Undersized Memory Structures in Oracle: SGA, PGA & Buffer Cache

 

Undersized Memory Structures in Oracle: SGA, PGA & Buffer Cache Issues

Learn how memory misconfiguration like small SGA or PGA causes slowdowns & how to size them correctly.

Introduction

Oracle Database relies heavily on memory structures like the System Global Area (SGA), Program Global Area (PGA), and Buffer Cache to deliver high performance. Misconfiguring these components—often by undersizing them—can lead to slowdowns, excessive disk I/O, and errors like ORA-04031. This blog post explores the impact of undersized memory structures, common issues, step-by-step solutions with example code, real-life scenarios, pros and cons of fixes, and their business implications. Aimed at DBAs and developers, this guide draws from production environments to provide practical, real-world insights for performance tuning.

Understanding Oracle Memory Structures

• System Global Area (SGA): Shared memory for database instance, holding Buffer Cache, Shared Pool, Redo Log Buffer, etc.

• Program Global Area (PGA): Private memory per session for sorting, hashing, and query execution.

• Buffer Cache: Part of SGA, caches data blocks to reduce disk I/O.

Undersizing these leads to performance bottlenecks, increased I/O, and application delays, impacting user experience and business operations.

Common Issues from Undersized Memory Structures

1. Small SGA

• Symptoms: Frequent disk reads/writes, high wait times (e.g., db file sequential read), ORA-04031 errors.

• Causes: Low SGA_TARGET or MEMORY_TARGET, insufficient Shared Pool or Buffer Cache.

• Impact: Slow query response, especially for OLTP systems with many concurrent users.

2. Small PGA

• Symptoms: Excessive disk-based sorts (sorts (disk) in V$SYSSTAT), slow joins, high workarea executions - onepass/multipass.

• Causes: Low PGA_AGGREGATE_TARGET, too many sessions exhausting PGA.

• Impact: Degraded performance in data warehouse queries or large reports.

3. Small Buffer Cache

• Symptoms: High physical reads in AWR reports, low cache hit ratio (<90%).

• Causes: Undersized DB_CACHE_SIZE or insufficient SGA allocation.

• Impact: Increased I/O, slowing down read-heavy applications like reporting systems.

Step-by-Step Solutions

Diagnosing Memory Issues

1. Check SGA Usage:

   • Query V$SGASTAT to see current allocations.

     SELECT POOL, NAME, BYTES/1024/1024 AS MB FROM V$SGASTAT ORDER BY POOL, NAME;

   • Look for high free memory (underutilized) or ORA-04031 errors (overloaded).

2. Monitor Buffer Cache Hit Ratio:

   • Calculate hit ratio to assess efficiency.

     SELECT NAME, VALUE FROM V$SYSSTAT WHERE NAME IN ('physical reads cache', 'consistent gets', 'db block gets');

     Formula: Hit Ratio = (consistent gets + db block gets - physical reads cache) / (consistent gets + db block gets) * 100. Aim for >90%.

3. Check PGA Usage:

   • Query V$PGASTAT for aggregate usage and sorts.

     SELECT NAME, VALUE/1024/1024 AS MB FROM V$PGASTAT WHERE NAME LIKE '%aggregate%';
     SELECT * FROM V$SYSSTAT WHERE NAME LIKE 'sorts%';

4. Use AWR Reports:

   • Generate an AWR report to identify memory-related waits.

     EXEC DBMS_WORKLOAD_REPOSITORY.CREATE_SNAPSHOT;
     SELECT * FROM DBA_HIST_AWR_RPT;

Fixing Undersized SGA

1. Enable Automatic Memory Management (AMM):

   • Set MEMORY_TARGET to let Oracle dynamically allocate SGA and PGA.

     ALTER SYSTEM SET MEMORY_TARGET = 4G SCOPE=SPFILE;
     ALTER SYSTEM SET SGA_TARGET = 0 SCOPE=SPFILE;
     ALTER SYSTEM SET PGA_AGGREGATE_TARGET = 0 SCOPE=SPFILE;

     Restart instance: SHUTDOWN IMMEDIATE; STARTUP;

2. Manually Increase SGA:

   • If AMM is disabled, adjust SGA_TARGET or individual pools.

     ALTER SYSTEM SET SGA_TARGET = 3G SCOPE=SPFILE;
     ALTER SYSTEM SET SHARED_POOL_SIZE = 512M SCOPE=SPFILE;

     Restart required.

3. Pin Frequently Used Objects:

   • Reduce Shared Pool fragmentation.

     EXEC DBMS_SHARED_POOL.KEEP('HR.PKG_EMPLOYEE', 'P');

Fixing Undersized PGA

1. Increase PGA_AGGREGATE_TARGET:

   • Adjust based on session count and workload.

     ALTER SYSTEM SET PGA_AGGREGATE_TARGET = 1G SCOPE=SPFILE;

2. Optimize Work Areas:

   • Set WORKAREA_SIZE_POLICY to AUTO and monitor V$SQL_WORKAREA.

     SELECT SQL_ID, OPERATION_TYPE, POLICY, ESTIMATED_OPTIMAL_SIZE/1024/1024 AS MB
     FROM V$SQL_WORKAREA WHERE LAST_EXECUTION = 'MULTI-PASS';

3. Limit Session PGA Usage:

   • Use resource manager to cap per-session PGA.

     BEGIN
       DBMS_RESOURCE_MANAGER.CREATE_PLAN_DIRECTIVE(
         PLAN => 'DAYTIME_PLAN',
         GROUP_OR_SUBPLAN => 'LOW_GROUP',
         MAX_PER_PGA => 100000000  -- 100MB
       );
     END;

Fixing Undersized Buffer Cache

1. Increase DB_CACHE_SIZE:

   • Manually adjust if not using AMM.

     ALTER SYSTEM SET DB_CACHE_SIZE = 1G SCOPE=SPFILE;

2. Add Additional Buffer Pools:

   • Use KEEP or RECYCLE pools for specific workloads.

     ALTER TABLE HR.EMPLOYEES STORAGE (BUFFER_POOL KEEP);

3. Monitor Cache Efficiency:

   • Query V$BH to check block usage.

     SELECT OBJD, COUNT(*) AS BLOCKS FROM V$BH GROUP BY OBJD ORDER BY BLOCKS DESC;

Real-Life Scenarios

• SGA Issue: In a retail banking system, an undersized SGA caused slow transaction processing during peak hours, with AWR showing high db file sequential read waits. Increasing SGA_TARGET to 4G and pinning key packages resolved it.

• PGA Issue: A data warehouse running nightly ETL jobs hit ORA-04036 (PGA limit exceeded) due to large sorts spilling to disk. Doubling PGA_AGGREGATE_TARGET and optimizing queries with parallel hints cut runtime by 40%.

• Buffer Cache Issue: An e-commerce platform saw slow product searches due to a low cache hit ratio (70%). Adding a KEEP pool for product tables and increasing DB_CACHE_SIZE to 2G boosted performance.

Pros and Cons of Solutions

• SGA Fixes:

  • Pros: AMM simplifies tuning, reducing manual effort. Pinning objects improves parse efficiency.

  • Cons: Large SGA demands more RAM, increasing costs. Restart needed for SPFILE changes.

• PGA Fixes:

  • Pros: Higher PGA reduces disk sorts, speeding up queries. Resource Manager prevents runaway sessions.

  • Cons: Over-allocating PGA can starve SGA, balancing is critical. Requires workload analysis.

• Buffer Cache Fixes:

  • Pros: KEEP pools optimize for hot tables. Higher cache size cuts I/O.

  • Cons: Misallocating to KEEP pool can waste memory. Hardware upgrades may be needed.

Usage in Real Life and Business

• Retail: Undersized SGA in an order management system can delay checkout processes, leading to cart abandonment and revenue loss. AMM and regular AWR analysis ensure smooth peak-time performance.

• Finance: PGA issues in reporting databases can delay critical financial close processes, risking regulatory penalties. Businesses use resource manager and automated scripts to adjust PGA dynamically.

• Healthcare: Low Buffer Cache hit ratios in patient record systems slow down queries, impacting care delivery. DBAs use KEEP pools for frequently accessed tables, maintaining sub-second response times.

Best Practices

1. Use AMM for Simplicity: Set MEMORY_TARGET for dynamic allocation unless fine-tuned control is needed.

2. Monitor Regularly: Use AWR, V$SGASTAT, and V$PGASTAT to catch issues early.

3. Test Changes: Apply in dev environments first, using tools like SQL Performance Analyzer.

4. Balance Memory: Ensure SGA and PGA are sized based on workload (OLTP vs. DSS).

5. Automate Tuning: Leverage Oracle Enterprise Manager or scripts for proactive adjustments.

Conclusion

Undersized SGA, PGA, or Buffer Cache can cripple Oracle Database performance, but with proper diagnosis and tuning, you can eliminate bottlenecks. By using provided queries, enabling AMM, and applying workload-specific fixes, DBAs can ensure optimal performance. In business contexts, these solutions translate to faster transactions, reliable reporting, and happy stakeholders. Regular monitoring and capacity planning are key to staying ahead of memory issues in production.

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