Block Cloning Detection (vclone.sql)

Use at Your Own Risk

This script is for educational purposes only. Always test in development environments before production use. See our disclaimer for full terms.

What This Script Does

This script detects potential block cloning in the database buffer cache by identifying blocks that appear multiple times. Block cloning occurs when the same database block (identified by file# and block#) exists in multiple buffer cache slots, which should normally not happen. The script queries V$BH (Buffer Header) to find blocks appearing more than 10 times, indicating possible buffer cache management issues, corruption, or abnormal caching behavior.

The Script

rem  vclone.sql
rem
ttitle 'Block Cloning'
rem
col file# format 9999 heading 'FILE|ID'
col block# format 999999 heading 'BLOCK|ID'
col block_count format 999999 heading 'BLOCK|COUNT'
rem
break on report
compute sum of block_count on report
rem
select file#, block#, count(*) block_count
  from v$bh
 group by file#, block#
having count(*) > 10;

Key Features

• Buffer Cache Analysis: Examines buffer cache contents for anomalies
• Clone Detection: Identifies blocks appearing multiple times in cache
• Threshold Filtering: Shows only blocks with significant duplication (>10 occurrences)
• File and Block Identification: Pinpoints exact location of problematic blocks
• Statistical Summary: Provides total count of cloned blocks
• Performance Impact Assessment: Helps identify cache inefficiencies

Usage

@vclone.sql

No parameters required - analyzes current buffer cache contents.

Required Privileges

SELECT on V$BH

Sample Output

                                              Block Cloning

 FILE    BLOCK   BLOCK
   ID       ID   COUNT
----- -------- -------
    5   123456      15
    7   234567      12
    8   345678      18
   12   456789      11
   15   567890      14
                -------
sum                 70

Key Output Columns

• FILE ID: Database file number containing the cloned block
• BLOCK ID: Block number within the file that is cloned
• BLOCK COUNT: Number of times this block appears in the buffer cache
• sum: Total number of cloned block instances

Understanding Block Cloning

Normal Buffer Cache Behavior

Expected Behavior

-- Normal buffer cache operation:
-- Each unique block (file#, block#) should appear once
-- Multiple sessions can access the same cached block
-- Block sharing is managed through buffer headers
-- No physical duplication should occur

Buffer Cache Structure

-- Buffer cache components:
-- Buffer headers (v$bh entries)
-- Data blocks in memory
-- Hash chains for block lookup
-- LRU (Least Recently Used) chains

Abnormal Cloning Scenarios

Potential Causes

-- Block cloning may indicate:
-- Buffer cache corruption
-- Hash chain inconsistencies
-- Memory management issues
-- Instance recovery problems
-- RAC cache fusion issues

Impact Assessment

-- Performance implications:
-- Wasted buffer cache memory
-- Inconsistent data access
-- Potential data corruption
-- Cache lookup inefficiencies

Common Use Cases

1. Buffer Cache Health Check

   • Verify buffer cache integrity
   • Detect memory management issues
   • Identify potential corruption
   • Monitor cache efficiency

2. Performance Troubleshooting

   • Diagnose cache-related performance issues
   • Investigate memory utilization problems
   • Analyze unusual buffer cache behavior
   • Support query performance optimization

3. System Integrity Monitoring

   • Detect potential data corruption
   • Monitor system stability
   • Identify hardware-related issues
   • Support preventive maintenance

4. RAC Environment Analysis

   • Monitor cluster cache coordination
   • Detect inter-instance issues
   • Analyze cache fusion efficiency
   • Support cluster optimization

Advanced Analysis

Block Source Analysis

File Type Identification

-- Identify affected file types:
-- System tablespace files
-- User tablespace files
-- Temporary files
-- Undo tablespace files
-- Index vs. table blocks

Object Correlation

-- Correlate with database objects:
SELECT
  dba_extents.owner,
  dba_extents.segment_name,
  dba_extents.segment_type,
  clones.file_id,
  clones.block_id,
  clones.block_count
FROM
  (SELECT file#, block#, count(*) as block_count
   FROM v$bh
   GROUP BY file#, block#
   HAVING count(*) > 10) clones,
  dba_extents
WHERE
  dba_extents.file_id = clones.file_id
  AND clones.block_id BETWEEN dba_extents.block_id
      AND dba_extents.block_id + dba_extents.blocks - 1;

Memory Impact Assessment

Cache Waste Calculation

-- Calculate wasted cache memory:
-- Total cloned blocks * DB_BLOCK_SIZE
-- Percentage of buffer cache affected
-- Impact on cache hit ratio
-- Memory allocation efficiency

Performance Impact

-- Assess performance implications:
-- Cache lookup overhead
-- Memory access patterns
-- I/O efficiency degradation
-- Application response impact

Troubleshooting Applications

Investigation Steps

Initial Assessment

-- First investigation steps:
-- Document cloning extent and patterns
-- Identify affected database objects
-- Check for recent system changes
-- Review error logs for anomalies

Root Cause Analysis

-- Investigate potential causes:
-- Recent instance crashes or restarts
-- Hardware memory issues
-- Database corruption indicators
-- RAC interconnect problems

Resolution Strategies

Immediate Actions

-- Immediate response options:
-- Monitor system stability
-- Check database consistency
-- Perform buffer cache flush if necessary
-- Alert appropriate support teams

Long-term Solutions

-- Long-term resolution:
-- Hardware diagnostics
-- Database consistency checks
-- System configuration review
-- Preventive maintenance planning

Diagnostic Correlation

System Health Checks

Memory Subsystem

-- Memory system validation:
-- Check for hardware memory errors
-- Validate memory configuration
-- Monitor memory utilization patterns
-- Review system error logs

Database Consistency

-- Database integrity checks:
-- Run DBVERIFY on affected files
-- Perform block corruption checks
-- Validate data dictionary consistency
-- Check for logical corruption

Performance Correlation

Cache Efficiency Metrics

-- Monitor cache performance:
-- Buffer cache hit ratio
-- Physical I/O patterns
-- Cache aging statistics
-- Memory allocation efficiency

Query Performance Impact

-- Assess query impact:
-- Response time degradation
-- Execution plan changes
-- Resource utilization patterns
-- User experience metrics

RAC-Specific Considerations

Cluster Cache Management

Inter-Instance Coordination

-- RAC cache considerations:
-- Global cache coordination
-- Cache fusion operations
-- Inter-instance messaging
-- Cluster resource allocation

RAC-Specific Diagnostics

-- RAC diagnostic queries:
-- Check GV$BH across all instances
-- Monitor global cache events
-- Analyze interconnect statistics
-- Review cluster cache efficiency

Global Cache Analysis

-- Global cache validation:
SELECT
  inst_id,
  file#,
  block#,
  count(*) as clone_count
FROM gv$bh
GROUP BY inst_id, file#, block#
HAVING count(*) > 10
ORDER BY inst_id, clone_count DESC;

Preventive Measures

Monitoring Integration

Automated Detection

-- Implement automated monitoring:
-- Schedule regular clone detection
-- Set up alerting thresholds
-- Monitor trends over time
-- Integrate with health checks

Baseline Establishment

-- Establish performance baselines:
-- Normal buffer cache behavior
-- Expected block distribution
-- Cache efficiency metrics
-- System stability indicators

System Maintenance

Regular Health Checks

-- Include in routine maintenance:
-- Buffer cache analysis
-- Memory subsystem validation
-- Database consistency checks
-- Performance metric reviews

Proactive Monitoring

-- Proactive system monitoring:
-- Hardware health checks
-- Memory error detection
-- Database integrity validation
-- Performance trend analysis

Advanced Modifications

Detailed Analysis

-- Enhanced clone detection:
SELECT
  file#,
  block#,
  count(*) as clone_count,
  min(ts#) as tablespace_id,
  min(obj) as object_id,
  min(status) as block_status,
  count(distinct status) as status_variety
FROM v$bh
GROUP BY file#, block#
HAVING count(*) > 5
ORDER BY clone_count DESC;

Threshold Adjustment

-- Adjustable threshold version:
SELECT
  file#,
  block#,
  count(*) block_count
FROM v$bh
GROUP BY file#, block#
HAVING count(*) > &threshold
ORDER BY count(*) DESC;

Object Identification

-- Include object details:
SELECT
  f.file#,
  f.name as filename,
  c.block#,
  c.block_count,
  o.owner,
  o.object_name,
  o.object_type
FROM
  (SELECT file#, block#, count(*) as block_count
   FROM v$bh
   GROUP BY file#, block#
   HAVING count(*) > 10) c,
  v$datafile f,
  dba_objects o,
  dba_extents e
WHERE c.file# = f.file#
  AND e.file_id = c.file#
  AND c.block# BETWEEN e.block_id AND e.block_id + e.blocks - 1
  AND o.object_id = e.segment_object_id;

Best Practices

Regular Monitoring

-- Establish monitoring routine:
-- Daily during critical periods
-- Weekly during normal operations
-- After system changes or upgrades
-- During performance troubleshooting

Documentation

-- Maintain documentation:
-- Baseline cloning patterns
-- Investigation procedures
-- Resolution actions taken
-- Trend analysis results

Escalation Procedures

-- Define escalation criteria:
-- Number of cloned blocks threshold
-- Performance impact severity
-- System stability concerns
-- Data integrity risks

Related Scripts

• vbhstat.sql - Buffer header statistics
• vbpcache.sql - Buffer pool cache analysis
• show_sga.sql - SGA memory analysis
• vsgastat.sql - SGA statistics

Summary

This script is essential for:

1. Buffer Cache Health - Detecting anomalies in buffer cache management
2. System Integrity - Identifying potential memory or corruption issues
3. Performance Optimization - Ensuring efficient buffer cache utilization
4. Proactive Monitoring - Preventing data integrity and performance problems
5. Troubleshooting Support - Providing diagnostic information for system issues