Inferred wrong type troubleshooting

Common issues and solutions for ClickHouse inferring wrong data types in Tinybird.

Common issues

String inferred as numeric

Issue: ClickHouse infers string data as numeric type

Solution: Explicitly specify string type in schema

-- Explicitly specify string type
CREATE TABLE events (
  id UInt32,
  user_id String,  -- Explicitly string, not inferred numeric
  value Float64
)

Numeric inferred as string

Issue: ClickHouse infers numeric data as string type

Solution: Explicitly specify numeric type in schema

-- Explicitly specify numeric type
CREATE TABLE events (
  id UInt32,
  user_id UInt32,  -- Explicitly numeric, not inferred string
  value Float64
)

Type inference problems

Mixed data types

Issue: Same column has mixed data types in sample

Solution: Use consistent data types or handle in schema

-- Handle mixed types in schema
CREATE TABLE events (
  id UInt32,
  mixed_field String,  -- Use string to handle mixed types
  value Float64
)

Date format confusion

Issue: ClickHouse infers wrong date format

Solution: Explicitly specify date type and format

-- Explicitly specify date type
CREATE TABLE events (
  id UInt32,
  timestamp DateTime,  -- Explicitly DateTime
  date Date           -- Explicitly Date
)

Schema hints

Using SCHEMA hints

Issue: Need to override type inference

Solution: Use SCHEMA hints in data source

-- Use SCHEMA hints to override inference
SCHEMA >
  id UInt32,
  user_id String,
  timestamp DateTime,
  value Float64

Handling JSON fields

Issue: JSON fields inferred incorrectly

Solution: Use explicit JSON type handling

-- Handle JSON fields explicitly
CREATE TABLE events (
  id UInt32,
  data JSON,  -- Explicitly JSON type
  metadata String  -- Keep as string if needed
)

Debugging type inference

Using toTypeName()

Issue: Need to check what type ClickHouse inferred

Solution: Use toTypeName() function

-- Check inferred types
SELECT
  toTypeName(column_name) as inferred_type,
  column_name
FROM events
LIMIT 1

Checking sample data

Issue: Need to understand why wrong type was inferred

Solution: Examine sample data

-- Examine sample data to understand inference
SELECT
  column_name,
  toTypeName(column_name) as type
FROM events
LIMIT 10

Best practices

  1. Always specify types - Don't rely on type inference
  2. Use SCHEMA hints - Override inference when needed
  3. Check sample data - Understand what data is being ingested
  4. Use toTypeName() - Debug type inference issues
  5. Document expected types - Keep track of expected data types
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