Code Samples - Module 6: Filters & Sorting¶

Overview¶

This directory contains comprehensive code samples demonstrating how to implement filters and sorting in Azure AI Search. The examples cover various filter types, sorting strategies, and optimization techniques across multiple programming languages.

Sample Categories¶

1. Basic Filters¶

Equality filters (eq, ne)
Comparison filters (gt, ge, lt, le)
Boolean logic combinations
Null value handling

2. Range Filters¶

Numeric range filtering
Date range filtering
Price range implementations
Performance optimization techniques

3. String Filters¶

Text matching with startswith, endswith, contains
Case sensitivity handling
Pattern matching techniques
Multi-language considerations

4. Date Filters¶

Date range filtering
Relative date calculations
Time zone handling
Date format considerations

5. Geographic Filters¶

Distance-based filtering
Bounding box filtering
Location proximity searches
Geographic sorting by distance

6. Sorting Operations¶

Single field sorting
Multi-field sorting
Custom sort orders
Performance optimization

7. Complex Filters¶

Collection filtering with any() and all()
Nested field filtering
Combined filter and search queries
Advanced logical expressions

8. Performance Tips¶

Filter optimization strategies
Index design considerations
Query performance monitoring
Caching strategies

Programming Languages¶

Each sample category is implemented in multiple programming languages:

Python - Using azure-search-documents SDK
C# - Using Azure.Search.Documents SDK
JavaScript/Node.js - Using @azure/search-documents SDK
REST API - Direct HTTP calls with examples

Sample Structure¶

Each programming language directory contains:

language/
├── README.md                    # Language-specific setup and overview
├── 01_basic_filters.*          # Basic filter implementations
├── 02_range_filters.*          # Range filtering examples
├── 03_string_filters.*         # String filtering techniques
├── 04_date_filters.*           # Date and time filtering
├── 05_geographic_filters.*     # Location-based filtering
├── 06_sorting_operations.*     # Sorting implementations
├── 07_complex_filters.*        # Advanced filtering scenarios
└── 08_performance_tips.*       # Optimization techniques

Prerequisites¶

Before running these samples, ensure you have:

Azure Resources¶

Azure AI Search service
Search index with filterable and sortable fields
Sample data for testing

Development Environment¶

Programming language runtime
Required SDKs and packages installed
Code editor or IDE
REST client (for REST API examples)

Index Configuration¶

Your search index should have fields configured with appropriate attributes: - filterable: true for fields used in filters - sortable: true for fields used in sorting - facetable: true for fields used in faceted navigation

Quick Start¶

1. Choose Your Language¶

Navigate to the appropriate language directory: - Python Examples - C# Examples - JavaScript Examples - REST API Examples

2. Set Up Environment¶

Follow the language-specific setup instructions in each directory's README.

3. Configure Connections¶

Update configuration files with your Azure AI Search service details.

4. Run Samples¶

Start with basic examples and progress to more complex scenarios.

Sample Scenarios¶

Scenario 1: E-commerce Product Filtering¶

Files: 01_basic_filters.*, 02_range_filters.*, 06_sorting_operations.*

Implement product catalog filtering: - Filter by category, brand, price range - Sort by price, rating, popularity - Handle multiple filter combinations - Optimize for performance

Scenario 2: Hotel Search with Location¶

Files: 05_geographic_filters.*, 04_date_filters.*, 07_complex_filters.*

Build location-based hotel search: - Filter by distance from location - Date range availability filtering - Amenity filtering with collections - Sort by distance and rating

Scenario 3: Document Search with Metadata¶

Files: 03_string_filters.*, 04_date_filters.*, 08_performance_tips.*

Search documents with metadata filtering: - Filter by document type, author, tags - Date range filtering for creation/modification - Text content filtering - Performance optimization

Filter Syntax Examples¶

Basic Equality Filters¶

category eq 'Electronics'
status ne 'Discontinued'
inStock eq true

Range Filters¶

price gt 100 and price lt 500
rating ge 4.0
lastModified gt 2024-01-01T00:00:00Z

String Filters¶

startswith(name, 'iPhone')
contains(description, 'wireless')
endswith(model, 'Pro')

Geographic Filters¶

geo.distance(location, geography'POINT(-122.131577 47.678581)') lt 10

Collection Filters¶

tags/any(t: t eq 'featured')
amenities/all(a: a ne null)

Complex Combinations¶

(category eq 'Hotels' and rating gt 4.0) or (category eq 'Resorts' and price lt 300)

Sorting Examples¶

Basic Sorting¶

$orderby=rating desc
$orderby=price asc
$orderby=name

Multi-field Sorting¶

$orderby=category asc, rating desc, price asc

Geographic Sorting¶

$orderby=geo.distance(location, geography'POINT(-122.131577 47.678581)')

Configuration Templates¶

Environment Variables¶

# Azure AI Search
SEARCH_SERVICE_NAME=your-search-service
SEARCH_API_KEY=your-api-key
SEARCH_ENDPOINT=https://your-search-service.search.windows.net
INDEX_NAME=your-index-name

Sample Index Schema¶

{
  "name": "products",
  "fields": [
    {"name": "id", "type": "Edm.String", "key": true},
    {"name": "name", "type": "Edm.String", "searchable": true, "filterable": true, "sortable": true},
    {"name": "category", "type": "Edm.String", "filterable": true, "facetable": true},
    {"name": "price", "type": "Edm.Double", "filterable": true, "sortable": true, "facetable": true},
    {"name": "rating", "type": "Edm.Double", "filterable": true, "sortable": true},
    {"name": "inStock", "type": "Edm.Boolean", "filterable": true},
    {"name": "lastModified", "type": "Edm.DateTimeOffset", "filterable": true, "sortable": true},
    {"name": "location", "type": "Edm.GeographyPoint", "filterable": true, "sortable": true},
    {"name": "tags", "type": "Collection(Edm.String)", "filterable": true, "facetable": true}
  ]
}

Best Practices Demonstrated¶

Performance Optimization¶

Efficient filter construction
Proper field attribute usage
Query optimization techniques
Result set size management

User Experience¶

Progressive filtering
Faceted navigation
Sort option presentation
Filter state management

Error Handling¶

Invalid filter syntax handling
Data type validation
Graceful degradation
User feedback mechanisms

Testing and Validation¶

Unit Tests¶

Each language directory includes tests for: - Filter syntax validation - Sort parameter handling - Error condition testing - Performance benchmarking

Integration Tests¶

End-to-end tests covering: - Complete filtering workflows - Multi-criteria scenarios - Performance validation - User experience flows

Sample Data Sets¶

Test data includes: - Various data types and ranges - Edge cases and null values - Geographic coordinates - Collection fields

Performance Considerations¶

Filter Optimization¶

Use most selective filters first
Combine filters efficiently
Avoid complex nested expressions
Monitor query performance

Sorting Optimization¶

Use appropriate field types
Consider storage implications
Implement caching strategies
Monitor resource usage

Index Design¶

Mark only necessary fields as filterable/sortable
Consider field storage requirements
Optimize for common query patterns
Balance functionality vs. performance

Troubleshooting¶

Common Issues¶

Field not filterable/sortable errors
Invalid OData syntax
Data type mismatches
Performance problems

Debugging Tools¶

Query syntax validation
Performance profiling
Error message interpretation
Index analysis tools

Interactive Notebooks¶

The notebooks directory contains Jupyter notebooks with: - Interactive filter building - Visual query results - Performance analysis - Experimentation environments

Additional Resources¶

Module Documentation¶

Main Documentation - Complete module overview
Prerequisites - Required setup and knowledge
Best Practices - Guidelines for effective implementation
Practice & Implementation - Hands-on exercises
Troubleshooting - Common issues and solutions

External Resources¶

When You Need Help¶

Syntax Issues: Check the Troubleshooting Guide
Performance Problems: Review Performance Analysis Examples
Complex Scenarios: Explore Complex Filter Examples

Next Steps¶

After exploring these samples: 1. Implement similar patterns in your projects 2. Customize for your specific data and requirements 3. Explore advanced features in intermediate modules 4. Share your experiences with the community

Feedback and Support¶

For questions, issues, or suggestions: - Review the troubleshooting guides - Check the Azure AI Search documentation - Engage with the community forums - Submit feedback through appropriate channels