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Practice & Implementation - Search Explorer & Portal Tools

Overview

This guide provides hands-on exercises and practical implementation scenarios for mastering Azure AI Search portal tools. Work through these exercises to build real-world skills with Search Explorer, Import Data wizard, and portal management features.

Prerequisites

Before starting these exercises, ensure you have: - Completed the Prerequisites setup - Access to Azure portal with Azure AI Search service - Sample data available for testing - Basic understanding of search concepts from previous modules

Exercise 1: Search Explorer Mastery

Objective

Master the Search Explorer interface and learn to construct, test, and debug search queries interactively.

Scenario

You're developing a hotel booking application and need to test various search scenarios using the Azure portal before implementing them in code.

Tasks

Task 1.1: Basic Search Operations

Navigate to Search Explorer and perform these basic operations:

Step 1: Simple Text Search 

{
  "search": "hotel"
}

Step 2: Wildcard Search 

{
  "search": "hot*"
}

Step 3: Phrase Search 

{
  "search": "\"luxury hotel\""
}

Implementation Notes: - Observe how different search types return different results - Note the relevance scores in the results - Pay attention to which fields are being searched

Task 1.2: Advanced Query Parameters

Test various query parameters to understand their effects:

Field-Specific Search 

{
  "search": "luxury",
  "searchFields": "HotelName,Description"
}

Search Mode Configuration 

{
  "search": "luxury hotel",
  "searchMode": "all"
}

Query Type Selection 

{
  "search": "hotel AND (pool OR spa)",
  "queryType": "full"
}

Task 1.3: Result Customization

Learn to shape and customize search results:

Field Selection 

{
  "search": "hotel",
  "select": "HotelName,Rating,Address/City"
}

Result Limiting 

{
  "search": "*",
  "top": 5,
  "skip": 10
}

Hit Highlighting 

{
  "search": "luxury",
  "highlight": "Description",
  "highlightPreTag": "<mark>",
  "highlightPostTag": "</mark>"
}

Expected Outcomes

  • Understand Search Explorer interface and capabilities
  • Master basic and advanced query construction
  • Learn to customize and analyze search results

Exercise 2: Filtering and Sorting in Search Explorer

Objective

Implement complex filtering and sorting scenarios using the portal interface.

Scenario

Hotel customers need sophisticated filtering options: price ranges, ratings, amenities, and location-based searches.

Tasks

Task 2.1: Basic Filtering

Test various filter scenarios:

Category Filtering 

{
  "search": "*",
  "filter": "Category eq 'Luxury'"
}

Rating Range 

{
  "search": "*",
  "filter": "Rating ge 4.0 and Rating le 5.0"
}

Boolean Filtering 

{
  "search": "*",
  "filter": "ParkingIncluded eq true"
}

Task 2.2: Complex Filter Combinations

Build sophisticated filter expressions:

Multi-Criteria Filtering 

{
  "search": "hotel",
  "filter": "Category eq 'Luxury' and Rating ge 4.5 and ParkingIncluded eq true"
}

OR Logic Filtering 

{
  "search": "*",
  "filter": "Category eq 'Luxury' or Category eq 'Boutique'"
}

Collection Filtering 

{
  "search": "*",
  "filter": "Tags/any(t: t eq 'pool' or t eq 'spa')"
}

Task 2.3: Geographic Filtering

Test location-based filtering:

Distance-Based Filtering 

{
  "search": "*",
  "filter": "geo.distance(Location, geography'POINT(-73.975403 40.760586)') lt 10"
}

Combined Geographic and Rating Filter 

{
  "search": "*",
  "filter": "geo.distance(Location, geography'POINT(-73.975403 40.760586)') lt 5 and Rating ge 4.0"
}

Task 2.4: Sorting Operations

Test various sorting scenarios:

Single Field Sorting 

{
  "search": "*",
  "orderby": "Rating desc"
}

Multi-Field Sorting 

{
  "search": "*",
  "orderby": "Category asc, Rating desc"
}

Geographic Sorting 

{
  "search": "*",
  "orderby": "geo.distance(Location, geography'POINT(-73.975403 40.760586)')"
}

Expected Outcomes

  • Master complex filtering techniques
  • Understand geographic search capabilities
  • Learn effective sorting strategies

Exercise 3: Faceted Navigation and Aggregations

Objective

Implement faceted search and understand aggregation capabilities through the portal.

Scenario

Create a faceted navigation system for hotel search that allows users to refine results by category, rating, city, and amenities.

Tasks

Task 3.1: Basic Faceting

Configure and test faceted search:

Category Facets 

{
  "search": "*",
  "facets": ["Category"]
}

Rating Facets with Intervals 

{
  "search": "*",
  "facets": ["Rating,interval:1"]
}

Multiple Facets 

{
  "search": "*",
  "facets": ["Category", "Address/City", "ParkingIncluded"]
}

Task 3.2: Advanced Faceting

Explore advanced faceting scenarios:

Facets with Filtering 

{
  "search": "hotel",
  "filter": "Category eq 'Luxury'",
  "facets": ["Address/City", "Rating,interval:0.5"]
}

Collection Facets 

{
  "search": "*",
  "facets": ["Tags"]
}

Task 3.3: Facet Analysis

Analyze facet results to understand data distribution:

  1. Count Analysis: Examine document counts for each facet value
  2. Coverage Analysis: Identify which facets provide good filtering options
  3. User Experience: Consider which facets would be most useful for users

Expected Outcomes

  • Understand faceted search implementation
  • Learn to analyze facet data for UX decisions
  • Master advanced faceting scenarios

Exercise 4: Import Data Wizard Walkthrough

Objective

Use the Import Data wizard to create complete search solutions from various data sources.

Scenario

Set up automated indexing for a hotel database stored in Azure Blob Storage, including AI enrichment for content extraction.

Tasks

Task 4.1: Azure Blob Storage Import

Create an end-to-end solution using the Import Data wizard:

Step 1: Data Source Configuration 1. Click "Import data" in the Azure portal 2. Select "Azure Blob Storage" as data source 3. Configure connection string and container 4. Set parsing mode (JSON, delimited text, etc.)

Step 2: Cognitive Skills (Optional) 1. Add cognitive skills for content enrichment 2. Configure key phrase extraction 3. Set up entity recognition 4. Configure language detection

Step 3: Index Customization 1. Review auto-generated index schema 2. Modify field attributes as needed 3. Configure analyzers for text fields 4. Set up field mappings

Step 4: Indexer Configuration 1. Set indexer name and description 2. Configure execution schedule 3. Set up change detection policy 4. Configure field mappings

Task 4.2: Azure SQL Database Import

Set up indexing from a relational database:

Step 1: Database Connection 1. Select "Azure SQL Database" as data source 2. Configure connection string 3. Select table or view 4. Configure query for data extraction

Step 2: Change Detection 1. Set up high water mark change detection 2. Configure deletion detection policy 3. Test connection and data access

Step 3: Index and Indexer Setup 1. Customize generated index schema 2. Configure field mappings for relational data 3. Set up appropriate indexer schedule

Task 4.3: Monitoring and Validation

After wizard completion:

Indexer Monitoring 1. Navigate to "Indexers" in the portal 2. Monitor indexer execution status 3. Review execution history and statistics 4. Check for errors or warnings

Index Validation 1. Use Search Explorer to test indexed data 2. Verify field mappings are correct 3. Test search functionality 4. Validate document count and content

Expected Outcomes

  • Master the Import Data wizard workflow
  • Understand different data source configurations
  • Learn to monitor and validate automated indexing

Exercise 5: Portal Management and Monitoring

Objective

Learn to effectively manage and monitor Azure AI Search services using portal tools.

Scenario

You're responsible for maintaining a production search service and need to monitor performance, manage resources, and troubleshoot issues.

Tasks

Task 5.1: Service Overview and Health

Explore the service management interface:

Service Dashboard 1. Navigate to service overview page 2. Review service tier and capacity 3. Check service health status 4. Monitor key metrics and usage

Resource Management 1. Review search units and replicas 2. Check storage usage and limits 3. Monitor API key usage 4. Review service configuration

Task 5.2: Index Management

Learn comprehensive index management:

Index Operations 1. View all indexes in the service 2. Check index statistics (document count, size) 3. Review index schema and field configurations 4. Monitor index performance metrics

Index Maintenance 1. Practice index rebuilding process 2. Understand index deletion implications 3. Learn index backup and restore concepts 4. Review index versioning strategies

Task 5.3: Indexer Management

Master indexer operations and monitoring:

Indexer Status Monitoring 1. View all indexers and their status 2. Review execution history and patterns 3. Analyze performance metrics 4. Identify and troubleshoot failures

Indexer Operations 1. Practice manual indexer execution 2. Modify indexer schedules 3. Update indexer configurations 4. Handle indexer errors and warnings

Task 5.4: Performance Monitoring

Set up comprehensive performance monitoring:

Metrics Analysis 1. Review search latency trends 2. Monitor query volume and patterns 3. Analyze indexing performance 4. Track resource utilization

Alert Configuration 1. Set up performance alerts 2. Configure error rate monitoring 3. Create capacity utilization alerts 4. Test alert notification systems

Expected Outcomes

  • Master service management and monitoring
  • Understand performance optimization techniques
  • Learn proactive maintenance strategies

Exercise 6: Query Development and Testing

Objective

Develop a systematic approach to query development and testing using portal tools.

Scenario

Build and test a comprehensive set of search queries for different user scenarios in a hotel booking application.

Tasks

Task 6.1: User Scenario Mapping

Define and test queries for different user types:

Business Traveler Queries 

{
  "search": "business hotel",
  "filter": "Category eq 'Business' and ParkingIncluded eq true",
  "orderby": "Rating desc",
  "facets": ["Address/City"]
}

Leisure Traveler Queries 

{
  "search": "resort spa pool",
  "filter": "Tags/any(t: t eq 'pool' or t eq 'spa')",
  "orderby": "Rating desc",
  "facets": ["Category", "Tags"]
}

Budget-Conscious Queries 

{
  "search": "*",
  "filter": "Rating ge 3.0",
  "orderby": "Rating desc",
  "facets": ["Category", "ParkingIncluded"]
}

Task 6.2: Performance Testing

Test query performance with different parameters:

Result Set Size Impact 

// Test with different top values
{"search": "*", "top": 10}
{"search": "*", "top": 50}
{"search": "*", "top": 100}

Field Selection Impact 

// All fields vs. selected fields
{"search": "hotel"}
{"search": "hotel", "select": "HotelName,Rating"}

Filter Complexity Impact 

// Simple vs. complex filters
{"search": "*", "filter": "Rating gt 4.0"}
{"search": "*", "filter": "Rating gt 4.0 and Category eq 'Luxury' and ParkingIncluded eq true"}

Task 6.3: Query Optimization

Optimize queries based on testing results:

Identify Slow Queries 1. Use browser developer tools to measure response times 2. Test with realistic data volumes 3. Document performance benchmarks 4. Identify optimization opportunities

Optimize Query Structure 1. Reorder filter conditions for better performance 2. Use more selective filters first 3. Optimize field selection 4. Consider facet usage impact

Expected Outcomes

  • Develop systematic query testing approach
  • Understand performance optimization techniques
  • Create reusable query patterns

Exercise 7: Troubleshooting and Debugging

Objective

Learn to diagnose and resolve common issues using portal tools.

Scenario

Troubleshoot various problems that arise in a production search environment.

Tasks

Task 7.1: Query Troubleshooting

Diagnose and fix common query issues:

Syntax Error Resolution 

// ❌ Problematic query
{
  "search": "hotel",
  "filter": "Rating > 4.0"  // Invalid operator
}

// ✅ Fixed query
{
  "search": "hotel",
  "filter": "Rating gt 4.0"  // Correct OData syntax
}

Field Reference Errors 

// ❌ Problematic query
{
  "search": "hotel",
  "filter": "rating gt 4.0"  // Incorrect field name case
}

// ✅ Fixed query
{
  "search": "hotel",
  "filter": "Rating gt 4.0"  // Correct field name
}

Task 7.2: Indexer Troubleshooting

Diagnose and resolve indexer issues:

Connection Problems 1. Test data source connectivity 2. Verify credentials and permissions 3. Check network access and firewall rules 4. Validate connection strings

Data Processing Errors 1. Review indexer execution logs 2. Identify problematic documents 3. Check field mapping configurations 4. Validate data formats and types

Performance Issues 1. Monitor indexer execution times 2. Identify bottlenecks in data processing 3. Optimize batch sizes and schedules 4. Review resource utilization

Task 7.3: Service Health Monitoring

Monitor and maintain service health:

Capacity Management 1. Monitor storage usage trends 2. Track query volume patterns 3. Analyze resource utilization 4. Plan for capacity scaling

Error Rate Analysis 1. Review error logs and patterns 2. Identify common failure scenarios 3. Implement preventive measures 4. Set up proactive monitoring

Expected Outcomes

  • Master troubleshooting techniques
  • Understand common problem patterns
  • Develop proactive monitoring strategies

Exercise 8: Integration Planning

Objective

Plan the transition from portal-based development to programmatic implementation.

Scenario

You've developed and tested search functionality in the portal and now need to implement it programmatically in your application.

Tasks

Task 8.1: Configuration Export

Document and export portal configurations:

Query Pattern Documentation 

// Document successful query patterns
const queryPatterns = {
  hotelSearch: {
    search: "hotel",
    filter: "Rating ge 4.0",
    orderby: "Rating desc",
    select: "HotelName,Rating,Address/City",
    facets: ["Category", "Address/City"]
  },
  locationSearch: {
    search: "*",
    filter: "geo.distance(Location, geography'POINT(-73.975403 40.760586)') lt 10",
    orderby: "geo.distance(Location, geography'POINT(-73.975403 40.760586)')"
  }
};

Index Schema Export 1. Copy index definition from portal 2. Save as JSON configuration file 3. Document field attribute decisions 4. Create deployment templates

Task 8.2: API Implementation Planning

Plan the programmatic implementation:

SDK Selection 1. Choose appropriate SDK (.NET, Python, JavaScript) 2. Plan authentication strategy 3. Design error handling approach 4. Consider performance optimization

Architecture Design 1. Plan search service integration 2. Design caching strategies 3. Consider scalability requirements 4. Plan monitoring and logging

Task 8.3: Testing Strategy

Develop comprehensive testing approach:

Unit Testing 1. Test query construction logic 2. Validate filter building functions 3. Test result processing code 4. Mock search service responses

Integration Testing 1. Test against actual search service 2. Validate end-to-end workflows 3. Test error handling scenarios 4. Performance testing with realistic loads

Expected Outcomes

  • Successfully transition from portal to code
  • Create comprehensive implementation plan
  • Establish testing and validation strategies

Completion Checklist

After completing these exercises, you should be able to:

  • [ ] Navigate and use Search Explorer effectively
  • [ ] Construct complex search queries with filters and sorting
  • [ ] Implement faceted search and analyze results
  • [ ] Use Import Data wizard for various data sources
  • [ ] Monitor and manage search services through portal
  • [ ] Troubleshoot common issues using portal tools
  • [ ] Optimize query performance based on testing
  • [ ] Plan transition from portal to programmatic implementation

Next Steps

  1. Apply to Your Project: Implement these techniques in your own search application
  2. Explore Advanced Features: Move on to intermediate modules for advanced capabilities
  3. Automation: Begin implementing programmatic versions of portal workflows
  4. Production Readiness: Focus on monitoring, scaling, and maintenance strategies

Additional Resources

Module Documentation

External Resources

When You Need Help

Remember: The portal is your testing ground and learning environment. Use it to experiment, validate concepts, and build confidence before implementing in code.