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Build cloud applications and infrastructure by combining the safety and reliability of infrastructure as code with the power of the Kotlin programming language.
@file:Suppress("NAME_SHADOWING", "DEPRECATION")
package com.pulumi.aws.glue.kotlin
import com.pulumi.aws.glue.MLTransformArgs.builder
import com.pulumi.aws.glue.kotlin.inputs.MLTransformInputRecordTableArgs
import com.pulumi.aws.glue.kotlin.inputs.MLTransformInputRecordTableArgsBuilder
import com.pulumi.aws.glue.kotlin.inputs.MLTransformParametersArgs
import com.pulumi.aws.glue.kotlin.inputs.MLTransformParametersArgsBuilder
import com.pulumi.core.Output
import com.pulumi.core.Output.of
import com.pulumi.kotlin.ConvertibleToJava
import com.pulumi.kotlin.PulumiTagMarker
import com.pulumi.kotlin.applySuspend
import kotlin.Double
import kotlin.Int
import kotlin.Pair
import kotlin.String
import kotlin.Suppress
import kotlin.Unit
import kotlin.collections.List
import kotlin.collections.Map
import kotlin.jvm.JvmName
/**
* Provides a Glue ML Transform resource.
* ## Example Usage
*
* ```typescript
* 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],
* });
* ```
* ```python
* 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]))
* ```
* ```csharp
* 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,
* },
* });
* });
* ```
* ```go
* 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
* })
* }
* ```
* ```java
* 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());
* }
* }
* ```
* ```yaml
* 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
* ```
*
* ## Import
* Using `pulumi import`, import Glue ML Transforms using `id`. For example:
* ```sh
* $ pulumi import aws:glue/mLTransform:MLTransform example tfm-c2cafbe83b1c575f49eaca9939220e2fcd58e2d5
* ```
* @property description Description of the ML Transform.
* @property glueVersion The version of glue to use, for example "1.0". For information about available versions, see the [AWS Glue Release Notes](https://docs.aws.amazon.com/glue/latest/dg/release-notes.html).
* @property inputRecordTables A list of AWS Glue table definitions used by the transform. see Input Record Tables.
* @property maxCapacity The number of AWS Glue data processing units (DPUs) that are allocated to task runs for this transform. You can allocate from `2` to `100` DPUs; the default is `10`. `max_capacity` is a mutually exclusive option with `number_of_workers` and `worker_type`.
* @property maxRetries The maximum number of times to retry this ML Transform if it fails.
* @property name The name you assign to this ML Transform. It must be unique in your account.
* @property numberOfWorkers The number of workers of a defined `worker_type` that are allocated when an ML Transform runs. Required with `worker_type`.
* @property parameters The algorithmic parameters that are specific to the transform type used. Conditionally dependent on the transform type. see Parameters.
* @property roleArn The ARN of the IAM role associated with this ML Transform.
* @property tags 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.
* @property timeout The ML Transform timeout in minutes. The default is 2880 minutes (48 hours).
* @property workerType The type of predefined worker that is allocated when an ML Transform runs. Accepts a value of `Standard`, `G.1X`, or `G.2X`. Required with `number_of_workers`.
*/
public data class MLTransformArgs(
public val description: Output? = null,
public val glueVersion: Output? = null,
public val inputRecordTables: Output>? = null,
public val maxCapacity: Output? = null,
public val maxRetries: Output? = null,
public val name: Output? = null,
public val numberOfWorkers: Output? = null,
public val parameters: Output? = null,
public val roleArn: Output? = null,
public val tags: Output>? = null,
public val timeout: Output? = null,
public val workerType: Output? = null,
) : ConvertibleToJava {
override fun toJava(): com.pulumi.aws.glue.MLTransformArgs =
com.pulumi.aws.glue.MLTransformArgs.builder()
.description(description?.applyValue({ args0 -> args0 }))
.glueVersion(glueVersion?.applyValue({ args0 -> args0 }))
.inputRecordTables(
inputRecordTables?.applyValue({ args0 ->
args0.map({ args0 ->
args0.let({ args0 ->
args0.toJava()
})
})
}),
)
.maxCapacity(maxCapacity?.applyValue({ args0 -> args0 }))
.maxRetries(maxRetries?.applyValue({ args0 -> args0 }))
.name(name?.applyValue({ args0 -> args0 }))
.numberOfWorkers(numberOfWorkers?.applyValue({ args0 -> args0 }))
.parameters(parameters?.applyValue({ args0 -> args0.let({ args0 -> args0.toJava() }) }))
.roleArn(roleArn?.applyValue({ args0 -> args0 }))
.tags(tags?.applyValue({ args0 -> args0.map({ args0 -> args0.key.to(args0.value) }).toMap() }))
.timeout(timeout?.applyValue({ args0 -> args0 }))
.workerType(workerType?.applyValue({ args0 -> args0 })).build()
}
/**
* Builder for [MLTransformArgs].
*/
@PulumiTagMarker
public class MLTransformArgsBuilder internal constructor() {
private var description: Output? = null
private var glueVersion: Output? = null
private var inputRecordTables: Output>? = null
private var maxCapacity: Output? = null
private var maxRetries: Output? = null
private var name: Output? = null
private var numberOfWorkers: Output? = null
private var parameters: Output? = null
private var roleArn: Output? = null
private var tags: Output>? = null
private var timeout: Output? = null
private var workerType: Output? = null
/**
* @param value Description of the ML Transform.
*/
@JvmName("fllgfcngevwmfbjx")
public suspend fun description(`value`: Output) {
this.description = value
}
/**
* @param value The version of glue to use, for example "1.0". For information about available versions, see the [AWS Glue Release Notes](https://docs.aws.amazon.com/glue/latest/dg/release-notes.html).
*/
@JvmName("fkhvvvvetgbqpwun")
public suspend fun glueVersion(`value`: Output) {
this.glueVersion = value
}
/**
* @param value A list of AWS Glue table definitions used by the transform. see Input Record Tables.
*/
@JvmName("soukhvhiltdluekv")
public suspend fun inputRecordTables(`value`: Output>) {
this.inputRecordTables = value
}
@JvmName("klotpfdbalcujkpu")
public suspend fun inputRecordTables(vararg values: Output) {
this.inputRecordTables = Output.all(values.asList())
}
/**
* @param values A list of AWS Glue table definitions used by the transform. see Input Record Tables.
*/
@JvmName("hcnovlfviitbavdo")
public suspend fun inputRecordTables(values: List>) {
this.inputRecordTables = Output.all(values)
}
/**
* @param value The number of AWS Glue data processing units (DPUs) that are allocated to task runs for this transform. You can allocate from `2` to `100` DPUs; the default is `10`. `max_capacity` is a mutually exclusive option with `number_of_workers` and `worker_type`.
*/
@JvmName("fksplcqpgvhjiqax")
public suspend fun maxCapacity(`value`: Output) {
this.maxCapacity = value
}
/**
* @param value The maximum number of times to retry this ML Transform if it fails.
*/
@JvmName("lrpcamtsphpdqyfw")
public suspend fun maxRetries(`value`: Output) {
this.maxRetries = value
}
/**
* @param value The name you assign to this ML Transform. It must be unique in your account.
*/
@JvmName("ruucdlenbnbhbjad")
public suspend fun name(`value`: Output) {
this.name = value
}
/**
* @param value The number of workers of a defined `worker_type` that are allocated when an ML Transform runs. Required with `worker_type`.
*/
@JvmName("iewdgbyptjopnpnk")
public suspend fun numberOfWorkers(`value`: Output) {
this.numberOfWorkers = value
}
/**
* @param value The algorithmic parameters that are specific to the transform type used. Conditionally dependent on the transform type. see Parameters.
*/
@JvmName("ismvilijdeghcjfx")
public suspend fun parameters(`value`: Output) {
this.parameters = value
}
/**
* @param value The ARN of the IAM role associated with this ML Transform.
*/
@JvmName("gisuyrkdtkirqbfa")
public suspend fun roleArn(`value`: Output) {
this.roleArn = value
}
/**
* @param value 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.
*/
@JvmName("upeyiadwrebpwsmm")
public suspend fun tags(`value`: Output>) {
this.tags = value
}
/**
* @param value The ML Transform timeout in minutes. The default is 2880 minutes (48 hours).
*/
@JvmName("whumvsftsphqnxob")
public suspend fun timeout(`value`: Output) {
this.timeout = value
}
/**
* @param value The type of predefined worker that is allocated when an ML Transform runs. Accepts a value of `Standard`, `G.1X`, or `G.2X`. Required with `number_of_workers`.
*/
@JvmName("hpbcojehynilohxx")
public suspend fun workerType(`value`: Output) {
this.workerType = value
}
/**
* @param value Description of the ML Transform.
*/
@JvmName("rcpbwupbcejrmkni")
public suspend fun description(`value`: String?) {
val toBeMapped = value
val mapped = toBeMapped?.let({ args0 -> of(args0) })
this.description = mapped
}
/**
* @param value The version of glue to use, for example "1.0". For information about available versions, see the [AWS Glue Release Notes](https://docs.aws.amazon.com/glue/latest/dg/release-notes.html).
*/
@JvmName("xahmiblwdtvygley")
public suspend fun glueVersion(`value`: String?) {
val toBeMapped = value
val mapped = toBeMapped?.let({ args0 -> of(args0) })
this.glueVersion = mapped
}
/**
* @param value A list of AWS Glue table definitions used by the transform. see Input Record Tables.
*/
@JvmName("eggsqnrsuwfggeyq")
public suspend fun inputRecordTables(`value`: List?) {
val toBeMapped = value
val mapped = toBeMapped?.let({ args0 -> of(args0) })
this.inputRecordTables = mapped
}
/**
* @param argument A list of AWS Glue table definitions used by the transform. see Input Record Tables.
*/
@JvmName("pygfhvveefifnhxo")
public suspend fun inputRecordTables(argument: List Unit>) {
val toBeMapped = argument.toList().map {
MLTransformInputRecordTableArgsBuilder().applySuspend {
it()
}.build()
}
val mapped = of(toBeMapped)
this.inputRecordTables = mapped
}
/**
* @param argument A list of AWS Glue table definitions used by the transform. see Input Record Tables.
*/
@JvmName("ydfygusoaomaiqhy")
public suspend fun inputRecordTables(vararg argument: suspend MLTransformInputRecordTableArgsBuilder.() -> Unit) {
val toBeMapped = argument.toList().map {
MLTransformInputRecordTableArgsBuilder().applySuspend {
it()
}.build()
}
val mapped = of(toBeMapped)
this.inputRecordTables = mapped
}
/**
* @param argument A list of AWS Glue table definitions used by the transform. see Input Record Tables.
*/
@JvmName("ggsmkonapxwwbatj")
public suspend fun inputRecordTables(argument: suspend MLTransformInputRecordTableArgsBuilder.() -> Unit) {
val toBeMapped = listOf(
MLTransformInputRecordTableArgsBuilder().applySuspend {
argument()
}.build(),
)
val mapped = of(toBeMapped)
this.inputRecordTables = mapped
}
/**
* @param values A list of AWS Glue table definitions used by the transform. see Input Record Tables.
*/
@JvmName("rwkqhlaflllfmqck")
public suspend fun inputRecordTables(vararg values: MLTransformInputRecordTableArgs) {
val toBeMapped = values.toList()
val mapped = toBeMapped.let({ args0 -> of(args0) })
this.inputRecordTables = mapped
}
/**
* @param value The number of AWS Glue data processing units (DPUs) that are allocated to task runs for this transform. You can allocate from `2` to `100` DPUs; the default is `10`. `max_capacity` is a mutually exclusive option with `number_of_workers` and `worker_type`.
*/
@JvmName("oshgkdlxmcqmsswu")
public suspend fun maxCapacity(`value`: Double?) {
val toBeMapped = value
val mapped = toBeMapped?.let({ args0 -> of(args0) })
this.maxCapacity = mapped
}
/**
* @param value The maximum number of times to retry this ML Transform if it fails.
*/
@JvmName("endugbygifpmldut")
public suspend fun maxRetries(`value`: Int?) {
val toBeMapped = value
val mapped = toBeMapped?.let({ args0 -> of(args0) })
this.maxRetries = mapped
}
/**
* @param value The name you assign to this ML Transform. It must be unique in your account.
*/
@JvmName("qairfjircwduaghc")
public suspend fun name(`value`: String?) {
val toBeMapped = value
val mapped = toBeMapped?.let({ args0 -> of(args0) })
this.name = mapped
}
/**
* @param value The number of workers of a defined `worker_type` that are allocated when an ML Transform runs. Required with `worker_type`.
*/
@JvmName("cbydnfpyeovmyodp")
public suspend fun numberOfWorkers(`value`: Int?) {
val toBeMapped = value
val mapped = toBeMapped?.let({ args0 -> of(args0) })
this.numberOfWorkers = mapped
}
/**
* @param value The algorithmic parameters that are specific to the transform type used. Conditionally dependent on the transform type. see Parameters.
*/
@JvmName("tqptrwxtjnmcwgeg")
public suspend fun parameters(`value`: MLTransformParametersArgs?) {
val toBeMapped = value
val mapped = toBeMapped?.let({ args0 -> of(args0) })
this.parameters = mapped
}
/**
* @param argument The algorithmic parameters that are specific to the transform type used. Conditionally dependent on the transform type. see Parameters.
*/
@JvmName("wxqyguqlpfmvnkvc")
public suspend fun parameters(argument: suspend MLTransformParametersArgsBuilder.() -> Unit) {
val toBeMapped = MLTransformParametersArgsBuilder().applySuspend { argument() }.build()
val mapped = of(toBeMapped)
this.parameters = mapped
}
/**
* @param value The ARN of the IAM role associated with this ML Transform.
*/
@JvmName("pvorrwpmhmtafctr")
public suspend fun roleArn(`value`: String?) {
val toBeMapped = value
val mapped = toBeMapped?.let({ args0 -> of(args0) })
this.roleArn = mapped
}
/**
* @param value 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.
*/
@JvmName("wafmbidyrllovjev")
public suspend fun tags(`value`: Map?) {
val toBeMapped = value
val mapped = toBeMapped?.let({ args0 -> of(args0) })
this.tags = mapped
}
/**
* @param values 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.
*/
@JvmName("uriijanuomsshldm")
public fun tags(vararg values: Pair) {
val toBeMapped = values.toMap()
val mapped = toBeMapped.let({ args0 -> of(args0) })
this.tags = mapped
}
/**
* @param value The ML Transform timeout in minutes. The default is 2880 minutes (48 hours).
*/
@JvmName("ntojvwlrwjeyjvdm")
public suspend fun timeout(`value`: Int?) {
val toBeMapped = value
val mapped = toBeMapped?.let({ args0 -> of(args0) })
this.timeout = mapped
}
/**
* @param value The type of predefined worker that is allocated when an ML Transform runs. Accepts a value of `Standard`, `G.1X`, or `G.2X`. Required with `number_of_workers`.
*/
@JvmName("dguiwqlvbtnqhcmw")
public suspend fun workerType(`value`: String?) {
val toBeMapped = value
val mapped = toBeMapped?.let({ args0 -> of(args0) })
this.workerType = mapped
}
internal fun build(): MLTransformArgs = MLTransformArgs(
description = description,
glueVersion = glueVersion,
inputRecordTables = inputRecordTables,
maxCapacity = maxCapacity,
maxRetries = maxRetries,
name = name,
numberOfWorkers = numberOfWorkers,
parameters = parameters,
roleArn = roleArn,
tags = tags,
timeout = timeout,
workerType = workerType,
)
}
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