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

Nullable columns cannot be sorting keys

Issue: Nullable columns cannot be used in sorting keys (ENGINE_SORTING_KEY), limiting query optimization

Solution: Use COALESCE to create non-nullable columns for sorting keys

-- Data Source schema: use COALESCE for sorting key
SCHEMA >
  `id` Int64,
  `nullable_status` Nullable(String),
  `status` String DEFAULT COALESCE(nullable_status, 'unknown'),
  `date` DateTime

ENGINE "MergeTree"
ENGINE_SORTING_KEY "status, date"

This allows you to use the column in the sorting key while preserving the nullable information in the original column.

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. Nullable columns can't be sorting keys - Use COALESCE to create non-nullable columns for sorting keys
  3. Handle nulls explicitly - Use COALESCE and CASE statements
  4. Consider alternatives - Use default values instead of nullable for large datasets
  5. Nullable columns are bigger and slower - They use more memory and storage than non-nullable columns
  6. Monitor nullable performance - Track impact on query performance
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