Fuzzy Search Example

This example demonstrates how to integrate fuzzy search with debouncing into your table. Fuzzy search allows users to find approximate matches and partial values, enhancing the search experience especially for larger datasets.

Overview

In this example, you will learn how to:

• Enable fuzzy search filtering using the enableFiltering prop
• Use the useDebouncedSearch hook to debounce search input
• Update the table dynamically with search results

Example

Key Concepts

• Debounced Search: Prevents rapid firing of search requests by adding a delay before processing input.
• Fuzzy Matching: Allows matching based on similarity rather than exact value, making the search more forgiving.
• State Management: The onStateChange prop is used to capture changes in filtering state, triggering the search.

Customization Tips

• Adjust threshold and distance values in the useDebouncedSearch hook for optimal matching.
• Combine fuzzy search with other filters to refine search results.

Best Practices

1. Performance: Use debouncing to reduce the number of search operations.
2. User Experience: Provide feedback (e.g., loading indicators) during search operations.
3. Type Safety: Always define your data types and use createColumnHelper for consistency.

Next Steps

• Explore Header Groups Example to learn about grouping columns.
• Check Basic Table Example for fundamental setups.
• Experiment with Virtualized Table for handling large datasets.