Databricks v1.56.0, Nov 12 24

Databricks v1.56.0 published on Tuesday, Nov 12, 2024 by Pulumi

databricks.Library

Explore with Pulumi AI

Databricks v1.56.0 published on Tuesday, Nov 12, 2024 by Pulumi

databricks.Library resource would always start the associated cluster if it’s not running, so make sure to have auto-termination configured. It’s not possible to atomically change the version of the same library without cluster restart. Libraries are fully removed from the cluster only after restart.

Plugin Framework Migration

The library resource has been migrated from sdkv2 to plugin framework。 If you encounter any problem with this resource and suspect it is due to the migration, you can fallback to sdkv2 by setting the environment variable in the following way export USE_SDK_V2_RESOURCES="databricks.Library".

Installing library on all clusters

You can install libraries on all clusters with the help of databricks.getClusters data resource:

import * as pulumi from "@pulumi/pulumi";
import * as databricks from "@pulumi/databricks";

export = async () => {
    const all = await databricks.getClusters({});
    const cli: databricks.Library[] = [];
    for (const range of all.ids.map((v, k) => ({key: k, value: v}))) {
        cli.push(new databricks.Library(`cli-${range.key}`, {
            clusterId: range.key,
            pypi: {
                "package": "databricks-cli",
            },
        }));
    }
}

import pulumi
import pulumi_databricks as databricks

all = databricks.get_clusters()
cli = []
for range in [{"key": k, "value": v} for [k, v] in enumerate(all.ids)]:
    cli.append(databricks.Library(f"cli-{range['key']}",
        cluster_id=range["key"],
        pypi={
            "package": "databricks-cli",
        }))

package main

import (
	"github.com/pulumi/pulumi-databricks/sdk/go/databricks"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)

func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		all, err := databricks.GetClusters(ctx, &databricks.GetClustersArgs{}, nil)
		if err != nil {
			return err
		}
		var cli []*databricks.Library
		for key0, _ := range all.Ids {
			__res, err := databricks.NewLibrary(ctx, fmt.Sprintf("cli-%v", key0), &databricks.LibraryArgs{
				ClusterId: pulumi.Float64(key0),
				Pypi: &databricks.LibraryPypiArgs{
					Package: pulumi.String("databricks-cli"),
				},
			})
			if err != nil {
				return err
			}
			cli = append(cli, __res)
		}
		return nil
	})
}

using System.Collections.Generic;
using System.Linq;
using System.Threading.Tasks;
using Pulumi;
using Databricks = Pulumi.Databricks;

return await Deployment.RunAsync(async() => 
{
    var all = await Databricks.GetClusters.InvokeAsync();

    var cli = new List<Databricks.Library>();
    foreach (var range in )
    {
        cli.Add(new Databricks.Library($"cli-{range.Key}", new()
        {
            ClusterId = range.Key,
            Pypi = new Databricks.Inputs.LibraryPypiArgs
            {
                Package = "databricks-cli",
            },
        }));
    }
});

package generated_program;

import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.databricks.DatabricksFunctions;
import com.pulumi.databricks.inputs.GetClustersArgs;
import com.pulumi.databricks.Library;
import com.pulumi.databricks.LibraryArgs;
import com.pulumi.databricks.inputs.LibraryPypiArgs;
import com.pulumi.codegen.internal.KeyedValue;
import java.util.List;
import java.util.ArrayList;
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) {
        final var all = DatabricksFunctions.getClusters();

        final var cli = all.applyValue(getClustersResult -> {
            final var resources = new ArrayList<Library>();
            for (var range : KeyedValue.of(getClustersResult.ids()) {
                var resource = new Library("cli-" + range.key(), LibraryArgs.builder()
                    .clusterId(range.key())
                    .pypi(LibraryPypiArgs.builder()
                        .package_("databricks-cli")
                        .build())
                    .build());

                resources.add(resource);
            }

            return resources;
        });

    }
}

resources:
  cli:
    type: databricks:Library
    properties:
      clusterId: ${range.key}
      pypi:
        package: databricks-cli
    options: {}
variables:
  all:
    fn::invoke:
      Function: databricks:getClusters
      Arguments: {}

Java/Scala Maven

Installing artifacts from Maven repository. You can also optionally specify a repo parameter for a custom Maven-style repository, that should be accessible without any authentication. Maven libraries are resolved in Databricks Control Plane, so repo should be accessible from it. It can even be properly configured maven s3 wagon, AWS CodeArtifact or Azure Artifacts.

import * as pulumi from "@pulumi/pulumi";
import * as databricks from "@pulumi/databricks";

const deequ = new databricks.Library("deequ", {
    clusterId: _this.id,
    maven: {
        coordinates: "com.amazon.deequ:deequ:1.0.4",
        exclusions: ["org.apache.avro:avro"],
    },
});

import pulumi
import pulumi_databricks as databricks

deequ = databricks.Library("deequ",
    cluster_id=this["id"],
    maven={
        "coordinates": "com.amazon.deequ:deequ:1.0.4",
        "exclusions": ["org.apache.avro:avro"],
    })

package main

import (
	"github.com/pulumi/pulumi-databricks/sdk/go/databricks"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)

func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		_, err := databricks.NewLibrary(ctx, "deequ", &databricks.LibraryArgs{
			ClusterId: pulumi.Any(this.Id),
			Maven: &databricks.LibraryMavenArgs{
				Coordinates: pulumi.String("com.amazon.deequ:deequ:1.0.4"),
				Exclusions: pulumi.StringArray{
					pulumi.String("org.apache.avro:avro"),
				},
			},
		})
		if err != nil {
			return err
		}
		return nil
	})
}

using System.Collections.Generic;
using System.Linq;
using Pulumi;
using Databricks = Pulumi.Databricks;

return await Deployment.RunAsync(() => 
{
    var deequ = new Databricks.Library("deequ", new()
    {
        ClusterId = @this.Id,
        Maven = new Databricks.Inputs.LibraryMavenArgs
        {
            Coordinates = "com.amazon.deequ:deequ:1.0.4",
            Exclusions = new[]
            {
                "org.apache.avro:avro",
            },
        },
    });

});

package generated_program;

import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.databricks.Library;
import com.pulumi.databricks.LibraryArgs;
import com.pulumi.databricks.inputs.LibraryMavenArgs;
import java.util.List;
import java.util.ArrayList;
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 deequ = new Library("deequ", LibraryArgs.builder()
            .clusterId(this_.id())
            .maven(LibraryMavenArgs.builder()
                .coordinates("com.amazon.deequ:deequ:1.0.4")
                .exclusions("org.apache.avro:avro")
                .build())
            .build());

    }
}

resources:
  deequ:
    type: databricks:Library
    properties:
      clusterId: ${this.id}
      maven:
        coordinates: com.amazon.deequ:deequ:1.0.4
        exclusions:
          - org.apache.avro:avro

Python PyPI

Installing Python PyPI artifacts. You can optionally also specify the repo parameter for a custom PyPI mirror, which should be accessible without any authentication for the network that cluster runs in.

repo host should be accessible from the Internet by Databricks control plane. If connectivity to custom PyPI repositories is required, please modify cluster-node /etc/pip.conf through databricks_global_init_script.

import * as pulumi from "@pulumi/pulumi";
import * as databricks from "@pulumi/databricks";

const fbprophet = new databricks.Library("fbprophet", {
    clusterId: _this.id,
    pypi: {
        "package": "fbprophet==0.6",
    },
});

import pulumi
import pulumi_databricks as databricks

fbprophet = databricks.Library("fbprophet",
    cluster_id=this["id"],
    pypi={
        "package": "fbprophet==0.6",
    })

package main

import (
	"github.com/pulumi/pulumi-databricks/sdk/go/databricks"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)

func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		_, err := databricks.NewLibrary(ctx, "fbprophet", &databricks.LibraryArgs{
			ClusterId: pulumi.Any(this.Id),
			Pypi: &databricks.LibraryPypiArgs{
				Package: pulumi.String("fbprophet==0.6"),
			},
		})
		if err != nil {
			return err
		}
		return nil
	})
}

using System.Collections.Generic;
using System.Linq;
using Pulumi;
using Databricks = Pulumi.Databricks;

return await Deployment.RunAsync(() => 
{
    var fbprophet = new Databricks.Library("fbprophet", new()
    {
        ClusterId = @this.Id,
        Pypi = new Databricks.Inputs.LibraryPypiArgs
        {
            Package = "fbprophet==0.6",
        },
    });

});

package generated_program;

import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.databricks.Library;
import com.pulumi.databricks.LibraryArgs;
import com.pulumi.databricks.inputs.LibraryPypiArgs;
import java.util.List;
import java.util.ArrayList;
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 fbprophet = new Library("fbprophet", LibraryArgs.builder()
            .clusterId(this_.id())
            .pypi(LibraryPypiArgs.builder()
                .package_("fbprophet==0.6")
                .build())
            .build());

    }
}

resources:
  fbprophet:
    type: databricks:Library
    properties:
      clusterId: ${this.id}
      pypi:
        package: fbprophet==0.6

Python requirements files

Installing Python libraries listed in the requirements.txt file. Only Workspace paths and Unity Catalog Volumes paths are supported. Requires a cluster with DBR 15.0+.

import * as pulumi from "@pulumi/pulumi";
import * as databricks from "@pulumi/databricks";

const libraries = new databricks.Library("libraries", {
    clusterId: _this.id,
    requirements: "/Workspace/path/to/requirements.txt",
});

import pulumi
import pulumi_databricks as databricks

libraries = databricks.Library("libraries",
    cluster_id=this["id"],
    requirements="/Workspace/path/to/requirements.txt")

package main

import (
	"github.com/pulumi/pulumi-databricks/sdk/go/databricks"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)

func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		_, err := databricks.NewLibrary(ctx, "libraries", &databricks.LibraryArgs{
			ClusterId:    pulumi.Any(this.Id),
			Requirements: pulumi.String("/Workspace/path/to/requirements.txt"),
		})
		if err != nil {
			return err
		}
		return nil
	})
}

using System.Collections.Generic;
using System.Linq;
using Pulumi;
using Databricks = Pulumi.Databricks;

return await Deployment.RunAsync(() => 
{
    var libraries = new Databricks.Library("libraries", new()
    {
        ClusterId = @this.Id,
        Requirements = "/Workspace/path/to/requirements.txt",
    });

});

package generated_program;

import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.databricks.Library;
import com.pulumi.databricks.LibraryArgs;
import java.util.List;
import java.util.ArrayList;
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 libraries = new Library("libraries", LibraryArgs.builder()
            .clusterId(this_.id())
            .requirements("/Workspace/path/to/requirements.txt")
            .build());

    }
}

resources:
  libraries:
    type: databricks:Library
    properties:
      clusterId: ${this.id}
      requirements: /Workspace/path/to/requirements.txt

R CRan

Installing artifacts from CRan. You can also optionally specify a repo parameter for a custom cran mirror.

import * as pulumi from "@pulumi/pulumi";
import * as databricks from "@pulumi/databricks";

const rkeops = new databricks.Library("rkeops", {
    clusterId: _this.id,
    cran: {
        "package": "rkeops",
    },
});

import pulumi
import pulumi_databricks as databricks

rkeops = databricks.Library("rkeops",
    cluster_id=this["id"],
    cran={
        "package": "rkeops",
    })

package main

import (
	"github.com/pulumi/pulumi-databricks/sdk/go/databricks"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)

func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		_, err := databricks.NewLibrary(ctx, "rkeops", &databricks.LibraryArgs{
			ClusterId: pulumi.Any(this.Id),
			Cran: &databricks.LibraryCranArgs{
				Package: pulumi.String("rkeops"),
			},
		})
		if err != nil {
			return err
		}
		return nil
	})
}

using System.Collections.Generic;
using System.Linq;
using Pulumi;
using Databricks = Pulumi.Databricks;

return await Deployment.RunAsync(() => 
{
    var rkeops = new Databricks.Library("rkeops", new()
    {
        ClusterId = @this.Id,
        Cran = new Databricks.Inputs.LibraryCranArgs
        {
            Package = "rkeops",
        },
    });

});

package generated_program;

import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.databricks.Library;
import com.pulumi.databricks.LibraryArgs;
import com.pulumi.databricks.inputs.LibraryCranArgs;
import java.util.List;
import java.util.ArrayList;
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 rkeops = new Library("rkeops", LibraryArgs.builder()
            .clusterId(this_.id())
            .cran(LibraryCranArgs.builder()
                .package_("rkeops")
                .build())
            .build());

    }
}

resources:
  rkeops:
    type: databricks:Library
    properties:
      clusterId: ${this.id}
      cran:
        package: rkeops

The following resources are often used in the same context:

End to end workspace management guide.
databricks.getClusters data to retrieve a list of databricks.Cluster ids.
databricks.Cluster to create Databricks Clusters.
databricks.ClusterPolicy to create a databricks.Cluster policy, which limits the ability to create clusters based on a set of rules.
databricks.DbfsFile data to get file content from Databricks File System (DBFS).
databricks.getDbfsFilePaths data to get list of file names from get file content from Databricks File System (DBFS).
databricks.DbfsFile to manage relatively small files on Databricks File System (DBFS).
databricks.GlobalInitScript to manage global init scripts, which are run on all databricks.Cluster and databricks_job.
databricks.Job to manage Databricks Jobs to run non-interactive code in a databricks_cluster.
databricks.Mount to mount your cloud storage on dbfs:/mnt/name.
databricks.Pipeline to deploy Delta Live Tables.
databricks.Repo to manage Databricks Repos.

Create Library Resource

Resources are created with functions called constructors. To learn more about declaring and configuring resources, see Resources.

Constructor syntax

new Library(name: string, args: LibraryArgs, opts?: CustomResourceOptions);

@overload
def Library(resource_name: str,
            args: LibraryArgs,
            opts: Optional[ResourceOptions] = None)

@overload
def Library(resource_name: str,
            opts: Optional[ResourceOptions] = None,
            cluster_id: Optional[str] = None,
            cran: Optional[LibraryCranArgs] = None,
            egg: Optional[str] = None,
            jar: Optional[str] = None,
            library_id: Optional[str] = None,
            maven: Optional[LibraryMavenArgs] = None,
            pypi: Optional[LibraryPypiArgs] = None,
            requirements: Optional[str] = None,
            whl: Optional[str] = None)

func NewLibrary(ctx *Context, name string, args LibraryArgs, opts ...ResourceOption) (*Library, error)

public Library(string name, LibraryArgs args, CustomResourceOptions? opts = null)

public Library(String name, LibraryArgs args)
public Library(String name, LibraryArgs args, CustomResourceOptions options)

type: databricks:Library
properties: # The arguments to resource properties.
options: # Bag of options to control resource's behavior.

Parameters

name string: The unique name of the resource.
args LibraryArgs: 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 LibraryArgs: 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 LibraryArgs: The arguments to resource properties.
opts ResourceOption: Bag of options to control resource's behavior.

name string: The unique name of the resource.
args LibraryArgs: The arguments to resource properties.
opts CustomResourceOptions: Bag of options to control resource's behavior.

name String: The unique name of the resource.
args LibraryArgs: 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 libraryResource = new Databricks.Library("libraryResource", new()
{
    ClusterId = "string",
    Cran = new Databricks.Inputs.LibraryCranArgs
    {
        Package = "string",
        Repo = "string",
    },
    Egg = "string",
    Jar = "string",
    LibraryId = "string",
    Maven = new Databricks.Inputs.LibraryMavenArgs
    {
        Coordinates = "string",
        Exclusions = new[]
        {
            "string",
        },
        Repo = "string",
    },
    Pypi = new Databricks.Inputs.LibraryPypiArgs
    {
        Package = "string",
        Repo = "string",
    },
    Requirements = "string",
    Whl = "string",
});

example, err := databricks.NewLibrary(ctx, "libraryResource", &databricks.LibraryArgs{
	ClusterId: pulumi.String("string"),
	Cran: &databricks.LibraryCranArgs{
		Package: pulumi.String("string"),
		Repo:    pulumi.String("string"),
	},
	Egg:       pulumi.String("string"),
	Jar:       pulumi.String("string"),
	LibraryId: pulumi.String("string"),
	Maven: &databricks.LibraryMavenArgs{
		Coordinates: pulumi.String("string"),
		Exclusions: pulumi.StringArray{
			pulumi.String("string"),
		},
		Repo: pulumi.String("string"),
	},
	Pypi: &databricks.LibraryPypiArgs{
		Package: pulumi.String("string"),
		Repo:    pulumi.String("string"),
	},
	Requirements: pulumi.String("string"),
	Whl:          pulumi.String("string"),
})

var libraryResource = new Library("libraryResource", LibraryArgs.builder()
    .clusterId("string")
    .cran(LibraryCranArgs.builder()
        .package_("string")
        .repo("string")
        .build())
    .egg("string")
    .jar("string")
    .libraryId("string")
    .maven(LibraryMavenArgs.builder()
        .coordinates("string")
        .exclusions("string")
        .repo("string")
        .build())
    .pypi(LibraryPypiArgs.builder()
        .package_("string")
        .repo("string")
        .build())
    .requirements("string")
    .whl("string")
    .build());

library_resource = databricks.Library("libraryResource",
    cluster_id="string",
    cran={
        "package": "string",
        "repo": "string",
    },
    egg="string",
    jar="string",
    library_id="string",
    maven={
        "coordinates": "string",
        "exclusions": ["string"],
        "repo": "string",
    },
    pypi={
        "package": "string",
        "repo": "string",
    },
    requirements="string",
    whl="string")

const libraryResource = new databricks.Library("libraryResource", {
    clusterId: "string",
    cran: {
        "package": "string",
        repo: "string",
    },
    egg: "string",
    jar: "string",
    libraryId: "string",
    maven: {
        coordinates: "string",
        exclusions: ["string"],
        repo: "string",
    },
    pypi: {
        "package": "string",
        repo: "string",
    },
    requirements: "string",
    whl: "string",
});

type: databricks:Library
properties:
    clusterId: string
    cran:
        package: string
        repo: string
    egg: string
    jar: string
    libraryId: string
    maven:
        coordinates: string
        exclusions:
            - string
        repo: string
    pypi:
        package: string
        repo: string
    requirements: string
    whl: string

Library 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 Library resource accepts the following input properties:

ClusterId string
Cran LibraryCran
Egg string
Jar string
LibraryId string
Maven LibraryMaven
Pypi LibraryPypi
Requirements string
Whl string

ClusterId string
Cran LibraryCranArgs
Egg string
Jar string
LibraryId string
Maven LibraryMavenArgs
Pypi LibraryPypiArgs
Requirements string
Whl string

clusterId String
cran LibraryCran
egg String
jar String
libraryId String
maven LibraryMaven
pypi LibraryPypi
requirements String
whl String

clusterId string
cran LibraryCran
egg string
jar string
libraryId string
maven LibraryMaven
pypi LibraryPypi
requirements string
whl string

cluster_id str
cran LibraryCranArgs
egg str
jar str
library_id str
maven LibraryMavenArgs
pypi LibraryPypiArgs
requirements str
whl str

clusterId String
cran Property Map
egg String
jar String
libraryId String
maven Property Map
pypi Property Map
requirements String
whl String

Outputs

All input properties are implicitly available as output properties. Additionally, the Library 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 str: The provider-assigned unique ID for this managed resource.

id String: The provider-assigned unique ID for this managed resource.

Look up Existing Library Resource

Get an existing Library 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?: LibraryState, opts?: CustomResourceOptions): Library

@staticmethod
def get(resource_name: str,
        id: str,
        opts: Optional[ResourceOptions] = None,
        cluster_id: Optional[str] = None,
        cran: Optional[LibraryCranArgs] = None,
        egg: Optional[str] = None,
        jar: Optional[str] = None,
        library_id: Optional[str] = None,
        maven: Optional[LibraryMavenArgs] = None,
        pypi: Optional[LibraryPypiArgs] = None,
        requirements: Optional[str] = None,
        whl: Optional[str] = None) -> Library

func GetLibrary(ctx *Context, name string, id IDInput, state *LibraryState, opts ...ResourceOption) (*Library, error)

public static Library Get(string name, Input<string> id, LibraryState? state, CustomResourceOptions? opts = null)

public static Library get(String name, Output<String> id, LibraryState state, CustomResourceOptions options)

Resource lookup is not supported in YAML

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.

The following state arguments are supported:

ClusterId string
Cran LibraryCran
Egg string
Jar string
LibraryId string
Maven LibraryMaven
Pypi LibraryPypi
Requirements string
Whl string

ClusterId string
Cran LibraryCranArgs
Egg string
Jar string
LibraryId string
Maven LibraryMavenArgs
Pypi LibraryPypiArgs
Requirements string
Whl string

clusterId String
cran LibraryCran
egg String
jar String
libraryId String
maven LibraryMaven
pypi LibraryPypi
requirements String
whl String

clusterId string
cran LibraryCran
egg string
jar string
libraryId string
maven LibraryMaven
pypi LibraryPypi
requirements string
whl string

cluster_id str
cran LibraryCranArgs
egg str
jar str
library_id str
maven LibraryMavenArgs
pypi LibraryPypiArgs
requirements str
whl str

clusterId String
cran Property Map
egg String
jar String
libraryId String
maven Property Map
pypi Property Map
requirements String
whl String

Supporting Types

LibraryCran, LibraryCranArgs

Package string
Repo string

Package string
Repo string

package_ String
repo String

package string
repo string

package str
repo str

package String
repo String

LibraryMaven, LibraryMavenArgs

Coordinates string
Exclusions List<string>
Repo string

Coordinates string
Exclusions []string
Repo string

coordinates String
exclusions List<String>
repo String

coordinates string
exclusions string[]
repo string

coordinates str
exclusions Sequence[str]
repo str

coordinates String
exclusions List<String>
repo String

LibraryPypi, LibraryPypiArgs

Package string
Repo string

Package string
Repo string

package_ String
repo String

package string
repo string

package str
repo str

package String
repo String

Import

!> Importing this resource is not currently supported.

To learn more about importing existing cloud resources, see Importing resources.

Package Details

Repository: databricks pulumi/pulumi-databricks
License: Apache-2.0
Notes: This Pulumi package is based on the databricks Terraform Provider.

Databricks v1.56.0 published on Tuesday, Nov 12, 2024 by Pulumi

pulumi/pulumi-databricks

databricks.Library

On this page

On this page

Plugin Framework Migration

Installing library on all clusters

Java/Scala Maven

Python PyPI

Python requirements files

R CRan

Create Library Resource

Constructor syntax

Parameters

Constructor example

Library Resource Properties

Inputs

Outputs

Look up Existing Library Resource

Supporting Types

LibraryCran, LibraryCranArgs

LibraryMaven, LibraryMavenArgs

LibraryPypi, LibraryPypiArgs

Import

Package Details

On this page

On this page

databricks.Library

On this page

On this page

Plugin Framework Migration

Installing library on all clusters

Java/Scala Maven

Python PyPI

Python requirements files

R CRan

Related Resources

Create Library Resource

Constructor syntax

Parameters

Constructor example

Library Resource Properties

Inputs

Outputs

Look up Existing Library Resource

Supporting Types

LibraryCran, LibraryCranArgs

LibraryMaven, LibraryMavenArgs

LibraryPypi, LibraryPypiArgs

Import

Package Details

On this page

On this page