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Introduction to QVDs in Qlik Sense

by Jay Cadmus

Unlock the power of data analysis with QVDs - Qlik's proprietary file format that optimizes data storage and retrieval for lightning-fast performance in Qlik Sense applications.
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Understanding the Purpose of QVDs
  • Data Persistence: QVD files serve as a persistent store for data used in Qlik Sense applications, allowing for rapid data loading and analysis.
  • Performance Optimization: Storing data in QVD format can significantly improve application performance by reducing the time required to load and process data.
  • Incremental Updates: QVDs enable efficient incremental data updates, allowing you to update only the changed or new data in your applications.
  • Reusability: QVD files can be shared and reused across multiple Qlik Sense applications, promoting data consistency and reducing development effort.
  • Data Governance: QVDs provide a controlled and auditable way to manage data sources, ensuring data integrity and security.
Accessing the Qlik Sense Scripting Documentation
Comprehensive Documentation
The Qlik Sense help site provides detailed technical documentation on all aspects of the platform, including scripting and QVD management.
Scripting Tutorials
Step-by-step guides and examples help users learn how to effectively leverage Qlik Sense scripting for data integration and transformation.
Searchable Content
The online documentation is fully searchable, allowing users to quickly find the information they need on specific Qlik Sense features and techniques.
Creating QVDs using the STORE Statement

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Identify Data
Determine the data you want to store in the QVD file.

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Use STORE Statement
Leverage the STORE statement in your Qlik Sense script to save the data.

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Specify File Name
Provide a unique and descriptive name for the QVD file.

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Set File Location
Specify the storage path for the QVD file within your Qlik Sense environment.
The STORE statement in the Qlik Sense scripting language allows you to save the data you have loaded and transformed into a QVD file. This provides a way to persist the data for future use, enabling efficient data access and minimizing the need for repetitive data processing.
Specifying the QVD File Name and Location
When creating QVD files using the STORE statement in Qlik Sense, you need to specify the file name and location. This is done by providing the full path and file name within the STORE statement. The path can be either an absolute path on the local file system or a relative path from the current working directory.
For example, to store a QVD file named sales_data.qvd in the C:\Qlik\DataFiles directory, the STORE statement would look like this:
STORE [SampleTable] INTO [lib:\Qlik\DataFiles\sample_data.qvd];
Ensuring the correct file name and location is crucial for efficiently organizing and managing your QVD files within your Qlik Sense application.
Controlling the content of the QVD file
Selective Data
When creating a QVD file, you can control the data that gets stored by using the WHERE clause in your STORE statement. This allows you to filter and include only the relevant data in the QVD file.
Field Selection
You can also specify which fields to include in the QVD file by listing them in the STORE statement. This helps optimize the file size and ensure that only the necessary data is stored.
Appending Data to an Existing QVD File
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Identify Existing QVD
Locate the QVD file you want to append data to in your Qlik Sense application.
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Modify Script
Update your load script to include the STORE statement with the QVD file name.
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Append Data
Use the CONCATENATE keyword to append new data to the existing QVD file.
Incremental Updates to QVD Files
  1. Leverage the INCREMENTAL keyword in the STORE statement to append new data to an existing QVD file.
  1. Ensure the WHERE clause specifies the appropriate filter to only load new or modified records.
  1. Use the FieldIntegrity function to validate field definitions between the QVD and the new data.
  1. Implement a process to manage version control and track changes to QVD files over time.
  1. Schedule periodic full reloads to optimize QVD file structure and maintain data integrity.
Compressing QVD Files for Efficient Storage

Reduce File Size
Compressing QVD files can significantly reduce their overall size, optimizing storage requirements and improving data transfer efficiency.

Faster Load Times
Compressed QVD files load more quickly, enhancing the performance of data retrieval and analysis processes.

Efficient Backup and Distribution
Compressed QVD files require less storage space and can be more easily backed up, shared, and distributed across systems.
Considerations for QVD File Naming Conventions
When naming QVD files, it's important to follow a consistent and meaningful convention to help with organization, identification, and maintenance. Some key considerations include using descriptive names that reflect the data contents, incorporating date or time information, and incorporating the data source or application name.
Adhering to a well-designed naming convention can make it easier to locate specific QVD files, track changes over time, and understand the purpose and origin of the data. This can be particularly valuable in environments with large numbers of QVD files or complex data models.
Reading QVD Files Using the LOAD Statement

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Specify QVD File
Use the LOAD statement to read data from a QVD file.

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Define File Path
Specify the full file path and name of the QVD file to load.

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Filter Data
Apply WHERE clauses to selectively load data from the QVD.

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Handle Errors
Ensure robust error handling when reading QVD files.
The LOAD statement in Qlik Sense scripting is used to read data from QVD files. This allows you to efficiently load data, apply filters, and handle any errors that may occur during the read process. By optimizing QVD file reads, you can improve the overall performance and reliability of your Qlik Sense applications.
Specifying the QVD file for data load
  • To read data from a QVD file in Qlik Sense, use the LOAD statement to specify the QVD file path and name.
  • The LOAD statement should include the FROM keyword followed by the file path and name of the QVD file to be loaded.
  • For example, LOAD * FROM [lib://DataFiles/mydata.qvd]; will load all fields from the mydata.qvd file located in the DataFiles library.
  • The file path can be specified using a Qlik Sense variable or a hard-coded absolute or relative path depending on your deployment.
  • Ensure the user accessing the QVD file has the necessary permissions to read the file from the specified location.
Filtering data during the QVD read
Selective Filtering
Use the WHERE clause in your LOAD statement to only read the specific data you need from the QVD file, reducing memory usage and improving performance.
Field-level Filtering
Specify which fields to include or exclude from the QVD read using the FIELDS clause, keeping your data set lean and focused.
Conditional Filtering
Leverage the IF-THEN-ELSE logic in your LOAD statement to dynamically filter data based on conditions, providing flexibility in your data processing.
Handling Errors When Reading QVD Files
When reading QVD files, it's important to have robust error handling mechanisms in place. Unexpected issues can arise, such as file access permissions, corrupted data, or incompatible file formats. Proper error handling ensures your data pipelines can gracefully handle these exceptions without causing complete failures.
You can use the TRY-CATCH construct in your Qlik Sense script to capture and handle any errors that occur during the QVD file read operation. This allows you to log the error details, notify the appropriate stakeholders, and potentially implement fallback strategies to recover from the issue.
Combining data from multiple QVD files

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Merge QVD Files
You can combine data from multiple QVD files using the CONCATENATE function in the Qlik Sense data load script.

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Specify File Paths
List the QVD file paths you want to read from, separating them with a comma inside the CONCATENATE statement.

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Align Field Names
Ensure the field names in the QVD files match so the data can be properly combined.
Optimizing QVD File Read Performance
Efficient Load
Load QVD files efficiently by using incremental updates and only loading the data needed.
Memory Management
Optimize memory usage by compressing QVD files and using appropriate data types.
Parallel Processing
Enable parallel processing to load multiple QVD files concurrently for improved performance.
Monitoring QVD File Usage and Size
Regularly monitoring the usage and size of your QVD files is crucial for maintaining efficient data processing and storage in your Qlik Sense application. By closely tracking QVD file metrics, you can identify opportunities for optimization, manage disk space, and ensure your data architecture remains scalable and performant.
Key metrics to monitor include the total number of QVD files, their individual and cumulative sizes, the frequency of access, and any trends in growth or usage over time. This data can be collected and visualized using Qlik Sense's native dashboarding capabilities or integrated with external monitoring tools.
Analyzing these insights will help you make informed decisions about file purging, compression, or restructuring your data model to maintain optimal QVD file management. Proactive monitoring allows you to stay ahead of potential performance issues and ensure your Qlik Sense environment continues to deliver value to your users.
Maintaining and Managing QVD Files
  • Monitoring QVD File Usage - Regularly review QVD file access patterns and load times to identify underutilized or performance-impacting files.
  • Optimizing QVD File Sizes - Compress QVD files, remove unnecessary data fields, and partition data to keep file sizes manageable.
  • Backup and Restore Procedures - Implement a robust backup strategy to safeguard QVD files and enable quick recovery in case of data loss or corruption.
  • Versioning and Archiving - Establish a versioning system to track changes to QVD files over time, and maintain an archive of older versions for historical analysis.
  • Automating QVD Maintenance - Develop scripts or workflows to automate common QVD management tasks, such as refreshing, compressing, or removing outdated files.
Best Practices for QVD File Management
Consistent Folder Structure
Maintain a well-organized folder hierarchy to store QVD files, making it easy to locate and manage them.
Detailed Documentation
Document the purpose, contents, and usage of each QVD file to ensure transparency and facilitate future maintenance.
Automated Processes
Implement scripts to automate the creation, update, and backup of QVD files, reducing manual effort and ensuring consistency.
Troubleshooting Common QVD-Related Issues
When working with QVD files in Qlik Sense, a few common issues may arise. These can include problems with file access, data integrity, or performance bottlenecks. Understanding how to identify and resolve these issues is crucial for maintaining a robust and reliable data infrastructure.
One common issue is file access errors, where the Qlik Sense engine is unable to locate or read the QVD file. This may be due to incorrect file paths, permissions problems, or network connectivity problems. Carefully reviewing the QVD file paths and access rights can help resolve these types of issues.
Another frequent problem is data integrity issues, where the QVD file contains corrupted or inconsistent data. This can happen due to issues with the data source, data transformation errors, or file corruption. Implementing robust data validation and testing procedures can help mitigate these problems.
Finally, performance bottlenecks can occur when loading or processing large QVD files. This may be caused by insufficient system resources, inefficient data structures, or suboptimal script designs. Profiling the load script, optimizing data modeling, and leveraging QVD compression can all help improve performance.
Key Takeaways
QVD files are a powerful feature in Qlik Sense that enable efficient data management and optimization. By understanding how to create, read, and maintain QVD files, you can improve the performance and reliability of your Qlik Sense applications.