DuckDB + PySpark (dagster-duckdb-pyspark)¶

This library provides an integration with the DuckDB database and PySpark data processing library.

dagster_duckdb_pyspark.duckdb_pyspark_io_manager IOManagerDefinition¶

Config Schema:

database (dagster.StringSource):

Path to the DuckDB database.

schema (dagster.StringSource, optional):

Name of the schema to use.

An IO manager definition that reads inputs from and writes PySpark DataFrames to DuckDB.

Returns:

IOManagerDefinition

Examples

from dagster_duckdb_pyspark import duckdb_pyspark_io_manager

@asset(
    key_prefix=["my_schema"]  # will be used as the schema in DuckDB
)
def my_table() -> pyspark.sql.DataFrame:  # the name of the asset will be the table name
    ...

@repository
def my_repo():
    return with_resources(
        [my_table],
        {"io_manager": duckdb_pyspark_io_manager.configured({"database": "my_db.duckdb"})}
    )

If you do not provide a schema, Dagster will determine a schema based on the assets and ops using the IO Manager. For assets, the schema will be determined from the asset key. For ops, the schema can be specified by including a “schema” entry in output metadata. If “schema” is not provided via config or on the asset/op, “public” will be used for the schema.

@op(
    out={"my_table": Out(metadata={"schema": "my_schema"})}
)
def make_my_table() -> pyspark.sql.DataFrame:
    # the returned value will be stored at my_schema.my_table
    ...

To only use specific columns of a table as input to a downstream op or asset, add the metadata “columns” to the In or AssetIn.

@asset(
    ins={"my_table": AssetIn("my_table", metadata={"columns": ["a"]})}
)
def my_table_a(my_table: pyspark.sql.DataFrame) -> pyspark.sql.DataFrame:
    # my_table will just contain the data from column "a"
    ...

class dagster_duckdb_pyspark.DuckDBPySparkTypeHandler[source]¶

Stores PySpark DataFrames in DuckDB.

Note: This type handler can only store outputs. It cannot currently load inputs.

To use this type handler, pass it to build_duckdb_io_manager

Example

from dagster_duckdb import build_duckdb_io_manager
from dagster_duckdb_pyspark import DuckDBPySparkTypeHandler

@asset
def my_table():
    ...

duckdb_io_manager = build_duckdb_io_manager([DuckDBPySparkTypeHandler()])

@repository
def my_repo():
    return with_resources(
        [my_table],
        {"io_manager": duckdb_io_manager.configured({"database": "my_db.duckdb"})}
    )