published on Wednesday, Sep 9, 2026 by DataRobot, Inc.
published on Wednesday, Sep 9, 2026 by DataRobot, Inc.
Data source
Example Usage
import * as pulumi from "@pulumi/pulumi";
import * as datarobot from "@datarobot/pulumi-datarobot";
const exampleDatabase = new datarobot.Datastore("example_database", {
canonicalName: "Example Database Datastore",
dataStoreType: "dr-database-v1",
driverId: "64a288a50636598d75df7f82",
fields: [{
id: "bq.project_id",
name: "Project Id",
value: "project-id",
}],
});
const exampleConnector = new datarobot.Datastore("example_connector", {
canonicalName: "Example Connector Datastore",
dataStoreType: "dr-connector-v1",
connectorId: "65538041dde6a1d664d0b2ec",
fields: [{
id: "fs.defaultFS",
name: "Bucket Name",
value: "my-bucket",
}],
});
const exampleDatabaseTable = new datarobot.Datasource("example_database_table", {
canonicalName: "Example Database Table Data Source",
dataSourceType: "dr-database-v1",
params: {
dataStoreId: exampleDatabase.id,
catalog: "my-catalog",
schema: "my-schema",
table: "my-table",
},
});
const exampleDatabaseQuery = new datarobot.Datasource("example_database_query", {
canonicalName: "Example Database Query Data Source",
dataSourceType: "dr-database-v1",
params: {
dataStoreId: exampleDatabase.id,
query: "SELECT * FROM my-table",
},
});
const exampleConnectorDatasource = new datarobot.Datasource("example_connector", {
canonicalName: "Example Connector Data Source",
dataSourceType: "dr-connector-v1",
params: {
dataStoreId: exampleConnector.id,
path: "/my-folder/my-file.csv",
},
});
export const exampleId = exampleDatabaseTable.id;
import pulumi
import pulumi_datarobot as datarobot
example_database = datarobot.Datastore("example_database",
canonical_name="Example Database Datastore",
data_store_type="dr-database-v1",
driver_id="64a288a50636598d75df7f82",
fields=[{
"id": "bq.project_id",
"name": "Project Id",
"value": "project-id",
}])
example_connector = datarobot.Datastore("example_connector",
canonical_name="Example Connector Datastore",
data_store_type="dr-connector-v1",
connector_id="65538041dde6a1d664d0b2ec",
fields=[{
"id": "fs.defaultFS",
"name": "Bucket Name",
"value": "my-bucket",
}])
example_database_table = datarobot.Datasource("example_database_table",
canonical_name="Example Database Table Data Source",
data_source_type="dr-database-v1",
params={
"data_store_id": example_database.id,
"catalog": "my-catalog",
"schema": "my-schema",
"table": "my-table",
})
example_database_query = datarobot.Datasource("example_database_query",
canonical_name="Example Database Query Data Source",
data_source_type="dr-database-v1",
params={
"data_store_id": example_database.id,
"query": "SELECT * FROM my-table",
})
example_connector_datasource = datarobot.Datasource("example_connector",
canonical_name="Example Connector Data Source",
data_source_type="dr-connector-v1",
params={
"data_store_id": example_connector.id,
"path": "/my-folder/my-file.csv",
})
pulumi.export("exampleId", example_database_table.id)
package main
import (
"github.com/datarobot-community/pulumi-datarobot/sdk/go/datarobot"
"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)
func main() {
pulumi.Run(func(ctx *pulumi.Context) error {
exampleDatabase, err := datarobot.NewDatastore(ctx, "example_database", &datarobot.DatastoreArgs{
CanonicalName: pulumi.String("Example Database Datastore"),
DataStoreType: pulumi.String("dr-database-v1"),
DriverId: pulumi.String("64a288a50636598d75df7f82"),
Fields: pulumi.StringMapArray{
pulumi.StringMap{
"id": pulumi.String("bq.project_id"),
"name": pulumi.String("Project Id"),
"value": pulumi.String("project-id"),
},
},
})
if err != nil {
return err
}
exampleConnector, err := datarobot.NewDatastore(ctx, "example_connector", &datarobot.DatastoreArgs{
CanonicalName: pulumi.String("Example Connector Datastore"),
DataStoreType: pulumi.String("dr-connector-v1"),
ConnectorId: pulumi.String("65538041dde6a1d664d0b2ec"),
Fields: pulumi.StringMapArray{
pulumi.StringMap{
"id": pulumi.String("fs.defaultFS"),
"name": pulumi.String("Bucket Name"),
"value": pulumi.String("my-bucket"),
},
},
})
if err != nil {
return err
}
exampleDatabaseTable, err := datarobot.NewDatasource(ctx, "example_database_table", &datarobot.DatasourceArgs{
CanonicalName: pulumi.String("Example Database Table Data Source"),
DataSourceType: pulumi.String("dr-database-v1"),
Params: &datarobot.DatasourceParamsArgs{
DataStoreId: exampleDatabase.ID().ToIDOutput().ToStringOutput(),
Catalog: pulumi.String("my-catalog"),
Schema: pulumi.String("my-schema"),
Table: pulumi.String("my-table"),
},
})
if err != nil {
return err
}
_, err = datarobot.NewDatasource(ctx, "example_database_query", &datarobot.DatasourceArgs{
CanonicalName: pulumi.String("Example Database Query Data Source"),
DataSourceType: pulumi.String("dr-database-v1"),
Params: &datarobot.DatasourceParamsArgs{
DataStoreId: exampleDatabase.ID().ToIDOutput().ToStringOutput(),
Query: pulumi.String("SELECT * FROM my-table"),
},
})
if err != nil {
return err
}
_, err = datarobot.NewDatasource(ctx, "example_connector", &datarobot.DatasourceArgs{
CanonicalName: pulumi.String("Example Connector Data Source"),
DataSourceType: pulumi.String("dr-connector-v1"),
Params: &datarobot.DatasourceParamsArgs{
DataStoreId: exampleConnector.ID().ToIDOutput().ToStringOutput(),
Path: pulumi.String("/my-folder/my-file.csv"),
},
})
if err != nil {
return err
}
ctx.Export("exampleId", exampleDatabaseTable.ID())
return nil
})
}
using System.Collections.Generic;
using System.Linq;
using Pulumi;
using Datarobot = DataRobotPulumi.Datarobot;
return await Deployment.RunAsync(() =>
{
var exampleDatabase = new Datarobot.Datastore("example_database", new()
{
CanonicalName = "Example Database Datastore",
DataStoreType = "dr-database-v1",
DriverId = "64a288a50636598d75df7f82",
Fields = new[]
{
{
{ "id", "bq.project_id" },
{ "name", "Project Id" },
{ "value", "project-id" },
},
},
});
var exampleConnector = new Datarobot.Datastore("example_connector", new()
{
CanonicalName = "Example Connector Datastore",
DataStoreType = "dr-connector-v1",
ConnectorId = "65538041dde6a1d664d0b2ec",
Fields = new[]
{
{
{ "id", "fs.defaultFS" },
{ "name", "Bucket Name" },
{ "value", "my-bucket" },
},
},
});
var exampleDatabaseTable = new Datarobot.Datasource("example_database_table", new()
{
CanonicalName = "Example Database Table Data Source",
DataSourceType = "dr-database-v1",
Params = new Datarobot.Inputs.DatasourceParamsArgs
{
DataStoreId = exampleDatabase.Id,
Catalog = "my-catalog",
Schema = "my-schema",
Table = "my-table",
},
});
var exampleDatabaseQuery = new Datarobot.Datasource("example_database_query", new()
{
CanonicalName = "Example Database Query Data Source",
DataSourceType = "dr-database-v1",
Params = new Datarobot.Inputs.DatasourceParamsArgs
{
DataStoreId = exampleDatabase.Id,
Query = "SELECT * FROM my-table",
},
});
var exampleConnectorDatasource = new Datarobot.Datasource("example_connector", new()
{
CanonicalName = "Example Connector Data Source",
DataSourceType = "dr-connector-v1",
Params = new Datarobot.Inputs.DatasourceParamsArgs
{
DataStoreId = exampleConnector.Id,
Path = "/my-folder/my-file.csv",
},
});
return new Dictionary<string, object?>
{
["exampleId"] = exampleDatabaseTable.Id,
};
});
package generated_program;
import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.datarobot.Datastore;
import com.pulumi.datarobot.DatastoreArgs;
import com.pulumi.datarobot.Datasource;
import com.pulumi.datarobot.DatasourceArgs;
import com.pulumi.datarobot.inputs.DatasourceParamsArgs;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.Map;
import java.io.File;
import java.nio.file.Files;
import java.nio.file.Paths;
public class App {
public static void main(String[] args) {
Pulumi.run(App::stack);
}
public static void stack(Context ctx) {
var exampleDatabase = new Datastore("exampleDatabase", DatastoreArgs.builder()
.canonicalName("Example Database Datastore")
.dataStoreType("dr-database-v1")
.driverId("64a288a50636598d75df7f82")
.fields(Map.ofEntries(
Map.entry("id", "bq.project_id"),
Map.entry("name", "Project Id"),
Map.entry("value", "project-id")
))
.build());
var exampleConnector = new Datastore("exampleConnector", DatastoreArgs.builder()
.canonicalName("Example Connector Datastore")
.dataStoreType("dr-connector-v1")
.connectorId("65538041dde6a1d664d0b2ec")
.fields(Map.ofEntries(
Map.entry("id", "fs.defaultFS"),
Map.entry("name", "Bucket Name"),
Map.entry("value", "my-bucket")
))
.build());
var exampleDatabaseTable = new Datasource("exampleDatabaseTable", DatasourceArgs.builder()
.canonicalName("Example Database Table Data Source")
.dataSourceType("dr-database-v1")
.params(DatasourceParamsArgs.builder()
.dataStoreId(exampleDatabase.id())
.catalog("my-catalog")
.schema("my-schema")
.table("my-table")
.build())
.build());
var exampleDatabaseQuery = new Datasource("exampleDatabaseQuery", DatasourceArgs.builder()
.canonicalName("Example Database Query Data Source")
.dataSourceType("dr-database-v1")
.params(DatasourceParamsArgs.builder()
.dataStoreId(exampleDatabase.id())
.query("SELECT * FROM my-table")
.build())
.build());
var exampleConnectorDatasource = new Datasource("exampleConnectorDatasource", DatasourceArgs.builder()
.canonicalName("Example Connector Data Source")
.dataSourceType("dr-connector-v1")
.params(DatasourceParamsArgs.builder()
.dataStoreId(exampleConnector.id())
.path("/my-folder/my-file.csv")
.build())
.build());
ctx.export("exampleId", exampleDatabaseTable.id());
}
}
resources:
exampleDatabase:
type: datarobot:Datastore
name: example_database
properties:
canonicalName: Example Database Datastore
dataStoreType: dr-database-v1
driverId: 64a288a50636598d75df7f82
fields:
- id: bq.project_id
name: Project Id
value: project-id
exampleConnector:
type: datarobot:Datastore
name: example_connector
properties:
canonicalName: Example Connector Datastore
dataStoreType: dr-connector-v1
connectorId: 65538041dde6a1d664d0b2ec
fields:
- id: fs.defaultFS
name: Bucket Name
value: my-bucket
exampleDatabaseTable:
type: datarobot:Datasource
name: example_database_table
properties:
canonicalName: Example Database Table Data Source
dataSourceType: dr-database-v1
params:
dataStoreId: ${exampleDatabase.id}
catalog: my-catalog
schema: my-schema
table: my-table
exampleDatabaseQuery:
type: datarobot:Datasource
name: example_database_query
properties:
canonicalName: Example Database Query Data Source
dataSourceType: dr-database-v1
params:
dataStoreId: ${exampleDatabase.id}
query: SELECT * FROM my-table
exampleConnectorDatasource:
type: datarobot:Datasource
name: example_connector
properties:
canonicalName: Example Connector Data Source
dataSourceType: dr-connector-v1
params:
dataStoreId: ${exampleConnector.id}
path: /my-folder/my-file.csv
outputs:
exampleId: ${exampleDatabaseTable.id}
pulumi {
required_providers {
datarobot = {
source = "pulumi/datarobot"
}
}
}
resource "datarobot_datastore" "example_database" {
canonical_name = "Example Database Datastore"
data_store_type = "dr-database-v1"
driver_id = "64a288a50636598d75df7f82"
fields = [{
"id" = "bq.project_id"
"name" = "Project Id"
"value" = "project-id"
}]
}
resource "datarobot_datastore" "example_connector" {
canonical_name = "Example Connector Datastore"
data_store_type = "dr-connector-v1"
connector_id = "65538041dde6a1d664d0b2ec"
fields = [{
"id" = "fs.defaultFS"
"name" = "Bucket Name"
"value" = "my-bucket"
}]
}
resource "datarobot_datasource" "example_database_table" {
canonical_name = "Example Database Table Data Source"
data_source_type = "dr-database-v1"
params = {
data_store_id = datarobot_datastore.example_database.id
catalog = "my-catalog"
schema = "my-schema"
table = "my-table"
}
}
resource "datarobot_datasource" "example_database_query" {
canonical_name = "Example Database Query Data Source"
data_source_type = "dr-database-v1"
params = {
data_store_id = datarobot_datastore.example_database.id
query = "SELECT * FROM my-table"
}
}
resource "datarobot_datasource" "example_connector" {
canonical_name = "Example Connector Data Source"
data_source_type = "dr-connector-v1"
params = {
data_store_id = datarobot_datastore.example_connector.id
path = "/my-folder/my-file.csv"
}
}
output "exampleId" {
value = datarobot_datasource.example_database_table.id
}
Create Datasource Resource
Resources are created with functions called constructors. To learn more about declaring and configuring resources, see Resources.
Constructor syntax
new Datasource(name: string, args: DatasourceArgs, opts?: CustomResourceOptions);@overload
def Datasource(resource_name: str,
args: DatasourceArgs,
opts: Optional[ResourceOptions] = None)
@overload
def Datasource(resource_name: str,
opts: Optional[ResourceOptions] = None,
canonical_name: Optional[str] = None,
data_source_type: Optional[str] = None,
params: Optional[DatasourceParamsArgs] = None)func NewDatasource(ctx *Context, name string, args DatasourceArgs, opts ...ResourceOption) (*Datasource, error)public Datasource(string name, DatasourceArgs args, CustomResourceOptions? opts = null)
public Datasource(String name, DatasourceArgs args)
public Datasource(String name, DatasourceArgs args, CustomResourceOptions options)
type: datarobot:Datasource
properties: # The arguments to resource properties.
options: # Bag of options to control resource's behavior.
resource "datarobot_datasource" "name" {
# resource properties
}Parameters
- name string
- The unique name of the resource.
- args DatasourceArgs
- The arguments to resource properties.
- opts CustomResourceOptions
- Bag of options to control resource's behavior.
- resource_name str
- The unique name of the resource.
- args DatasourceArgs
- The arguments to resource properties.
- opts ResourceOptions
- Bag of options to control resource's behavior.
- ctx Context
- Context object for the current deployment.
- name string
- The unique name of the resource.
- args DatasourceArgs
- The arguments to resource properties.
- opts ResourceOption
- Bag of options to control resource's behavior.
- name string
- The unique name of the resource.
- args DatasourceArgs
- The arguments to resource properties.
- opts CustomResourceOptions
- Bag of options to control resource's behavior.
- name String
- The unique name of the resource.
- args DatasourceArgs
- The arguments to resource properties.
- options CustomResourceOptions
- Bag of options to control resource's behavior.
Constructor example
The following reference example uses placeholder values for all input properties.
var datasourceResource = new Datarobot.Datasource("datasourceResource", new()
{
CanonicalName = "string",
DataSourceType = "string",
Params = new Datarobot.Inputs.DatasourceParamsArgs
{
DataStoreId = "string",
Catalog = "string",
FetchSize = 0,
PartitionColumn = "string",
Path = "string",
Query = "string",
Schema = "string",
Table = "string",
},
});
example, err := datarobot.NewDatasource(ctx, "datasourceResource", &datarobot.DatasourceArgs{
CanonicalName: pulumi.String("string"),
DataSourceType: pulumi.String("string"),
Params: &datarobot.DatasourceParamsArgs{
DataStoreId: pulumi.String("string"),
Catalog: pulumi.String("string"),
FetchSize: pulumi.Int(0),
PartitionColumn: pulumi.String("string"),
Path: pulumi.String("string"),
Query: pulumi.String("string"),
Schema: pulumi.String("string"),
Table: pulumi.String("string"),
},
})
resource "datarobot_datasource" "datasourceResource" {
lifecycle {
create_before_destroy = true
}
canonical_name = "string"
data_source_type = "string"
params = {
data_store_id = "string"
catalog = "string"
fetch_size = 0
partition_column = "string"
path = "string"
query = "string"
schema = "string"
table = "string"
}
}
var datasourceResource = new Datasource("datasourceResource", DatasourceArgs.builder()
.canonicalName("string")
.dataSourceType("string")
.params(DatasourceParamsArgs.builder()
.dataStoreId("string")
.catalog("string")
.fetchSize(0)
.partitionColumn("string")
.path("string")
.query("string")
.schema("string")
.table("string")
.build())
.build());
datasource_resource = datarobot.Datasource("datasourceResource",
canonical_name="string",
data_source_type="string",
params={
"data_store_id": "string",
"catalog": "string",
"fetch_size": 0,
"partition_column": "string",
"path": "string",
"query": "string",
"schema": "string",
"table": "string",
})
const datasourceResource = new datarobot.Datasource("datasourceResource", {
canonicalName: "string",
dataSourceType: "string",
params: {
dataStoreId: "string",
catalog: "string",
fetchSize: 0,
partitionColumn: "string",
path: "string",
query: "string",
schema: "string",
table: "string",
},
});
type: datarobot:Datasource
properties:
canonicalName: string
dataSourceType: string
params:
catalog: string
dataStoreId: string
fetchSize: 0
partitionColumn: string
path: string
query: string
schema: string
table: string
Datasource Resource Properties
To learn more about resource properties and how to use them, see Inputs and Outputs in the Architecture and Concepts docs.
Inputs
In Python, inputs that are objects can be passed either as argument classes or as dictionary literals.
The Datasource resource accepts the following input properties:
- Canonical
Name string - The user-friendly name of the data source.
- Data
Source stringType - The type of data source.
- Params
Data
Robot Datasource Params - The data source parameters.
- Canonical
Name string - The user-friendly name of the data source.
- Data
Source stringType - The type of data source.
- Params
Datasource
Params Args - The data source parameters.
- canonical_
name string - The user-friendly name of the data source.
- data_
source_ stringtype - The type of data source.
- params object
- The data source parameters.
- canonical
Name String - The user-friendly name of the data source.
- data
Source StringType - The type of data source.
- params
Datasource
Params - The data source parameters.
- canonical
Name string - The user-friendly name of the data source.
- data
Source stringType - The type of data source.
- params
Datasource
Params - The data source parameters.
- canonical_
name str - The user-friendly name of the data source.
- data_
source_ strtype - The type of data source.
- params
Datasource
Params Args - The data source parameters.
- canonical
Name String - The user-friendly name of the data source.
- data
Source StringType - The type of data source.
- params Property Map
- The data source parameters.
Outputs
All input properties are implicitly available as output properties. Additionally, the Datasource resource produces the following output properties:
- Id string
- The provider-assigned unique ID for this managed resource.
- Id string
- The provider-assigned unique ID for this managed resource.
- id string
- The provider-assigned unique ID for this managed resource.
- id String
- The provider-assigned unique ID for this managed resource.
- id string
- The provider-assigned unique ID for this managed resource.
- id str
- The provider-assigned unique ID for this managed resource.
- id String
- The provider-assigned unique ID for this managed resource.
Look up Existing Datasource Resource
Get an existing Datasource resource’s state with the given name, ID, and optional extra properties used to qualify the lookup.
public static get(name: string, id: Input<ID>, state?: DatasourceState, opts?: CustomResourceOptions): Datasource@staticmethod
def get(resource_name: str,
id: str,
opts: Optional[ResourceOptions] = None,
canonical_name: Optional[str] = None,
data_source_type: Optional[str] = None,
params: Optional[DatasourceParamsArgs] = None) -> Datasourcefunc GetDatasource(ctx *Context, name string, id IDInput, state *DatasourceState, opts ...ResourceOption) (*Datasource, error)public static Datasource Get(string name, Input<string> id, DatasourceState? state, CustomResourceOptions? opts = null)public static Datasource get(String name, Output<String> id, DatasourceState state, CustomResourceOptions options)resources: _: type: datarobot:Datasource get: id: ${id}import {
to = datarobot_datasource.example
id = "${id}"
}
- name
- The unique name of the resulting resource.
- id
- The unique provider ID of the resource to lookup.
- state
- Any extra arguments used during the lookup.
- opts
- A bag of options that control this resource's behavior.
- resource_name
- The unique name of the resulting resource.
- id
- The unique provider ID of the resource to lookup.
- name
- The unique name of the resulting resource.
- id
- The unique provider ID of the resource to lookup.
- state
- Any extra arguments used during the lookup.
- opts
- A bag of options that control this resource's behavior.
- name
- The unique name of the resulting resource.
- id
- The unique provider ID of the resource to lookup.
- state
- Any extra arguments used during the lookup.
- opts
- A bag of options that control this resource's behavior.
- name
- The unique name of the resulting resource.
- id
- The unique provider ID of the resource to lookup.
- state
- Any extra arguments used during the lookup.
- opts
- A bag of options that control this resource's behavior.
- Canonical
Name string - The user-friendly name of the data source.
- Data
Source stringType - The type of data source.
- Params
Data
Robot Datasource Params - The data source parameters.
- Canonical
Name string - The user-friendly name of the data source.
- Data
Source stringType - The type of data source.
- Params
Datasource
Params Args - The data source parameters.
- canonical_
name string - The user-friendly name of the data source.
- data_
source_ stringtype - The type of data source.
- params object
- The data source parameters.
- canonical
Name String - The user-friendly name of the data source.
- data
Source StringType - The type of data source.
- params
Datasource
Params - The data source parameters.
- canonical
Name string - The user-friendly name of the data source.
- data
Source stringType - The type of data source.
- params
Datasource
Params - The data source parameters.
- canonical_
name str - The user-friendly name of the data source.
- data_
source_ strtype - The type of data source.
- params
Datasource
Params Args - The data source parameters.
- canonical
Name String - The user-friendly name of the data source.
- data
Source StringType - The type of data source.
- params Property Map
- The data source parameters.
Supporting Types
DatasourceParams, DatasourceParamsArgs
- Data
Store stringId - The id of the DataStore.
- Catalog string
- The Catalog name in the database if supported.
- Fetch
Size int - A user specified fetch size in the range [1, 20000]. By default a fetchSize will be assigned to balance throughput and memory usage.
- Partition
Column string - The name of the partition column.
- Path string
- The user-specified path for BLOB storage.
- Query string
- The user specified SQL query.
- Schema string
- The name of the schema associated with the table.
- Table string
- The name of specified database table.
- Data
Store stringId - The id of the DataStore.
- Catalog string
- The Catalog name in the database if supported.
- Fetch
Size int - A user specified fetch size in the range [1, 20000]. By default a fetchSize will be assigned to balance throughput and memory usage.
- Partition
Column string - The name of the partition column.
- Path string
- The user-specified path for BLOB storage.
- Query string
- The user specified SQL query.
- Schema string
- The name of the schema associated with the table.
- Table string
- The name of specified database table.
- data_
store_ stringid - The id of the DataStore.
- catalog string
- The Catalog name in the database if supported.
- fetch_
size number - A user specified fetch size in the range [1, 20000]. By default a fetchSize will be assigned to balance throughput and memory usage.
- partition_
column string - The name of the partition column.
- path string
- The user-specified path for BLOB storage.
- query string
- The user specified SQL query.
- schema string
- The name of the schema associated with the table.
- table string
- The name of specified database table.
- data
Store StringId - The id of the DataStore.
- catalog String
- The Catalog name in the database if supported.
- fetch
Size Integer - A user specified fetch size in the range [1, 20000]. By default a fetchSize will be assigned to balance throughput and memory usage.
- partition
Column String - The name of the partition column.
- path String
- The user-specified path for BLOB storage.
- query String
- The user specified SQL query.
- schema String
- The name of the schema associated with the table.
- table String
- The name of specified database table.
- data
Store stringId - The id of the DataStore.
- catalog string
- The Catalog name in the database if supported.
- fetch
Size number - A user specified fetch size in the range [1, 20000]. By default a fetchSize will be assigned to balance throughput and memory usage.
- partition
Column string - The name of the partition column.
- path string
- The user-specified path for BLOB storage.
- query string
- The user specified SQL query.
- schema string
- The name of the schema associated with the table.
- table string
- The name of specified database table.
- data_
store_ strid - The id of the DataStore.
- catalog str
- The Catalog name in the database if supported.
- fetch_
size int - A user specified fetch size in the range [1, 20000]. By default a fetchSize will be assigned to balance throughput and memory usage.
- partition_
column str - The name of the partition column.
- path str
- The user-specified path for BLOB storage.
- query str
- The user specified SQL query.
- schema str
- The name of the schema associated with the table.
- table str
- The name of specified database table.
- data
Store StringId - The id of the DataStore.
- catalog String
- The Catalog name in the database if supported.
- fetch
Size Number - A user specified fetch size in the range [1, 20000]. By default a fetchSize will be assigned to balance throughput and memory usage.
- partition
Column String - The name of the partition column.
- path String
- The user-specified path for BLOB storage.
- query String
- The user specified SQL query.
- schema String
- The name of the schema associated with the table.
- table String
- The name of specified database table.
Package Details
- Repository
- datarobot datarobot-community/pulumi-datarobot
- License
- Apache-2.0
- Notes
- This Pulumi package is based on the
datarobotTerraform Provider.
published on Wednesday, Sep 9, 2026 by DataRobot, Inc.