apache/beam · critical
invalid schema type: %v
Error message
invalid schema type: %v
What it means
mustInferSchema uses the cloud.google.com/go/bigquery InferSchema on a zero value of the element type to derive a BigQuery table schema. If InferSchema cannot map the Go type to BigQuery fields (unsupported field types, nested pointers/maps, unexported or recursive fields), it returns an error and mustInferSchema panics with "invalid schema type: %v", naming the reflect.Type. This is a programming/config error: the type handed to bigqueryio is not schema-inferable.
Source
Thrown at sdks/go/pkg/beam/io/bigqueryio/bigquery.go:229
}
return err
}
emit(reflect.ValueOf(val).Elem().Interface()) // emit(*val)
}
return nil
}
func mustInferSchema(t reflect.Type) bigquery.Schema {
if t.Kind() != reflect.Struct {
panic(fmt.Sprintf("schema type must be struct: %v", t))
}
checkTypeRegistered(t)
schema, err := bigquery.InferSchema(reflect.Zero(t).Interface())
if err != nil {
panic(errors.Wrapf(err, "invalid schema type: %v", t))
}
return schema
}
func checkTypeRegistered(t reflect.Type) {
t = reflectx.SkipPtr(t)
key, ok := runtime.TypeKey(t)
if !ok {
panic(fmt.Sprintf("type %v must be a named type (not anonymous) for registration", t))
}
if _, registered := runtime.LookupType(key); !registered {
panic(fmt.Sprintf("type %v is not registered. Ensure that beam.RegisterType(%v) "+
"is called before beam.Init().", t, t))
}
}
func mustParseTable(table string) QualifiedTableName {View on GitHub (pinned to 12126d8942)
Solutions
- Replace unsupported fields (map, interface, recursive pointers) in the element struct with supported types or a *bigquery.QueryParameterValue-style representation.
- Use bigqueryio.WithSchema (or WithQuerySchema for queries) to supply an explicit bigquery.Schema instead of relying on inference.
- Register the element type with gob (gob.Register) if the failure comes from checkTypeRegistered on an unregistered custom type.
- Test inference locally by calling bigquery.InferSchema(reflect.Zero(t).Interface()) directly to see the underlying unsupported-field error.
Example fix
// before
type row struct {
Tags map[string]string
}
beam.ParDo(s, fn) // bigqueryio.Write panics: invalid schema type
// after
bigqueryio.Write(s, project, dataset, table, []bigqueryio.WithSchema{bigqueryio.WithSchema(bigquery.Schema{
{Name: "Tags", Type: bigquery.StringFieldType, Repeated: true},
})}) Defensive patterns
Strategy: validation
Validate before calling
if _, err := bigquery.InferSchema(reflect.Zero(elemType).Interface()); err != nil {
// fail fast: use bigqueryio.WithSchema(...) with an explicit schema instead
} Prevention
- Keep sink element structs limited to BigQuery-mappable field types (no maps/interfaces/recursive pointers).
- Prefer explicit WithSchema over schema inference in production pipelines.
- gob.Register every custom type used as a PCollection element.
- Add a unit test that infers the schema for each sink element type.
When it happens
Trigger: Calling bigqueryio.Query or bigqueryio.Write with an element type that bigquery.InferSchema rejects: maps, unsupported nested types, interface fields, or a type not registered for gob when required by the pipeline encoding path.
Common situations: Writing rows using ad-hoc structs with fields BigQuery cannot represent; after refactoring a struct to add a map or interface field; passing a named type whose underlying structure has unsupported members; missing gob registration of the element type in distributed execution.
Understand the failure class
Background: Schema validation failed / invalid input schema: payload rejected because its shape doesn't match the expected schema — this error's family across 28 libraries.
Related errors
- Reserved field name <field.name()> in user schema.
- RECORD/STRUCT are not primitive types
- Unknown BigQuery type: " + bqType
- Unknown BigQuery Field Mode: %s
- Unknown Avro type: " + type.getType()
AI-assisted analysis of apache/beam@12126d8942 (2026-09-13).
Data as JSON: /api/errors/16b213e5092b9071.
Report an issue: GitHub.