Finding Oracle PGA Memory Hogs with Foglight: A Practical Guide

The Problem: When PGA Memory Goes Wild

Recently, a customer approached us with a common yet challenging issue: “We have many queries consuming a lot of PGA memory. Can Foglight help us find which queries consume the most?”

This question touches on a critical aspect of Oracle performance tuning that many DBAs struggle with daily. Let’s explore how Foglight can help identify and troubleshoot PGA memory issues.

Understanding PGA Memory in Oracle

• PGA (Program Global Area) stores session-specific data:
  • Sort operations
  • Hash joins
  • Bitmap operations
  • Session variables
• High PGA usage can lead to:
  • Increased CPU consumption
  • More disk I/O operations
  • System performance degradation
  • ORA-04030 errors in extreme cases

The Foglight Approach: Indirect but Effective

While Foglight doesn’t directly track PGA memory at the session level, it provides powerful indirect indicators through Performance Investigator (PI).

Key Metrics That Signal PGA Memory Issues

Metrics affected by high PGA usage:
1. CPU Usage - Memory allocation/deallocation overhead
2. User I/O Wait - Memory-to-disk spilling
3. Direct Writes - Temp tablespace usage
4. Disk Reads - Insufficient memory for operations
5. Buffer Gets - Memory operation delays

Step-by-Step: Finding Memory-Hungry Queries

Step 1: Navigate to Performance Investigator

• Open your Oracle instance in Foglight
• Click on Performance Investigator tab

Step 2: Filter by Relevant Wait Categories

• Start with CPU filter - high PGA often manifests as CPU spikes
• Check User I/O filter - indicates memory spilling to disk

Step 3: Analyze the Workload Tree

• Focus on Statements dimension
  • Click Select Metrics to add memory-related columns:
  • Executions (fewer = potential memory waits)
  • Disk Reads (higher = potential memory shortage)
  • Direct Writes (higher = temp space usage)
  • Rows Processed (efficiency indicator)

Step 4: Identify Problematic Statements

Look for statements with:

• High CPU time relative to executions
• Excessive disk reads for the data volume
• High direct writes indicating temp usage
• Poor rows-processed-to-execution ratio

Real-World Example

During the customer investigation, we found:

-- Top CPU consumer (40.62 seconds in last hour):
SELECT * FROM (SELECT t.tablespace_name, t.BLOCK...
-- This query showed signs of memory-intensive operations

-- Memory-heavy aggregation:
SELECT owner, SUM(BYTES)/1024/1024 MB
FROM DBA_EXTENTS
GROUP BY owner
-- High disk reads and direct writes indicated PGA spilling

Monitoring Strategy: Proactive PGA Management

Create Custom Alerts

• Set thresholds for:
• CPU spikes correlated with specific users/programs
• Excessive direct writes to temp
• Disk read patterns indicating memory shortage

Regular Review Points

• Daily: Check top CPU consumers in PI
• Weekly: Review statement efficiency metrics • Monthly: Analyze trends in temp tablespace usage

Oracle-Side Validation

While Foglight provides the performance view, validate findings with:

-- Current PGA usage by session
SELECT
 s.sid || ' - ' || s.username AS session_info,
 ROUND(p.pga_used_mem/1024/1024, 2) AS pga_used_mb,
 ROUND(p.pga_alloc_mem/1024/1024, 2) AS pga_alloc_mb,
 s.sql_id,
 s.event
FROM v$session s
JOIN v$process p ON s.paddr = p.addr
WHERE s.type = 'USER'
ORDER BY p.pga_alloc_mem DESC;

-- Historical PGA usage by SQL
SELECT
 sql_id,
 ROUND(AVG(pga_allocated)/1024/1024, 2) AS avg_pga_mb,
 ROUND(MAX(pga_allocated)/1024/1024, 2) AS max_pga_mb,
 COUNT(*) AS execution_count
FROM v$active_session_history
WHERE pga_allocated > 0
GROUP BY sql_id
ORDER BY max_pga_mb DESC;

Best Practices for PGA Troubleshooting

• Correlate Multiple Metrics: Don’t rely on single indicators
• Time-Based Analysis: Compare peak vs. off-peak patterns
• User/Program Patterns: Identify repeat offenders
• Statement Efficiency: Focus on execution-to-resource ratios

Future Considerations

While the current approach is effective, direct PGA memory tracking at the session level would enhance Foglight’s capabilities. This enhancement request highlights the evolving needs of Oracle performance monitoring.

Conclusion

Foglight’s Performance Investigator provides a comprehensive framework for identifying PGA memory issues through: • CPU and I/O pattern analysis • Statement-level resource consumption tracking • Multi-dimensional performance correlation

By understanding these indirect indicators and following the systematic approach outlined above, DBAs can effectively identify and resolve PGA memory bottlenecks before they impact production systems.

Have you encountered PGA memory challenges in your Oracle environment? Share your experiences and let us know how you’ve leveraged Foglight for performance troubleshooting.