This dialect allows you to use Kysely with DuckDB. Please see following instructions and API Reference.
$ npm install --save kysely duckdb kysely-duckdb
import * as duckdb from "duckdb";
import { Kysely } from "kysely";
import { DuckDbDialect } from "kysely-duckdb"
const db = new duckdb.Database(":memory:");
const duckdbDialect = new DuckDbDialect({
database: db,
tableMappings: {
person:
`read_json('./person.json', columns={"first_name": "STRING", "gender": "STRING", "last_name": "STRING"})`,
},
});
const kysely = new Kysely<DatabaseSchema>({ dialect: duckdbDialect });
const res = await kysely.selectFrom("person").selectAll().execute();
The configuration object of DuckDbDialect
can contain the following properties:
database
: A duckdb.Database
instance or a function that returns a Promise
of a duckdb.Database
instance.tableMappings
: A mapping of table names in Kysely to DuckDB table expressions. This is useful if you want to use DuckDB's external data sources, such as JSON files or CSV files.DuckDB supports various data types like arrays, structs, blobs and more. Kysely has not built in supports for these types, but it can handle almost of these using raw SQL feature.
This package includes some shallow helper for these types.
import type { DuckDBNodeDataTypes } from "kysely-duckdb";
import { datatypes } from "kysely-dockdb";
// DuckDBNodeDataTypes: type mappings for table schema
export interface Database {
t1: {
int_list: number[];
string_list: string[];
map1: DuckDBNodeDataTypes["MAP"]; // `map` is alias of string now. The returned value from duckdb is like '{a=1,b=2}'
struct1: {
x: number;
y: string;
};
bitstring1: DuckDBNodeDataTypes["BIT"];
blob1: DuckDBNodeDataTypes["BLOB"];
bool1: DuckDBNodeDataTypes["BOOLEAN"];
date1: DuckDBNodeDataTypes["DATE"];
timestamp1: DuckDBNodeDataTypes["TIMESTAMP"];
timestamptz1: DuckDBNodeDataTypes["TIMESTAMPTZ"];
interval1: DuckDBNodeDataTypes["INTERVAL"];
};
}
...
// datatypes: type constructors
const kysely = new Kysely<Database>({dialect: duckDbDialect});
await kysely
.insertInto("t1")
.values([{
int_list: datatypes.list([3, 4, 5]),
string_list: datatypes.list(["d", "e", "f"]),
map1: types.map([[1, 2], [3, 4]]),
struct1: datatypes.struct({
x: sql`${1}`,
y: sql`${"aaa"}`,
}),
bitstring1: datatypes.bit("010101"),
blob1: datatypes.blob(Buffer.from([0xBB, 0xCC])),
bool1: true,
date1: datatypes.date(new Date()),
timestamp1: datatypes.timestamp(new Date()),
timestamptz1: datatypes.timestamptz(new Date().toISOString().slice(0, -1) + "+03:00"),
interval1: sql`INTERVAL 1 YEAR`,
}])
.execute();