aws.glue.MLTransform
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Provides a Glue ML Transform resource.
Example Usage
import * as pulumi from "@pulumi/pulumi";
import * as aws from "@pulumi/aws";
const testCatalogDatabase = new aws.glue.CatalogDatabase("test", {name: "example"});
const testCatalogTable = new aws.glue.CatalogTable("test", {
name: "example",
databaseName: testCatalogDatabase.name,
owner: "my_owner",
retention: 1,
tableType: "VIRTUAL_VIEW",
viewExpandedText: "view_expanded_text_1",
viewOriginalText: "view_original_text_1",
storageDescriptor: {
bucketColumns: ["bucket_column_1"],
compressed: false,
inputFormat: "SequenceFileInputFormat",
location: "my_location",
numberOfBuckets: 1,
outputFormat: "SequenceFileInputFormat",
storedAsSubDirectories: false,
parameters: {
param1: "param1_val",
},
columns: [
{
name: "my_column_1",
type: "int",
comment: "my_column1_comment",
},
{
name: "my_column_2",
type: "string",
comment: "my_column2_comment",
},
],
serDeInfo: {
name: "ser_de_name",
parameters: {
param1: "param_val_1",
},
serializationLibrary: "org.apache.hadoop.hive.serde2.columnar.ColumnarSerDe",
},
sortColumns: [{
column: "my_column_1",
sortOrder: 1,
}],
skewedInfo: {
skewedColumnNames: ["my_column_1"],
skewedColumnValueLocationMaps: {
my_column_1: "my_column_1_val_loc_map",
},
skewedColumnValues: ["skewed_val_1"],
},
},
partitionKeys: [
{
name: "my_column_1",
type: "int",
comment: "my_column_1_comment",
},
{
name: "my_column_2",
type: "string",
comment: "my_column_2_comment",
},
],
parameters: {
param1: "param1_val",
},
});
const test = new aws.glue.MLTransform("test", {
name: "example",
roleArn: testAwsIamRole.arn,
inputRecordTables: [{
databaseName: testCatalogTable.databaseName,
tableName: testCatalogTable.name,
}],
parameters: {
transformType: "FIND_MATCHES",
findMatchesParameters: {
primaryKeyColumnName: "my_column_1",
},
},
}, {
dependsOn: [testAwsIamRolePolicyAttachment],
});
import pulumi
import pulumi_aws as aws
test_catalog_database = aws.glue.CatalogDatabase("test", name="example")
test_catalog_table = aws.glue.CatalogTable("test",
name="example",
database_name=test_catalog_database.name,
owner="my_owner",
retention=1,
table_type="VIRTUAL_VIEW",
view_expanded_text="view_expanded_text_1",
view_original_text="view_original_text_1",
storage_descriptor={
"bucket_columns": ["bucket_column_1"],
"compressed": False,
"input_format": "SequenceFileInputFormat",
"location": "my_location",
"number_of_buckets": 1,
"output_format": "SequenceFileInputFormat",
"stored_as_sub_directories": False,
"parameters": {
"param1": "param1_val",
},
"columns": [
{
"name": "my_column_1",
"type": "int",
"comment": "my_column1_comment",
},
{
"name": "my_column_2",
"type": "string",
"comment": "my_column2_comment",
},
],
"ser_de_info": {
"name": "ser_de_name",
"parameters": {
"param1": "param_val_1",
},
"serialization_library": "org.apache.hadoop.hive.serde2.columnar.ColumnarSerDe",
},
"sort_columns": [{
"column": "my_column_1",
"sort_order": 1,
}],
"skewed_info": {
"skewed_column_names": ["my_column_1"],
"skewed_column_value_location_maps": {
"my_column_1": "my_column_1_val_loc_map",
},
"skewed_column_values": ["skewed_val_1"],
},
},
partition_keys=[
{
"name": "my_column_1",
"type": "int",
"comment": "my_column_1_comment",
},
{
"name": "my_column_2",
"type": "string",
"comment": "my_column_2_comment",
},
],
parameters={
"param1": "param1_val",
})
test = aws.glue.MLTransform("test",
name="example",
role_arn=test_aws_iam_role["arn"],
input_record_tables=[{
"database_name": test_catalog_table.database_name,
"table_name": test_catalog_table.name,
}],
parameters={
"transform_type": "FIND_MATCHES",
"find_matches_parameters": {
"primary_key_column_name": "my_column_1",
},
},
opts = pulumi.ResourceOptions(depends_on=[test_aws_iam_role_policy_attachment]))
package main
import (
"github.com/pulumi/pulumi-aws/sdk/v6/go/aws/glue"
"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)
func main() {
pulumi.Run(func(ctx *pulumi.Context) error {
testCatalogDatabase, err := glue.NewCatalogDatabase(ctx, "test", &glue.CatalogDatabaseArgs{
Name: pulumi.String("example"),
})
if err != nil {
return err
}
testCatalogTable, err := glue.NewCatalogTable(ctx, "test", &glue.CatalogTableArgs{
Name: pulumi.String("example"),
DatabaseName: testCatalogDatabase.Name,
Owner: pulumi.String("my_owner"),
Retention: pulumi.Int(1),
TableType: pulumi.String("VIRTUAL_VIEW"),
ViewExpandedText: pulumi.String("view_expanded_text_1"),
ViewOriginalText: pulumi.String("view_original_text_1"),
StorageDescriptor: &glue.CatalogTableStorageDescriptorArgs{
BucketColumns: pulumi.StringArray{
pulumi.String("bucket_column_1"),
},
Compressed: pulumi.Bool(false),
InputFormat: pulumi.String("SequenceFileInputFormat"),
Location: pulumi.String("my_location"),
NumberOfBuckets: pulumi.Int(1),
OutputFormat: pulumi.String("SequenceFileInputFormat"),
StoredAsSubDirectories: pulumi.Bool(false),
Parameters: pulumi.StringMap{
"param1": pulumi.String("param1_val"),
},
Columns: glue.CatalogTableStorageDescriptorColumnArray{
&glue.CatalogTableStorageDescriptorColumnArgs{
Name: pulumi.String("my_column_1"),
Type: pulumi.String("int"),
Comment: pulumi.String("my_column1_comment"),
},
&glue.CatalogTableStorageDescriptorColumnArgs{
Name: pulumi.String("my_column_2"),
Type: pulumi.String("string"),
Comment: pulumi.String("my_column2_comment"),
},
},
SerDeInfo: &glue.CatalogTableStorageDescriptorSerDeInfoArgs{
Name: pulumi.String("ser_de_name"),
Parameters: pulumi.StringMap{
"param1": pulumi.String("param_val_1"),
},
SerializationLibrary: pulumi.String("org.apache.hadoop.hive.serde2.columnar.ColumnarSerDe"),
},
SortColumns: glue.CatalogTableStorageDescriptorSortColumnArray{
&glue.CatalogTableStorageDescriptorSortColumnArgs{
Column: pulumi.String("my_column_1"),
SortOrder: pulumi.Int(1),
},
},
SkewedInfo: &glue.CatalogTableStorageDescriptorSkewedInfoArgs{
SkewedColumnNames: pulumi.StringArray{
pulumi.String("my_column_1"),
},
SkewedColumnValueLocationMaps: pulumi.StringMap{
"my_column_1": pulumi.String("my_column_1_val_loc_map"),
},
SkewedColumnValues: pulumi.StringArray{
pulumi.String("skewed_val_1"),
},
},
},
PartitionKeys: glue.CatalogTablePartitionKeyArray{
&glue.CatalogTablePartitionKeyArgs{
Name: pulumi.String("my_column_1"),
Type: pulumi.String("int"),
Comment: pulumi.String("my_column_1_comment"),
},
&glue.CatalogTablePartitionKeyArgs{
Name: pulumi.String("my_column_2"),
Type: pulumi.String("string"),
Comment: pulumi.String("my_column_2_comment"),
},
},
Parameters: pulumi.StringMap{
"param1": pulumi.String("param1_val"),
},
})
if err != nil {
return err
}
_, err = glue.NewMLTransform(ctx, "test", &glue.MLTransformArgs{
Name: pulumi.String("example"),
RoleArn: pulumi.Any(testAwsIamRole.Arn),
InputRecordTables: glue.MLTransformInputRecordTableArray{
&glue.MLTransformInputRecordTableArgs{
DatabaseName: testCatalogTable.DatabaseName,
TableName: testCatalogTable.Name,
},
},
Parameters: &glue.MLTransformParametersArgs{
TransformType: pulumi.String("FIND_MATCHES"),
FindMatchesParameters: &glue.MLTransformParametersFindMatchesParametersArgs{
PrimaryKeyColumnName: pulumi.String("my_column_1"),
},
},
}, pulumi.DependsOn([]pulumi.Resource{
testAwsIamRolePolicyAttachment,
}))
if err != nil {
return err
}
return nil
})
}
using System.Collections.Generic;
using System.Linq;
using Pulumi;
using Aws = Pulumi.Aws;
return await Deployment.RunAsync(() =>
{
var testCatalogDatabase = new Aws.Glue.CatalogDatabase("test", new()
{
Name = "example",
});
var testCatalogTable = new Aws.Glue.CatalogTable("test", new()
{
Name = "example",
DatabaseName = testCatalogDatabase.Name,
Owner = "my_owner",
Retention = 1,
TableType = "VIRTUAL_VIEW",
ViewExpandedText = "view_expanded_text_1",
ViewOriginalText = "view_original_text_1",
StorageDescriptor = new Aws.Glue.Inputs.CatalogTableStorageDescriptorArgs
{
BucketColumns = new[]
{
"bucket_column_1",
},
Compressed = false,
InputFormat = "SequenceFileInputFormat",
Location = "my_location",
NumberOfBuckets = 1,
OutputFormat = "SequenceFileInputFormat",
StoredAsSubDirectories = false,
Parameters =
{
{ "param1", "param1_val" },
},
Columns = new[]
{
new Aws.Glue.Inputs.CatalogTableStorageDescriptorColumnArgs
{
Name = "my_column_1",
Type = "int",
Comment = "my_column1_comment",
},
new Aws.Glue.Inputs.CatalogTableStorageDescriptorColumnArgs
{
Name = "my_column_2",
Type = "string",
Comment = "my_column2_comment",
},
},
SerDeInfo = new Aws.Glue.Inputs.CatalogTableStorageDescriptorSerDeInfoArgs
{
Name = "ser_de_name",
Parameters =
{
{ "param1", "param_val_1" },
},
SerializationLibrary = "org.apache.hadoop.hive.serde2.columnar.ColumnarSerDe",
},
SortColumns = new[]
{
new Aws.Glue.Inputs.CatalogTableStorageDescriptorSortColumnArgs
{
Column = "my_column_1",
SortOrder = 1,
},
},
SkewedInfo = new Aws.Glue.Inputs.CatalogTableStorageDescriptorSkewedInfoArgs
{
SkewedColumnNames = new[]
{
"my_column_1",
},
SkewedColumnValueLocationMaps =
{
{ "my_column_1", "my_column_1_val_loc_map" },
},
SkewedColumnValues = new[]
{
"skewed_val_1",
},
},
},
PartitionKeys = new[]
{
new Aws.Glue.Inputs.CatalogTablePartitionKeyArgs
{
Name = "my_column_1",
Type = "int",
Comment = "my_column_1_comment",
},
new Aws.Glue.Inputs.CatalogTablePartitionKeyArgs
{
Name = "my_column_2",
Type = "string",
Comment = "my_column_2_comment",
},
},
Parameters =
{
{ "param1", "param1_val" },
},
});
var test = new Aws.Glue.MLTransform("test", new()
{
Name = "example",
RoleArn = testAwsIamRole.Arn,
InputRecordTables = new[]
{
new Aws.Glue.Inputs.MLTransformInputRecordTableArgs
{
DatabaseName = testCatalogTable.DatabaseName,
TableName = testCatalogTable.Name,
},
},
Parameters = new Aws.Glue.Inputs.MLTransformParametersArgs
{
TransformType = "FIND_MATCHES",
FindMatchesParameters = new Aws.Glue.Inputs.MLTransformParametersFindMatchesParametersArgs
{
PrimaryKeyColumnName = "my_column_1",
},
},
}, new CustomResourceOptions
{
DependsOn =
{
testAwsIamRolePolicyAttachment,
},
});
});
package generated_program;
import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.aws.glue.CatalogDatabase;
import com.pulumi.aws.glue.CatalogDatabaseArgs;
import com.pulumi.aws.glue.CatalogTable;
import com.pulumi.aws.glue.CatalogTableArgs;
import com.pulumi.aws.glue.inputs.CatalogTableStorageDescriptorArgs;
import com.pulumi.aws.glue.inputs.CatalogTableStorageDescriptorSerDeInfoArgs;
import com.pulumi.aws.glue.inputs.CatalogTableStorageDescriptorSkewedInfoArgs;
import com.pulumi.aws.glue.inputs.CatalogTablePartitionKeyArgs;
import com.pulumi.aws.glue.MLTransform;
import com.pulumi.aws.glue.MLTransformArgs;
import com.pulumi.aws.glue.inputs.MLTransformInputRecordTableArgs;
import com.pulumi.aws.glue.inputs.MLTransformParametersArgs;
import com.pulumi.aws.glue.inputs.MLTransformParametersFindMatchesParametersArgs;
import com.pulumi.resources.CustomResourceOptions;
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 testCatalogDatabase = new CatalogDatabase("testCatalogDatabase", CatalogDatabaseArgs.builder()
.name("example")
.build());
var testCatalogTable = new CatalogTable("testCatalogTable", CatalogTableArgs.builder()
.name("example")
.databaseName(testCatalogDatabase.name())
.owner("my_owner")
.retention(1)
.tableType("VIRTUAL_VIEW")
.viewExpandedText("view_expanded_text_1")
.viewOriginalText("view_original_text_1")
.storageDescriptor(CatalogTableStorageDescriptorArgs.builder()
.bucketColumns("bucket_column_1")
.compressed(false)
.inputFormat("SequenceFileInputFormat")
.location("my_location")
.numberOfBuckets(1)
.outputFormat("SequenceFileInputFormat")
.storedAsSubDirectories(false)
.parameters(Map.of("param1", "param1_val"))
.columns(
CatalogTableStorageDescriptorColumnArgs.builder()
.name("my_column_1")
.type("int")
.comment("my_column1_comment")
.build(),
CatalogTableStorageDescriptorColumnArgs.builder()
.name("my_column_2")
.type("string")
.comment("my_column2_comment")
.build())
.serDeInfo(CatalogTableStorageDescriptorSerDeInfoArgs.builder()
.name("ser_de_name")
.parameters(Map.of("param1", "param_val_1"))
.serializationLibrary("org.apache.hadoop.hive.serde2.columnar.ColumnarSerDe")
.build())
.sortColumns(CatalogTableStorageDescriptorSortColumnArgs.builder()
.column("my_column_1")
.sortOrder(1)
.build())
.skewedInfo(CatalogTableStorageDescriptorSkewedInfoArgs.builder()
.skewedColumnNames("my_column_1")
.skewedColumnValueLocationMaps(Map.of("my_column_1", "my_column_1_val_loc_map"))
.skewedColumnValues("skewed_val_1")
.build())
.build())
.partitionKeys(
CatalogTablePartitionKeyArgs.builder()
.name("my_column_1")
.type("int")
.comment("my_column_1_comment")
.build(),
CatalogTablePartitionKeyArgs.builder()
.name("my_column_2")
.type("string")
.comment("my_column_2_comment")
.build())
.parameters(Map.of("param1", "param1_val"))
.build());
var test = new MLTransform("test", MLTransformArgs.builder()
.name("example")
.roleArn(testAwsIamRole.arn())
.inputRecordTables(MLTransformInputRecordTableArgs.builder()
.databaseName(testCatalogTable.databaseName())
.tableName(testCatalogTable.name())
.build())
.parameters(MLTransformParametersArgs.builder()
.transformType("FIND_MATCHES")
.findMatchesParameters(MLTransformParametersFindMatchesParametersArgs.builder()
.primaryKeyColumnName("my_column_1")
.build())
.build())
.build(), CustomResourceOptions.builder()
.dependsOn(testAwsIamRolePolicyAttachment)
.build());
}
}
resources:
test:
type: aws:glue:MLTransform
properties:
name: example
roleArn: ${testAwsIamRole.arn}
inputRecordTables:
- databaseName: ${testCatalogTable.databaseName}
tableName: ${testCatalogTable.name}
parameters:
transformType: FIND_MATCHES
findMatchesParameters:
primaryKeyColumnName: my_column_1
options:
dependson:
- ${testAwsIamRolePolicyAttachment}
testCatalogDatabase:
type: aws:glue:CatalogDatabase
name: test
properties:
name: example
testCatalogTable:
type: aws:glue:CatalogTable
name: test
properties:
name: example
databaseName: ${testCatalogDatabase.name}
owner: my_owner
retention: 1
tableType: VIRTUAL_VIEW
viewExpandedText: view_expanded_text_1
viewOriginalText: view_original_text_1
storageDescriptor:
bucketColumns:
- bucket_column_1
compressed: false
inputFormat: SequenceFileInputFormat
location: my_location
numberOfBuckets: 1
outputFormat: SequenceFileInputFormat
storedAsSubDirectories: false
parameters:
param1: param1_val
columns:
- name: my_column_1
type: int
comment: my_column1_comment
- name: my_column_2
type: string
comment: my_column2_comment
serDeInfo:
name: ser_de_name
parameters:
param1: param_val_1
serializationLibrary: org.apache.hadoop.hive.serde2.columnar.ColumnarSerDe
sortColumns:
- column: my_column_1
sortOrder: 1
skewedInfo:
skewedColumnNames:
- my_column_1
skewedColumnValueLocationMaps:
my_column_1: my_column_1_val_loc_map
skewedColumnValues:
- skewed_val_1
partitionKeys:
- name: my_column_1
type: int
comment: my_column_1_comment
- name: my_column_2
type: string
comment: my_column_2_comment
parameters:
param1: param1_val
Create MLTransform Resource
Resources are created with functions called constructors. To learn more about declaring and configuring resources, see Resources.
Constructor syntax
new MLTransform(name: string, args: MLTransformArgs, opts?: CustomResourceOptions);
@overload
def MLTransform(resource_name: str,
args: MLTransformArgs,
opts: Optional[ResourceOptions] = None)
@overload
def MLTransform(resource_name: str,
opts: Optional[ResourceOptions] = None,
input_record_tables: Optional[Sequence[MLTransformInputRecordTableArgs]] = None,
parameters: Optional[MLTransformParametersArgs] = None,
role_arn: Optional[str] = None,
description: Optional[str] = None,
glue_version: Optional[str] = None,
max_capacity: Optional[float] = None,
max_retries: Optional[int] = None,
name: Optional[str] = None,
number_of_workers: Optional[int] = None,
tags: Optional[Mapping[str, str]] = None,
timeout: Optional[int] = None,
worker_type: Optional[str] = None)
func NewMLTransform(ctx *Context, name string, args MLTransformArgs, opts ...ResourceOption) (*MLTransform, error)
public MLTransform(string name, MLTransformArgs args, CustomResourceOptions? opts = null)
public MLTransform(String name, MLTransformArgs args)
public MLTransform(String name, MLTransformArgs args, CustomResourceOptions options)
type: aws:glue:MLTransform
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 MLTransformArgs
- 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 MLTransformArgs
- 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 MLTransformArgs
- The arguments to resource properties.
- opts ResourceOption
- Bag of options to control resource's behavior.
- name string
- The unique name of the resource.
- args MLTransformArgs
- The arguments to resource properties.
- opts CustomResourceOptions
- Bag of options to control resource's behavior.
- name String
- The unique name of the resource.
- args MLTransformArgs
- 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 mltransformResource = new Aws.Glue.MLTransform("mltransformResource", new()
{
InputRecordTables = new[]
{
new Aws.Glue.Inputs.MLTransformInputRecordTableArgs
{
DatabaseName = "string",
TableName = "string",
CatalogId = "string",
ConnectionName = "string",
},
},
Parameters = new Aws.Glue.Inputs.MLTransformParametersArgs
{
FindMatchesParameters = new Aws.Glue.Inputs.MLTransformParametersFindMatchesParametersArgs
{
AccuracyCostTradeOff = 0,
EnforceProvidedLabels = false,
PrecisionRecallTradeOff = 0,
PrimaryKeyColumnName = "string",
},
TransformType = "string",
},
RoleArn = "string",
Description = "string",
GlueVersion = "string",
MaxCapacity = 0,
MaxRetries = 0,
Name = "string",
NumberOfWorkers = 0,
Tags =
{
{ "string", "string" },
},
Timeout = 0,
WorkerType = "string",
});
example, err := glue.NewMLTransform(ctx, "mltransformResource", &glue.MLTransformArgs{
InputRecordTables: glue.MLTransformInputRecordTableArray{
&glue.MLTransformInputRecordTableArgs{
DatabaseName: pulumi.String("string"),
TableName: pulumi.String("string"),
CatalogId: pulumi.String("string"),
ConnectionName: pulumi.String("string"),
},
},
Parameters: &glue.MLTransformParametersArgs{
FindMatchesParameters: &glue.MLTransformParametersFindMatchesParametersArgs{
AccuracyCostTradeOff: pulumi.Float64(0),
EnforceProvidedLabels: pulumi.Bool(false),
PrecisionRecallTradeOff: pulumi.Float64(0),
PrimaryKeyColumnName: pulumi.String("string"),
},
TransformType: pulumi.String("string"),
},
RoleArn: pulumi.String("string"),
Description: pulumi.String("string"),
GlueVersion: pulumi.String("string"),
MaxCapacity: pulumi.Float64(0),
MaxRetries: pulumi.Int(0),
Name: pulumi.String("string"),
NumberOfWorkers: pulumi.Int(0),
Tags: pulumi.StringMap{
"string": pulumi.String("string"),
},
Timeout: pulumi.Int(0),
WorkerType: pulumi.String("string"),
})
var mltransformResource = new MLTransform("mltransformResource", MLTransformArgs.builder()
.inputRecordTables(MLTransformInputRecordTableArgs.builder()
.databaseName("string")
.tableName("string")
.catalogId("string")
.connectionName("string")
.build())
.parameters(MLTransformParametersArgs.builder()
.findMatchesParameters(MLTransformParametersFindMatchesParametersArgs.builder()
.accuracyCostTradeOff(0)
.enforceProvidedLabels(false)
.precisionRecallTradeOff(0)
.primaryKeyColumnName("string")
.build())
.transformType("string")
.build())
.roleArn("string")
.description("string")
.glueVersion("string")
.maxCapacity(0)
.maxRetries(0)
.name("string")
.numberOfWorkers(0)
.tags(Map.of("string", "string"))
.timeout(0)
.workerType("string")
.build());
mltransform_resource = aws.glue.MLTransform("mltransformResource",
input_record_tables=[{
"database_name": "string",
"table_name": "string",
"catalog_id": "string",
"connection_name": "string",
}],
parameters={
"find_matches_parameters": {
"accuracy_cost_trade_off": 0,
"enforce_provided_labels": False,
"precision_recall_trade_off": 0,
"primary_key_column_name": "string",
},
"transform_type": "string",
},
role_arn="string",
description="string",
glue_version="string",
max_capacity=0,
max_retries=0,
name="string",
number_of_workers=0,
tags={
"string": "string",
},
timeout=0,
worker_type="string")
const mltransformResource = new aws.glue.MLTransform("mltransformResource", {
inputRecordTables: [{
databaseName: "string",
tableName: "string",
catalogId: "string",
connectionName: "string",
}],
parameters: {
findMatchesParameters: {
accuracyCostTradeOff: 0,
enforceProvidedLabels: false,
precisionRecallTradeOff: 0,
primaryKeyColumnName: "string",
},
transformType: "string",
},
roleArn: "string",
description: "string",
glueVersion: "string",
maxCapacity: 0,
maxRetries: 0,
name: "string",
numberOfWorkers: 0,
tags: {
string: "string",
},
timeout: 0,
workerType: "string",
});
type: aws:glue:MLTransform
properties:
description: string
glueVersion: string
inputRecordTables:
- catalogId: string
connectionName: string
databaseName: string
tableName: string
maxCapacity: 0
maxRetries: 0
name: string
numberOfWorkers: 0
parameters:
findMatchesParameters:
accuracyCostTradeOff: 0
enforceProvidedLabels: false
precisionRecallTradeOff: 0
primaryKeyColumnName: string
transformType: string
roleArn: string
tags:
string: string
timeout: 0
workerType: string
MLTransform 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 MLTransform resource accepts the following input properties:
- Input
Record List<MLTransformTables Input Record Table> - A list of AWS Glue table definitions used by the transform. see Input Record Tables.
- Parameters
MLTransform
Parameters - The algorithmic parameters that are specific to the transform type used. Conditionally dependent on the transform type. see Parameters.
- Role
Arn string - The ARN of the IAM role associated with this ML Transform.
- Description string
- Description of the ML Transform.
- Glue
Version string - The version of glue to use, for example "1.0". For information about available versions, see the AWS Glue Release Notes.
- Max
Capacity double - The number of AWS Glue data processing units (DPUs) that are allocated to task runs for this transform. You can allocate from
2
to100
DPUs; the default is10
.max_capacity
is a mutually exclusive option withnumber_of_workers
andworker_type
. - Max
Retries int - The maximum number of times to retry this ML Transform if it fails.
- Name string
- The name you assign to this ML Transform. It must be unique in your account.
- Number
Of intWorkers - The number of workers of a defined
worker_type
that are allocated when an ML Transform runs. Required withworker_type
. - Dictionary<string, string>
- Key-value map of resource tags. .If configured with a provider
default_tags
configuration block present, tags with matching keys will overwrite those defined at the provider-level. - Timeout int
- The ML Transform timeout in minutes. The default is 2880 minutes (48 hours).
- Worker
Type string - The type of predefined worker that is allocated when an ML Transform runs. Accepts a value of
Standard
,G.1X
, orG.2X
. Required withnumber_of_workers
.
- Input
Record []MLTransformTables Input Record Table Args - A list of AWS Glue table definitions used by the transform. see Input Record Tables.
- Parameters
MLTransform
Parameters Args - The algorithmic parameters that are specific to the transform type used. Conditionally dependent on the transform type. see Parameters.
- Role
Arn string - The ARN of the IAM role associated with this ML Transform.
- Description string
- Description of the ML Transform.
- Glue
Version string - The version of glue to use, for example "1.0". For information about available versions, see the AWS Glue Release Notes.
- Max
Capacity float64 - The number of AWS Glue data processing units (DPUs) that are allocated to task runs for this transform. You can allocate from
2
to100
DPUs; the default is10
.max_capacity
is a mutually exclusive option withnumber_of_workers
andworker_type
. - Max
Retries int - The maximum number of times to retry this ML Transform if it fails.
- Name string
- The name you assign to this ML Transform. It must be unique in your account.
- Number
Of intWorkers - The number of workers of a defined
worker_type
that are allocated when an ML Transform runs. Required withworker_type
. - map[string]string
- Key-value map of resource tags. .If configured with a provider
default_tags
configuration block present, tags with matching keys will overwrite those defined at the provider-level. - Timeout int
- The ML Transform timeout in minutes. The default is 2880 minutes (48 hours).
- Worker
Type string - The type of predefined worker that is allocated when an ML Transform runs. Accepts a value of
Standard
,G.1X
, orG.2X
. Required withnumber_of_workers
.
- input
Record List<MLTransformTables Input Record Table> - A list of AWS Glue table definitions used by the transform. see Input Record Tables.
- parameters
MLTransform
Parameters - The algorithmic parameters that are specific to the transform type used. Conditionally dependent on the transform type. see Parameters.
- role
Arn String - The ARN of the IAM role associated with this ML Transform.
- description String
- Description of the ML Transform.
- glue
Version String - The version of glue to use, for example "1.0". For information about available versions, see the AWS Glue Release Notes.
- max
Capacity Double - The number of AWS Glue data processing units (DPUs) that are allocated to task runs for this transform. You can allocate from
2
to100
DPUs; the default is10
.max_capacity
is a mutually exclusive option withnumber_of_workers
andworker_type
. - max
Retries Integer - The maximum number of times to retry this ML Transform if it fails.
- name String
- The name you assign to this ML Transform. It must be unique in your account.
- number
Of IntegerWorkers - The number of workers of a defined
worker_type
that are allocated when an ML Transform runs. Required withworker_type
. - Map<String,String>
- Key-value map of resource tags. .If configured with a provider
default_tags
configuration block present, tags with matching keys will overwrite those defined at the provider-level. - timeout Integer
- The ML Transform timeout in minutes. The default is 2880 minutes (48 hours).
- worker
Type String - The type of predefined worker that is allocated when an ML Transform runs. Accepts a value of
Standard
,G.1X
, orG.2X
. Required withnumber_of_workers
.
- input
Record MLTransformTables Input Record Table[] - A list of AWS Glue table definitions used by the transform. see Input Record Tables.
- parameters
MLTransform
Parameters - The algorithmic parameters that are specific to the transform type used. Conditionally dependent on the transform type. see Parameters.
- role
Arn string - The ARN of the IAM role associated with this ML Transform.
- description string
- Description of the ML Transform.
- glue
Version string - The version of glue to use, for example "1.0". For information about available versions, see the AWS Glue Release Notes.
- max
Capacity number - The number of AWS Glue data processing units (DPUs) that are allocated to task runs for this transform. You can allocate from
2
to100
DPUs; the default is10
.max_capacity
is a mutually exclusive option withnumber_of_workers
andworker_type
. - max
Retries number - The maximum number of times to retry this ML Transform if it fails.
- name string
- The name you assign to this ML Transform. It must be unique in your account.
- number
Of numberWorkers - The number of workers of a defined
worker_type
that are allocated when an ML Transform runs. Required withworker_type
. - {[key: string]: string}
- Key-value map of resource tags. .If configured with a provider
default_tags
configuration block present, tags with matching keys will overwrite those defined at the provider-level. - timeout number
- The ML Transform timeout in minutes. The default is 2880 minutes (48 hours).
- worker
Type string - The type of predefined worker that is allocated when an ML Transform runs. Accepts a value of
Standard
,G.1X
, orG.2X
. Required withnumber_of_workers
.
- input_
record_ Sequence[MLTransformtables Input Record Table Args] - A list of AWS Glue table definitions used by the transform. see Input Record Tables.
- parameters
MLTransform
Parameters Args - The algorithmic parameters that are specific to the transform type used. Conditionally dependent on the transform type. see Parameters.
- role_
arn str - The ARN of the IAM role associated with this ML Transform.
- description str
- Description of the ML Transform.
- glue_
version str - The version of glue to use, for example "1.0". For information about available versions, see the AWS Glue Release Notes.
- max_
capacity float - The number of AWS Glue data processing units (DPUs) that are allocated to task runs for this transform. You can allocate from
2
to100
DPUs; the default is10
.max_capacity
is a mutually exclusive option withnumber_of_workers
andworker_type
. - max_
retries int - The maximum number of times to retry this ML Transform if it fails.
- name str
- The name you assign to this ML Transform. It must be unique in your account.
- number_
of_ intworkers - The number of workers of a defined
worker_type
that are allocated when an ML Transform runs. Required withworker_type
. - Mapping[str, str]
- Key-value map of resource tags. .If configured with a provider
default_tags
configuration block present, tags with matching keys will overwrite those defined at the provider-level. - timeout int
- The ML Transform timeout in minutes. The default is 2880 minutes (48 hours).
- worker_
type str - The type of predefined worker that is allocated when an ML Transform runs. Accepts a value of
Standard
,G.1X
, orG.2X
. Required withnumber_of_workers
.
- input
Record List<Property Map>Tables - A list of AWS Glue table definitions used by the transform. see Input Record Tables.
- parameters Property Map
- The algorithmic parameters that are specific to the transform type used. Conditionally dependent on the transform type. see Parameters.
- role
Arn String - The ARN of the IAM role associated with this ML Transform.
- description String
- Description of the ML Transform.
- glue
Version String - The version of glue to use, for example "1.0". For information about available versions, see the AWS Glue Release Notes.
- max
Capacity Number - The number of AWS Glue data processing units (DPUs) that are allocated to task runs for this transform. You can allocate from
2
to100
DPUs; the default is10
.max_capacity
is a mutually exclusive option withnumber_of_workers
andworker_type
. - max
Retries Number - The maximum number of times to retry this ML Transform if it fails.
- name String
- The name you assign to this ML Transform. It must be unique in your account.
- number
Of NumberWorkers - The number of workers of a defined
worker_type
that are allocated when an ML Transform runs. Required withworker_type
. - Map<String>
- Key-value map of resource tags. .If configured with a provider
default_tags
configuration block present, tags with matching keys will overwrite those defined at the provider-level. - timeout Number
- The ML Transform timeout in minutes. The default is 2880 minutes (48 hours).
- worker
Type String - The type of predefined worker that is allocated when an ML Transform runs. Accepts a value of
Standard
,G.1X
, orG.2X
. Required withnumber_of_workers
.
Outputs
All input properties are implicitly available as output properties. Additionally, the MLTransform resource produces the following output properties:
- Arn string
- Amazon Resource Name (ARN) of Glue ML Transform.
- Id string
- The provider-assigned unique ID for this managed resource.
- Label
Count int - The number of labels available for this transform.
- Schemas
List<MLTransform
Schema> - The object that represents the schema that this transform accepts. see Schema.
- Dictionary<string, string>
- A map of tags assigned to the resource, including those inherited from the provider
default_tags
configuration block.
- Arn string
- Amazon Resource Name (ARN) of Glue ML Transform.
- Id string
- The provider-assigned unique ID for this managed resource.
- Label
Count int - The number of labels available for this transform.
- Schemas
[]MLTransform
Schema - The object that represents the schema that this transform accepts. see Schema.
- map[string]string
- A map of tags assigned to the resource, including those inherited from the provider
default_tags
configuration block.
- arn String
- Amazon Resource Name (ARN) of Glue ML Transform.
- id String
- The provider-assigned unique ID for this managed resource.
- label
Count Integer - The number of labels available for this transform.
- schemas
List<MLTransform
Schema> - The object that represents the schema that this transform accepts. see Schema.
- Map<String,String>
- A map of tags assigned to the resource, including those inherited from the provider
default_tags
configuration block.
- arn string
- Amazon Resource Name (ARN) of Glue ML Transform.
- id string
- The provider-assigned unique ID for this managed resource.
- label
Count number - The number of labels available for this transform.
- schemas
MLTransform
Schema[] - The object that represents the schema that this transform accepts. see Schema.
- {[key: string]: string}
- A map of tags assigned to the resource, including those inherited from the provider
default_tags
configuration block.
- arn str
- Amazon Resource Name (ARN) of Glue ML Transform.
- id str
- The provider-assigned unique ID for this managed resource.
- label_
count int - The number of labels available for this transform.
- schemas
Sequence[MLTransform
Schema] - The object that represents the schema that this transform accepts. see Schema.
- Mapping[str, str]
- A map of tags assigned to the resource, including those inherited from the provider
default_tags
configuration block.
- arn String
- Amazon Resource Name (ARN) of Glue ML Transform.
- id String
- The provider-assigned unique ID for this managed resource.
- label
Count Number - The number of labels available for this transform.
- schemas List<Property Map>
- The object that represents the schema that this transform accepts. see Schema.
- Map<String>
- A map of tags assigned to the resource, including those inherited from the provider
default_tags
configuration block.
Look up Existing MLTransform Resource
Get an existing MLTransform 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?: MLTransformState, opts?: CustomResourceOptions): MLTransform
@staticmethod
def get(resource_name: str,
id: str,
opts: Optional[ResourceOptions] = None,
arn: Optional[str] = None,
description: Optional[str] = None,
glue_version: Optional[str] = None,
input_record_tables: Optional[Sequence[MLTransformInputRecordTableArgs]] = None,
label_count: Optional[int] = None,
max_capacity: Optional[float] = None,
max_retries: Optional[int] = None,
name: Optional[str] = None,
number_of_workers: Optional[int] = None,
parameters: Optional[MLTransformParametersArgs] = None,
role_arn: Optional[str] = None,
schemas: Optional[Sequence[MLTransformSchemaArgs]] = None,
tags: Optional[Mapping[str, str]] = None,
tags_all: Optional[Mapping[str, str]] = None,
timeout: Optional[int] = None,
worker_type: Optional[str] = None) -> MLTransform
func GetMLTransform(ctx *Context, name string, id IDInput, state *MLTransformState, opts ...ResourceOption) (*MLTransform, error)
public static MLTransform Get(string name, Input<string> id, MLTransformState? state, CustomResourceOptions? opts = null)
public static MLTransform get(String name, Output<String> id, MLTransformState 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.
- Arn string
- Amazon Resource Name (ARN) of Glue ML Transform.
- Description string
- Description of the ML Transform.
- Glue
Version string - The version of glue to use, for example "1.0". For information about available versions, see the AWS Glue Release Notes.
- Input
Record List<MLTransformTables Input Record Table> - A list of AWS Glue table definitions used by the transform. see Input Record Tables.
- Label
Count int - The number of labels available for this transform.
- Max
Capacity double - The number of AWS Glue data processing units (DPUs) that are allocated to task runs for this transform. You can allocate from
2
to100
DPUs; the default is10
.max_capacity
is a mutually exclusive option withnumber_of_workers
andworker_type
. - Max
Retries int - The maximum number of times to retry this ML Transform if it fails.
- Name string
- The name you assign to this ML Transform. It must be unique in your account.
- Number
Of intWorkers - The number of workers of a defined
worker_type
that are allocated when an ML Transform runs. Required withworker_type
. - Parameters
MLTransform
Parameters - The algorithmic parameters that are specific to the transform type used. Conditionally dependent on the transform type. see Parameters.
- Role
Arn string - The ARN of the IAM role associated with this ML Transform.
- Schemas
List<MLTransform
Schema> - The object that represents the schema that this transform accepts. see Schema.
- Dictionary<string, string>
- Key-value map of resource tags. .If configured with a provider
default_tags
configuration block present, tags with matching keys will overwrite those defined at the provider-level. - Dictionary<string, string>
- A map of tags assigned to the resource, including those inherited from the provider
default_tags
configuration block. - Timeout int
- The ML Transform timeout in minutes. The default is 2880 minutes (48 hours).
- Worker
Type string - The type of predefined worker that is allocated when an ML Transform runs. Accepts a value of
Standard
,G.1X
, orG.2X
. Required withnumber_of_workers
.
- Arn string
- Amazon Resource Name (ARN) of Glue ML Transform.
- Description string
- Description of the ML Transform.
- Glue
Version string - The version of glue to use, for example "1.0". For information about available versions, see the AWS Glue Release Notes.
- Input
Record []MLTransformTables Input Record Table Args - A list of AWS Glue table definitions used by the transform. see Input Record Tables.
- Label
Count int - The number of labels available for this transform.
- Max
Capacity float64 - The number of AWS Glue data processing units (DPUs) that are allocated to task runs for this transform. You can allocate from
2
to100
DPUs; the default is10
.max_capacity
is a mutually exclusive option withnumber_of_workers
andworker_type
. - Max
Retries int - The maximum number of times to retry this ML Transform if it fails.
- Name string
- The name you assign to this ML Transform. It must be unique in your account.
- Number
Of intWorkers - The number of workers of a defined
worker_type
that are allocated when an ML Transform runs. Required withworker_type
. - Parameters
MLTransform
Parameters Args - The algorithmic parameters that are specific to the transform type used. Conditionally dependent on the transform type. see Parameters.
- Role
Arn string - The ARN of the IAM role associated with this ML Transform.
- Schemas
[]MLTransform
Schema Args - The object that represents the schema that this transform accepts. see Schema.
- map[string]string
- Key-value map of resource tags. .If configured with a provider
default_tags
configuration block present, tags with matching keys will overwrite those defined at the provider-level. - map[string]string
- A map of tags assigned to the resource, including those inherited from the provider
default_tags
configuration block. - Timeout int
- The ML Transform timeout in minutes. The default is 2880 minutes (48 hours).
- Worker
Type string - The type of predefined worker that is allocated when an ML Transform runs. Accepts a value of
Standard
,G.1X
, orG.2X
. Required withnumber_of_workers
.
- arn String
- Amazon Resource Name (ARN) of Glue ML Transform.
- description String
- Description of the ML Transform.
- glue
Version String - The version of glue to use, for example "1.0". For information about available versions, see the AWS Glue Release Notes.
- input
Record List<MLTransformTables Input Record Table> - A list of AWS Glue table definitions used by the transform. see Input Record Tables.
- label
Count Integer - The number of labels available for this transform.
- max
Capacity Double - The number of AWS Glue data processing units (DPUs) that are allocated to task runs for this transform. You can allocate from
2
to100
DPUs; the default is10
.max_capacity
is a mutually exclusive option withnumber_of_workers
andworker_type
. - max
Retries Integer - The maximum number of times to retry this ML Transform if it fails.
- name String
- The name you assign to this ML Transform. It must be unique in your account.
- number
Of IntegerWorkers - The number of workers of a defined
worker_type
that are allocated when an ML Transform runs. Required withworker_type
. - parameters
MLTransform
Parameters - The algorithmic parameters that are specific to the transform type used. Conditionally dependent on the transform type. see Parameters.
- role
Arn String - The ARN of the IAM role associated with this ML Transform.
- schemas
List<MLTransform
Schema> - The object that represents the schema that this transform accepts. see Schema.
- Map<String,String>
- Key-value map of resource tags. .If configured with a provider
default_tags
configuration block present, tags with matching keys will overwrite those defined at the provider-level. - Map<String,String>
- A map of tags assigned to the resource, including those inherited from the provider
default_tags
configuration block. - timeout Integer
- The ML Transform timeout in minutes. The default is 2880 minutes (48 hours).
- worker
Type String - The type of predefined worker that is allocated when an ML Transform runs. Accepts a value of
Standard
,G.1X
, orG.2X
. Required withnumber_of_workers
.
- arn string
- Amazon Resource Name (ARN) of Glue ML Transform.
- description string
- Description of the ML Transform.
- glue
Version string - The version of glue to use, for example "1.0". For information about available versions, see the AWS Glue Release Notes.
- input
Record MLTransformTables Input Record Table[] - A list of AWS Glue table definitions used by the transform. see Input Record Tables.
- label
Count number - The number of labels available for this transform.
- max
Capacity number - The number of AWS Glue data processing units (DPUs) that are allocated to task runs for this transform. You can allocate from
2
to100
DPUs; the default is10
.max_capacity
is a mutually exclusive option withnumber_of_workers
andworker_type
. - max
Retries number - The maximum number of times to retry this ML Transform if it fails.
- name string
- The name you assign to this ML Transform. It must be unique in your account.
- number
Of numberWorkers - The number of workers of a defined
worker_type
that are allocated when an ML Transform runs. Required withworker_type
. - parameters
MLTransform
Parameters - The algorithmic parameters that are specific to the transform type used. Conditionally dependent on the transform type. see Parameters.
- role
Arn string - The ARN of the IAM role associated with this ML Transform.
- schemas
MLTransform
Schema[] - The object that represents the schema that this transform accepts. see Schema.
- {[key: string]: string}
- Key-value map of resource tags. .If configured with a provider
default_tags
configuration block present, tags with matching keys will overwrite those defined at the provider-level. - {[key: string]: string}
- A map of tags assigned to the resource, including those inherited from the provider
default_tags
configuration block. - timeout number
- The ML Transform timeout in minutes. The default is 2880 minutes (48 hours).
- worker
Type string - The type of predefined worker that is allocated when an ML Transform runs. Accepts a value of
Standard
,G.1X
, orG.2X
. Required withnumber_of_workers
.
- arn str
- Amazon Resource Name (ARN) of Glue ML Transform.
- description str
- Description of the ML Transform.
- glue_
version str - The version of glue to use, for example "1.0". For information about available versions, see the AWS Glue Release Notes.
- input_
record_ Sequence[MLTransformtables Input Record Table Args] - A list of AWS Glue table definitions used by the transform. see Input Record Tables.
- label_
count int - The number of labels available for this transform.
- max_
capacity float - The number of AWS Glue data processing units (DPUs) that are allocated to task runs for this transform. You can allocate from
2
to100
DPUs; the default is10
.max_capacity
is a mutually exclusive option withnumber_of_workers
andworker_type
. - max_
retries int - The maximum number of times to retry this ML Transform if it fails.
- name str
- The name you assign to this ML Transform. It must be unique in your account.
- number_
of_ intworkers - The number of workers of a defined
worker_type
that are allocated when an ML Transform runs. Required withworker_type
. - parameters
MLTransform
Parameters Args - The algorithmic parameters that are specific to the transform type used. Conditionally dependent on the transform type. see Parameters.
- role_
arn str - The ARN of the IAM role associated with this ML Transform.
- schemas
Sequence[MLTransform
Schema Args] - The object that represents the schema that this transform accepts. see Schema.
- Mapping[str, str]
- Key-value map of resource tags. .If configured with a provider
default_tags
configuration block present, tags with matching keys will overwrite those defined at the provider-level. - Mapping[str, str]
- A map of tags assigned to the resource, including those inherited from the provider
default_tags
configuration block. - timeout int
- The ML Transform timeout in minutes. The default is 2880 minutes (48 hours).
- worker_
type str - The type of predefined worker that is allocated when an ML Transform runs. Accepts a value of
Standard
,G.1X
, orG.2X
. Required withnumber_of_workers
.
- arn String
- Amazon Resource Name (ARN) of Glue ML Transform.
- description String
- Description of the ML Transform.
- glue
Version String - The version of glue to use, for example "1.0". For information about available versions, see the AWS Glue Release Notes.
- input
Record List<Property Map>Tables - A list of AWS Glue table definitions used by the transform. see Input Record Tables.
- label
Count Number - The number of labels available for this transform.
- max
Capacity Number - The number of AWS Glue data processing units (DPUs) that are allocated to task runs for this transform. You can allocate from
2
to100
DPUs; the default is10
.max_capacity
is a mutually exclusive option withnumber_of_workers
andworker_type
. - max
Retries Number - The maximum number of times to retry this ML Transform if it fails.
- name String
- The name you assign to this ML Transform. It must be unique in your account.
- number
Of NumberWorkers - The number of workers of a defined
worker_type
that are allocated when an ML Transform runs. Required withworker_type
. - parameters Property Map
- The algorithmic parameters that are specific to the transform type used. Conditionally dependent on the transform type. see Parameters.
- role
Arn String - The ARN of the IAM role associated with this ML Transform.
- schemas List<Property Map>
- The object that represents the schema that this transform accepts. see Schema.
- Map<String>
- Key-value map of resource tags. .If configured with a provider
default_tags
configuration block present, tags with matching keys will overwrite those defined at the provider-level. - Map<String>
- A map of tags assigned to the resource, including those inherited from the provider
default_tags
configuration block. - timeout Number
- The ML Transform timeout in minutes. The default is 2880 minutes (48 hours).
- worker
Type String - The type of predefined worker that is allocated when an ML Transform runs. Accepts a value of
Standard
,G.1X
, orG.2X
. Required withnumber_of_workers
.
Supporting Types
MLTransformInputRecordTable, MLTransformInputRecordTableArgs
- Database
Name string - A database name in the AWS Glue Data Catalog.
- Table
Name string - A table name in the AWS Glue Data Catalog.
- Catalog
Id string - A unique identifier for the AWS Glue Data Catalog.
- Connection
Name string - The name of the connection to the AWS Glue Data Catalog.
- Database
Name string - A database name in the AWS Glue Data Catalog.
- Table
Name string - A table name in the AWS Glue Data Catalog.
- Catalog
Id string - A unique identifier for the AWS Glue Data Catalog.
- Connection
Name string - The name of the connection to the AWS Glue Data Catalog.
- database
Name String - A database name in the AWS Glue Data Catalog.
- table
Name String - A table name in the AWS Glue Data Catalog.
- catalog
Id String - A unique identifier for the AWS Glue Data Catalog.
- connection
Name String - The name of the connection to the AWS Glue Data Catalog.
- database
Name string - A database name in the AWS Glue Data Catalog.
- table
Name string - A table name in the AWS Glue Data Catalog.
- catalog
Id string - A unique identifier for the AWS Glue Data Catalog.
- connection
Name string - The name of the connection to the AWS Glue Data Catalog.
- database_
name str - A database name in the AWS Glue Data Catalog.
- table_
name str - A table name in the AWS Glue Data Catalog.
- catalog_
id str - A unique identifier for the AWS Glue Data Catalog.
- connection_
name str - The name of the connection to the AWS Glue Data Catalog.
- database
Name String - A database name in the AWS Glue Data Catalog.
- table
Name String - A table name in the AWS Glue Data Catalog.
- catalog
Id String - A unique identifier for the AWS Glue Data Catalog.
- connection
Name String - The name of the connection to the AWS Glue Data Catalog.
MLTransformParameters, MLTransformParametersArgs
- Find
Matches MLTransformParameters Parameters Find Matches Parameters - The parameters for the find matches algorithm. see Find Matches Parameters.
- Transform
Type string - The type of machine learning transform. For information about the types of machine learning transforms, see Creating Machine Learning Transforms.
- Find
Matches MLTransformParameters Parameters Find Matches Parameters - The parameters for the find matches algorithm. see Find Matches Parameters.
- Transform
Type string - The type of machine learning transform. For information about the types of machine learning transforms, see Creating Machine Learning Transforms.
- find
Matches MLTransformParameters Parameters Find Matches Parameters - The parameters for the find matches algorithm. see Find Matches Parameters.
- transform
Type String - The type of machine learning transform. For information about the types of machine learning transforms, see Creating Machine Learning Transforms.
- find
Matches MLTransformParameters Parameters Find Matches Parameters - The parameters for the find matches algorithm. see Find Matches Parameters.
- transform
Type string - The type of machine learning transform. For information about the types of machine learning transforms, see Creating Machine Learning Transforms.
- find_
matches_ MLTransformparameters Parameters Find Matches Parameters - The parameters for the find matches algorithm. see Find Matches Parameters.
- transform_
type str - The type of machine learning transform. For information about the types of machine learning transforms, see Creating Machine Learning Transforms.
- find
Matches Property MapParameters - The parameters for the find matches algorithm. see Find Matches Parameters.
- transform
Type String - The type of machine learning transform. For information about the types of machine learning transforms, see Creating Machine Learning Transforms.
MLTransformParametersFindMatchesParameters, MLTransformParametersFindMatchesParametersArgs
- Accuracy
Cost doubleTrade Off - The value that is selected when tuning your transform for a balance between accuracy and cost.
- Enforce
Provided boolLabels - The value to switch on or off to force the output to match the provided labels from users.
- Precision
Recall doubleTrade Off - The value selected when tuning your transform for a balance between precision and recall.
- Primary
Key stringColumn Name - The name of a column that uniquely identifies rows in the source table.
- Accuracy
Cost float64Trade Off - The value that is selected when tuning your transform for a balance between accuracy and cost.
- Enforce
Provided boolLabels - The value to switch on or off to force the output to match the provided labels from users.
- Precision
Recall float64Trade Off - The value selected when tuning your transform for a balance between precision and recall.
- Primary
Key stringColumn Name - The name of a column that uniquely identifies rows in the source table.
- accuracy
Cost DoubleTrade Off - The value that is selected when tuning your transform for a balance between accuracy and cost.
- enforce
Provided BooleanLabels - The value to switch on or off to force the output to match the provided labels from users.
- precision
Recall DoubleTrade Off - The value selected when tuning your transform for a balance between precision and recall.
- primary
Key StringColumn Name - The name of a column that uniquely identifies rows in the source table.
- accuracy
Cost numberTrade Off - The value that is selected when tuning your transform for a balance between accuracy and cost.
- enforce
Provided booleanLabels - The value to switch on or off to force the output to match the provided labels from users.
- precision
Recall numberTrade Off - The value selected when tuning your transform for a balance between precision and recall.
- primary
Key stringColumn Name - The name of a column that uniquely identifies rows in the source table.
- accuracy_
cost_ floattrade_ off - The value that is selected when tuning your transform for a balance between accuracy and cost.
- enforce_
provided_ boollabels - The value to switch on or off to force the output to match the provided labels from users.
- precision_
recall_ floattrade_ off - The value selected when tuning your transform for a balance between precision and recall.
- primary_
key_ strcolumn_ name - The name of a column that uniquely identifies rows in the source table.
- accuracy
Cost NumberTrade Off - The value that is selected when tuning your transform for a balance between accuracy and cost.
- enforce
Provided BooleanLabels - The value to switch on or off to force the output to match the provided labels from users.
- precision
Recall NumberTrade Off - The value selected when tuning your transform for a balance between precision and recall.
- primary
Key StringColumn Name - The name of a column that uniquely identifies rows in the source table.
MLTransformSchema, MLTransformSchemaArgs
Import
Using pulumi import
, import Glue ML Transforms using id
. For example:
$ pulumi import aws:glue/mLTransform:MLTransform example tfm-c2cafbe83b1c575f49eaca9939220e2fcd58e2d5
To learn more about importing existing cloud resources, see Importing resources.
Package Details
- Repository
- AWS Classic pulumi/pulumi-aws
- License
- Apache-2.0
- Notes
- This Pulumi package is based on the
aws
Terraform Provider.