Full Table Scan

SUMMARY

A full table scan is a database operation that reads every row in a table sequentially from start to finish. While simple and reliable, full table scans can be resource-intensive for large tables, making them less efficient than targeted operations using indexes.

Understanding full table scans

A full table scan occurs when a database system needs to examine every row in a table to satisfy a query. This process is analogous to reading every page in a book to find specific information, rather than using an index to jump directly to the relevant pages.

When full table scans occur

Full table scans typically happen in several scenarios:

When no suitable index exists for the query conditions
When the query needs to access a large portion of the table (typically >20-30% of rows)
When the table is small enough that a full scan is more efficient than index usage
When the query planner determines that a full scan is the most cost-effective approach

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Performance implications

The performance impact of full table scans depends heavily on several factors:

Storage considerations

Sequential read performance of the storage system
Whether data fits in memory or requires disk I/O
Page cache efficiency and buffer pool utilization

Data volume factors

Table size and row count
Row width and total data volume
Data compression ratios

# Pseudocode demonstrating full table scan cost
scan_cost = (
    number_of_pages * 
    page_read_cost +
    rows_per_page * 
    row_processing_cost
)

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Optimization strategies

Several techniques can help minimize the impact of full table scans:

Proper indexing strategy

Create indexes for frequently queried columns
Monitor and maintain index usage patterns
Consider columnar storage for analytical workloads

Query optimization

Use partition pruning when possible
Leverage predicate pushdown capabilities
Consider materialized views for frequent queries

System configuration

Optimize buffer pool size
Configure appropriate I/O settings
Use parallel scan capabilities when available

Monitoring and diagnostics

To identify and analyze full table scan operations:

-- ⚠️ ANSI (requires QuestDB adaptation)
EXPLAIN ANALYZE
SELECT *
FROM trades
WHERE timestamp > '2024-01-01'
  AND amount > 1000;

Key metrics to monitor:

Scan duration
Pages read
Buffer cache hit ratio
I/O utilization

This information helps database administrators optimize query performance and decide when to create additional indexes or implement other optimization strategies.

Best practices

Regular analysis

Monitor query patterns
Identify frequent full table scans
Evaluate optimization opportunities

Design considerations

Implement appropriate partitioning strategies
Consider data archival policies
Balance index maintenance costs with query performance

Query development

Write queries that can utilize existing indexes
Consider query patterns during schema design
Use appropriate time-range filters for time-series data