Creating the Reports sheet
- Other charts
- Summary
- 9. Advanced Data Transformation
- 10. Security
- 11. Data Visualization Strategy
- 12. Sales Perspective
- 13. Financial Perspective
- 14. Marketing Perspective
- 15. Working Capital Perspective
- 16. Operations Perspective
- 17. Human Resources
- 18. Fact Sheets
- 19. Balanced Scorecard
- 20. Troubleshooting Analysis
- 21. Mastering Qlik Sense Data Visualization
- Index
QlikView 12 supports more nodes in a clustered environment, which means that in multi-node environments QlikView will be able to support more concurrent users.
In QlikView 12.1, released in November 2016, even more improvements have been made in the area of clustering, allowing QlikView to scale to even more nodes, users, and documents.
Changes in QlikView 12.1 include improvements for dealing with high-load scenarios, such as shared file caching, offline mode for PGO files, better caching in AccessPoint, and more efficient communication between services.
QlikView 12.1 also has the option to use unbalanced nodes in a cluster (that is, using servers with differences in CPU and RAM in the same cluster). For Publisher, it is now possible to create multiple Publisher (QDS) clusters, referred to as Publisher groups, and to assigns tasks to specific nodes within a cluster.
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