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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

Query Optimization

Learn to write efficient SQL queries

Connection Issues

Resolve connection and network problems