SchemaProvider

The SchemaProvider class specifies which Iceberg schema to use when reading from or writing to an Iceberg table. It allows you to select a schema by its current state, by a specific snapshot, or by schema or snapshot ID. This is useful for advanced scenarios such as schema evolution and ensuring a specific schema mapping.

Syntax

SchemaProvider.from_current()
SchemaProvider.from_current_snapshot()
SchemaProvider.from_schema_id(schema_id: int)
SchemaProvider.from_snapshot_id(snapshot_id: int)

Constructors

SchemaProvider.from_current()

Use the current schema from the Iceberg table.
SchemaProvider.from_current_snapshot()

Use the schema from the current snapshot of the Iceberg table.
SchemaProvider.from_schema_id(schema_id: int)

Use the schema with the specified schema ID.
SchemaProvider.from_snapshot_id(snapshot_id: int)

Use the schema from the specified snapshot ID.

Parameters

Parameter	Type	Description
schema_id	int	The unique identifier of the Iceberg schema to use. Only required for `from_schema_id`.
snapshot_id	int	The unique identifier of the Iceberg snapshot to use. Only required for `from_snapshot_id`.

Methods

None.

Examples

The following examples show how to create a SchemaProvider and use it with other Iceberg classes:

from deephaven.experimental import iceberg
from deephaven import dtypes as dht

source_def = {
    "Area": dht.string,
    "Category": dht.string,
    "Price": dht.double,
}

# Use the current schema
default_schema = iceberg.SchemaProvider.from_current()

# Use a specific schema by ID
schema_by_id = iceberg.SchemaProvider.from_schema_id(1)

# Use a schema from a specific snapshot
schema_by_snapshot = iceberg.SchemaProvider.from_snapshot_id(123456789)

# Pass SchemaProvider to an InferenceResolver
resolver = iceberg.InferenceResolver(schema_provider=default_schema)

# Pass SchemaProvider to a TableParquetWriterOptions
writer_options = iceberg.TableParquetWriterOptions(
    table_definition=source_def, schema_provider=schema_by_id
)