Nullable columns troubleshooting

Common issues and solutions for nullable column performance in ClickHouse and Tinybird.

Common issues

Performance impact of nullable columns

Issue: Nullable columns can significantly impact query performance

Solution: Use nullable columns only when necessary

-- Avoid nullable for frequently filtered columns
-- Instead of: Nullable(String) user_id
-- Use: String user_id with default value

Inefficient nullable operations

Issue: Operations on nullable columns without proper handling

Solution: Handle nulls explicitly in queries

-- Handle nulls explicitly
SELECT 
  CASE 
    WHEN nullable_column IS NULL THEN 'unknown'
    ELSE nullable_column
  END as safe_column
FROM events

Performance optimization

Using COALESCE

Issue: Complex null handling in queries

Solution: Use COALESCE for simple null handling

-- Use COALESCE for null handling
SELECT COALESCE(nullable_column, 'default_value') as safe_column
FROM events

Avoiding nullable in indexes

Issue: Nullable columns in indexes can be inefficient

Solution: Use non-nullable columns for indexes when possible

-- Use non-nullable columns for indexes
-- Instead of indexing nullable_column
-- Index a computed non-nullable column
ALTER TABLE events ADD INDEX idx_safe_column 
  COALESCE(nullable_column, 'default') TYPE minmax GRANULARITY 1

Memory considerations

Memory overhead of nullable columns

Issue: Nullable columns use more memory than non-nullable

Solution: Consider alternatives for large datasets

-- Use default values instead of nullable for large datasets
-- Instead of: Nullable(UInt32) value
-- Use: UInt32 value DEFAULT 0

Storage optimization

Issue: Nullable columns with many null values

Solution: Use sparse columns or separate null tracking

-- Track nulls separately for optimization
SELECT 
  value,
  CASE WHEN value IS NULL THEN 1 ELSE 0 END as is_null
FROM events

Best practices

  1. Use nullable sparingly - Only for truly optional data
  2. Handle nulls explicitly - Use COALESCE and CASE statements
  3. Avoid nullable in indexes - Use non-nullable computed columns
  4. Consider alternatives - Use default values for large datasets
  5. Monitor nullable performance - Track impact on query performance