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Overview

This guide helps you diagnose and resolve performance issues when using Koala Data Explorer with Oracle Fusion Cloud.

Slow Query Performance

Identifying Slow Queries

Symptoms:
  • Queries take long time to execute
  • Timeout errors
  • VS Code becomes unresponsive during query execution
Diagnostic Steps:
  1. Check query execution time: Monitor timing in results panel
  2. Compare similar queries: See if specific queries are slower
  3. Test with row limits: Add WHERE ROWNUM <= 100 to test

Common Causes of Slow Queries

Large Result Sets

Problem: Returning too many rows
-- Slow: No row limit
SELECT * FROM ap_invoices_all;

-- Better: With reasonable limit
SELECT * FROM ap_invoices_all WHERE ROWNUM <= 1000;
Solutions:
  1. Add row limits: Always use ROWNUM or FETCH FIRST
  2. Filter data: Use specific WHERE clauses
  3. Select specific columns: Avoid SELECT *

Missing WHERE Clauses

Problem: Full table scans on large tables
-- Slow: Full table scan
SELECT * FROM per_all_people_f;

-- Better: Filtered query
SELECT * FROM per_all_people_f 
WHERE effective_end_date = DATE '4712-12-31'
AND ROWNUM <= 1000;

Inefficient Joins

Problem: Joining large tables without proper conditions
-- Slow: Cartesian product
SELECT e.*, d.*
FROM per_all_people_f e, hr_all_organization_units d;

-- Better: Proper join with conditions
SELECT e.person_number, d.name
FROM per_all_people_f e
JOIN per_all_assignments_m a ON e.person_id = a.person_id
JOIN hr_all_organization_units d ON a.organization_id = d.organization_id
WHERE e.effective_end_date = DATE '4712-12-31'
AND a.effective_end_date = DATE '4712-12-31'
AND ROWNUM <= 1000;

Network Performance Issues

Slow Connection to Oracle Fusion

Symptoms:
  • Long delays before queries start executing
  • Intermittent timeouts
  • Slow authentication
Causes:
  1. Network latency: Distance to Oracle Fusion servers
  2. VPN overhead: Corporate VPN adding latency
  3. Bandwidth limitations: Slow internet connection
  4. Proxy servers: Corporate proxies adding delays
Solutions:
  1. Test network speed: Use network speed tests
  2. Check VPN: Try without VPN if possible
  3. Use wired connection: Ethernet instead of WiFi
  4. Peak hours: Avoid peak usage times

DNS Resolution Issues

Symptoms:
  • Initial connection delays
  • Intermittent “host not found” errors
Solutions:
  1. Use IP addresses: If DNS is slow, try IP address
  2. DNS cache: Clear DNS cache on your machine
  3. Alternative DNS: Try different DNS servers (8.8.8.8, 1.1.1.1)

VS Code Performance Issues

High Memory Usage

Symptoms:
  • VS Code becomes slow or unresponsive
  • High memory usage in Task Manager
  • System becomes sluggish
Causes:
  1. Large result sets: Too much data loaded in memory
  2. Multiple query tabs: Many tabs with results open
  3. Query history: Large query history accumulation
Solutions:
  1. Clear results: Close result tabs when done
  2. Limit query results: Use smaller row limits
  3. Restart VS Code: Periodically restart to clear memory
  4. Close unused tabs: Keep only necessary tabs open

Slow UI Response

Symptoms:
  • Typing lag in query editor
  • Slow scrolling through results
  • Delayed button clicks
Solutions:
  1. Reduce result set size: Display fewer rows
  2. Close large results: Clear memory-intensive results
  3. Disable extensions: Temporarily disable other VS Code extensions
  4. Check system resources: Monitor CPU and memory usage

Oracle Fusion Performance

Database-Side Performance

Common Oracle Issues:
  1. Peak usage times: High load during business hours
  2. Maintenance windows: Scheduled maintenance affecting performance
  3. Resource contention: Other users running heavy queries
Solutions:
  1. Off-peak usage: Run queries during low-usage times
  2. Check announcements: Monitor Oracle Fusion maintenance schedules
  3. Optimize queries: Use efficient SQL patterns

Query Optimization Techniques

Use Indexes Effectively

-- Good: Filter on indexed columns
SELECT * FROM ap_invoices_all 
WHERE invoice_date >= DATE '2024-01-01'
AND ROWNUM <= 1000;

-- Avoid: Functions on indexed columns
SELECT * FROM ap_invoices_all 
WHERE TO_CHAR(invoice_date, 'YYYY') = '2024';

Efficient Date Filtering

-- Efficient: Date range filtering
SELECT * FROM transactions
WHERE transaction_date BETWEEN DATE '2024-01-01' AND DATE '2024-12-31'
AND ROWNUM <= 1000;

-- Less efficient: Date functions
SELECT * FROM transactions
WHERE EXTRACT(YEAR FROM transaction_date) = 2024;

Data Export Performance

Slow Export Operations

Symptoms:
  • Export operations take very long
  • Export failures due to timeouts
  • Large file generation delays
Solutions:

For Large Datasets:

  1. Use CSV instead of Excel: CSV is faster for large data
  2. Export in batches: Break large exports into smaller chunks
  3. Filter before export: Reduce data size with WHERE clauses

Excel Export Optimization:

-- For Excel export (10K row limit)
SELECT specific_columns
FROM your_table
WHERE filter_conditions
AND ROWNUM <= 10000;

CSV Export for Large Data:

-- For large CSV exports
SELECT specific_columns
FROM your_table
WHERE filter_conditions
AND ROWNUM <= 50000; -- Adjust based on needs

Performance Monitoring

Built-in Performance Tracking

Available Metrics:
  • Query execution time (displayed in results)
  • Row count returned
  • Connection response time
How to Use:
  1. Monitor timing: Check execution time for each query
  2. Compare performance: Track changes over time
  3. Identify patterns: Note which queries are consistently slow

Performance Benchmarking

Simple Benchmarks:
-- Test connection speed
SELECT 1 FROM dual;

-- Test simple table access
SELECT COUNT(*) FROM hr_all_organization_units;

-- Test filtered query
SELECT COUNT(*) FROM per_all_people_f 
WHERE effective_end_date = DATE '4712-12-31';

System Resource Optimization

Computer Performance

Recommended Specifications:
  • RAM: 8GB+ (16GB recommended)
  • CPU: Modern multi-core processor
  • Storage: SSD recommended for better performance
  • Network: Stable broadband connection
Optimization Tips:
  1. Close unnecessary applications: Free up system resources
  2. Regular restarts: Clear memory and temporary files
  3. Disk cleanup: Ensure adequate free disk space
  4. Update drivers: Keep network and graphics drivers current

VS Code Optimization

Settings to Consider:
{
  "koalaDataExplorer.maxRows": 1000,
  "koalaDataExplorer.timeout": 120000,
  "koalaDataExplorer.autoRefreshDataSources": false
}
Extension Management:
  1. Disable unused extensions: Reduce VS Code overhead
  2. Update regularly: Keep Koala and VS Code updated
  3. Reset settings: Restore default settings if issues persist

Troubleshooting Workflow

Step-by-Step Performance Diagnosis

  1. Identify the issue:
    • Slow queries?
    • Slow connections?
    • Slow UI?
    • Slow exports?
  2. Isolate the cause:
    • Test simple queries first
    • Check network connectivity
    • Monitor system resources
    • Compare with known working queries
  3. Apply targeted solutions:
    • Query optimization for slow queries
    • Network troubleshooting for connection issues
    • Resource management for UI issues
  4. Verify improvement:
    • Test the same operations again
    • Monitor performance over time
    • Document what worked

Performance Testing Queries

Connection Test:
SELECT SYSDATE FROM dual;
Small Table Test:
SELECT COUNT(*) FROM fnd_lookup_values WHERE ROWNUM <= 1;
Filtered Query Test:
SELECT * FROM hr_all_organization_units 
WHERE organization_id < 1000 
AND ROWNUM <= 100;

Best Practices for Performance

Query Writing Best Practices

  1. Always use row limits: Protect against accidentally large results
  2. Filter early and often: Use WHERE clauses to reduce data
  3. Select only needed columns: Avoid SELECT *
  4. Use appropriate date ranges: Don’t query all historical data
  5. Test with small datasets first: Verify query logic before scaling up

Usage Patterns

  1. Plan your queries: Think about what data you need before writing SQL
  2. Reuse successful patterns: Save and reuse well-performing queries
  3. Monitor your usage: Be aware of peak times and system load
  4. Batch similar work: Group related queries together
  5. Clean up regularly: Close unused tabs and clear old results

Environment Considerations

  1. Development vs Production: Performance may vary between environments
  2. Time zones: Consider Oracle Fusion server time zone for peak usage
  3. Geographic location: Distance from Oracle servers affects latency
  4. Corporate networks: Internal networks may have different performance characteristics

Getting Performance Help

Information to Collect

Before contacting support about performance issues:
  1. Query details: The specific query experiencing issues
  2. Timing information: How long queries take vs. expected time
  3. System information: Your computer specs and network type
  4. Environment details: Which Oracle Fusion environment
  5. Reproducibility: Whether issue is consistent or intermittent

Performance Logs

Enable performance logging:
  1. Open VS Code settings
  2. Search for “Koala performance”
  3. Enable performance monitoring
  4. Reproduce the issue
  5. Collect timing information

Next Steps