Oracle Memory Performance Tuning: A Complete Guide to SGA & PGA Optimization

Introduction

Memory is one of the most critical resources in an Oracle Database. A well-tuned memory configuration reduces disk I/O, improves SQL execution speed, minimizes parsing overhead, and enhances overall database performance.

Oracle divides its memory into two major components:

  • System Global Area (SGA) – Shared memory used by all database processes.
  • Program Global Area (PGA) – Private memory allocated to each server process.

Improper memory sizing can lead to issues such as ORA-04031, excessive physical reads, high CPU usage, disk-based sorting, poor SQL performance, and increased application response time.

In this guide, we’ll explore Oracle’s memory architecture, explain every SGA and PGA component, discuss common performance issues, and provide practical tuning techniques used in production environments.


Oracle Memory Architecture

Oracle memory is broadly divided into:

                     Oracle Database Memory


                +---------------------------+

                |      Oracle Instance      |

                +---------------------------+

                           |

        -----------------------------------------

        |                                       |

+--------------------+                +--------------------+

|        SGA         |                |        PGA         |

| Shared Memory      |                | Private Memory     |

| Shared by Sessions |                | Per Server Process |

+--------------------+                +--------------------+

SGA (System Global Area)

The SGA is allocated when the Oracle instance starts and is shared among all users and background processes.

Its main goal is to:

  • Cache frequently accessed data
  • Reduce disk I/O
  • Improve SQL execution
  • Store SQL execution plans
  • Manage redo information


PGA (Program Global Area)

The PGA is allocated separately for each server process.

It stores:

  • Session variables
  • Sort operations
  • Hash joins
  • Bitmap merge operations
  • Cursor information

Unlike the SGA, the PGA is not shared.


Components of the SGA

1. Shared Pool

The Shared Pool stores:

  • Parsed SQL statements
  • Execution plans
  • Data Dictionary Cache
  • Library Cache
  • PL/SQL code

Benefits

  • Reduces hard parsing
  • Improves SQL reuse
  • Saves CPU resources

Symptoms of an Undersized Shared Pool

  • ORA-04031
  • High hard parse rate
  • Library cache misses
  • Increased CPU usage

Monitoring

SELECT * FROM V$SGASTAT

WHERE POOL='shared pool';


2. Database Buffer Cache

The Buffer Cache stores recently accessed data blocks in memory.

Instead of reading blocks from disk repeatedly, Oracle retrieves them from the cache.

Benefits

  • Reduces physical reads
  • Improves response time
  • Minimizes disk I/O

Common Problems

  • High physical reads
  • Buffer cache contention
  • Low cache hit ratio

Monitoring

SELECT

physical_reads,

db_block_gets,

consistent_gets

FROM V$SYSSTAT;


3. Redo Log Buffer

Stores redo entries before LGWR writes them to the online redo logs.

Too Small?

May cause:

  • log buffer space waits
  • Increased commit latency

Monitor

SELECT *

FROM V$SYSSTAT

WHERE NAME LIKE '%redo%';


4. Large Pool

Large Pool is optional but highly recommended.

Used for:

  • RMAN backup
  • Shared Server
  • Parallel Query
  • I/O server processes

Benefits:

  • Prevents Shared Pool fragmentation


5. Java Pool

Stores memory for Java execution inside Oracle.

Required only if Java Stored Procedures or JVM features are used.


6. Streams Pool

Used by:

  • Oracle Streams
  • Oracle GoldenGate Integrated Capture
  • Advanced Queuing


Components of the PGA

Unlike the SGA, PGA is allocated per server process.


Sort Area

Used during:

  • ORDER BY
  • GROUP BY
  • DISTINCT

If insufficient:

Oracle performs disk-based sorting.


Hash Area

Used by:

  • Hash Join
  • Hash Aggregation

Insufficient PGA causes temporary tablespace usage.


Bitmap Merge Area

Used during bitmap index processing.


Session Memory

Stores:

  • Session variables
  • PL/SQL variables
  • Runtime information


Cursor Area

Stores execution state of SQL cursors.


Automatic Memory Management (AMM)

Oracle can automatically manage both SGA and PGA.

Parameters:

MEMORY_TARGET

MEMORY_MAX_TARGET

Advantages:

  • Easy administration
  • Dynamic memory allocation
  • Suitable for most environments


Automatic Shared Memory Management (ASMM)

Oracle manages only the SGA automatically.

Parameters:

SGA_TARGET

SGA_MAX_SIZE

PGA_AGGREGATE_TARGET

Preferred in many production systems because it gives DBAs more control over PGA sizing.


Manual Memory Management

Every memory component is configured manually.

Examples:

SHARED_POOL_SIZE

DB_CACHE_SIZE

LARGE_POOL_SIZE

JAVA_POOL_SIZE

LOG_BUFFER

Recommended only for specialized workloads.


Key Dynamic Performance Views

View

Purpose

V$SGA

Displays SGA allocation

V$SGASTAT

SGA component statistics

V$PGASTAT

PGA statistics

V$PROCESS_MEMORY

Process memory usage

V$MEMORY_TARGET_ADVICE

AMM sizing advice

V$SGA_TARGET_ADVICE

SGA sizing advice

V$ACTIVE_SESSION_HISTORY

Memory-related waits

V$SYSSTAT

System statistics


Common Memory Bottlenecks

ORA-04031

Cause

Unable to allocate memory from Shared Pool.

Fix

  • Increase Shared Pool
  • Flush Shared Pool (temporary)
  • Reduce hard parsing
  • Use bind variables


High Physical Reads

Cause

Buffer Cache too small or inefficient SQL.

Fix

  • Tune SQL
  • Add indexes
  • Increase DB_CACHE_SIZE if justified


Excessive Hard Parsing

Cause

Applications not using bind variables.

Fix

  • Use bind variables
  • Increase Shared Pool
  • Enable cursor sharing where appropriate


PGA Spills to Disk

Cause

PGA too small.

Symptoms

  • Temporary tablespace growth
  • Slow hash joins
  • Slow sorts

Fix

Increase:

PGA_AGGREGATE_TARGET


Memory Advisory Views

SGA Advice

SELECT *

FROM V$SGA_TARGET_ADVICE;

Shows estimated performance improvement for different SGA sizes.


PGA Advice

SELECT *

FROM V$PGA_TARGET_ADVICE;

Displays expected cache hit percentages for various PGA sizes.


Useful Monitoring Queries

Current SGA Size

SELECT *

FROM V$SGA;


Shared Pool Usage

SELECT *

FROM V$SGASTAT

WHERE POOL='shared pool';


PGA Statistics

SELECT *

FROM V$PGASTAT;


Process Memory

SELECT *

FROM V$PROCESS_MEMORY;


Buffer Cache Statistics

SELECT

NAME,

VALUE

FROM V$SYSSTAT

WHERE NAME IN

('physical reads',

'db block gets',

'consistent gets');


Performance Tuning Workflow

User reports slow application

            │

            ▼

Collect AWR Report

            │

            ▼

Check Memory Statistics

            │

            ▼

Review Wait Events

            │

            ▼

Analyze SGA & PGA Usage

            │

            ▼

Identify Bottleneck

            │

            ▼

Tune Memory Parameters

            │

            ▼

Validate Performance


Best Practices

  • Use ASMM or AMM unless manual tuning is required.
  • Keep optimizer statistics current before adjusting memory.
  • Monitor AWR and ASH regularly for memory-related waits.
  • Avoid increasing SGA or PGA without evidence from advisory views.
  • Use bind variables to reduce hard parsing.
  • Review V$SGA_TARGET_ADVICE and V$PGA_TARGET_ADVICE before resizing memory.
  • Monitor temporary tablespace usage to detect PGA shortages.
  • Validate changes under production-like workloads.


Real-World Scenario

A financial application experienced slow reporting during month-end processing.

Investigation

  • AWR showed high direct path read temp waits.
  • V$PGASTAT indicated a low PGA cache hit percentage.
  • Large hash joins were spilling to the temporary tablespace.

Resolution

  • Increased PGA_AGGREGATE_TARGET from 8 GB to 16 GB.
  • Optimized SQL joins and updated optimizer statistics.
  • Reviewed execution plans to reduce unnecessary sorting.

Outcome

  • Temporary tablespace usage decreased significantly.
  • Report execution time dropped from 28 minutes to under 6 minutes.
  • CPU utilization became more stable during peak reporting.


Conclusion

Oracle memory tuning is about allocating the right amount of memory to the right components based on workload characteristics, not simply increasing RAM. A properly sized SGA reduces disk I/O and parsing overhead, while an optimized PGA improves sort and join performance by minimizing disk spills.

By regularly monitoring AWR reports, advisory views, dynamic performance views, and wait events, DBAs can make informed tuning decisions that improve database responsiveness, scalability, and overall system stability.

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