Data warehousing with AWS Glue

For data warehousing with AWS Glue, a basic setup often involves creating an AWS Glue Job and possibly an AWS Glue Workflow to manage and orchestrate transformations. The Glue Job will execute your ETL (Extract, Transform, Load) script stored in an S3 bucket, transforming your data as per your requirements.

Here is a simple example of a Pulumi program written in C# that sets up a Glue Job:

using Pulumi;
using Aws = Pulumi.Aws;

class MyStack : Stack
{
    public MyStack()
    {
        // Create a role for the Glue job
        var glueJobRole = new Aws.Iam.Role("myGlueJobRole", new Aws.Iam.RoleArgs
        {
            AssumeRolePolicy = @"{
                  ""Version"": ""2012-10-17"",
                  ""Statement"": [
                    {
                      ""Action"": ""sts:AssumeRole"",
                      ""Principal"": {
                        ""Service"": ""glue.amazonaws.com""
                      },
                      ""Effect"": ""Allow"",
                      ""Sid"": """"
                    }
                  ]
                }"
        });
        
        // Add Policy to the Glue job role
        var glueJobRolePolicy = new Aws.Iam.RolePolicy("myGlueJobRolePolicy", new Aws.Iam.RolePolicyArgs
        {
            Role = glueJobRole.Id,
            Policy = @"{
                    ""Version"": ""2012-10-17"",
                    ""Statement"": [
                        {
                            ""Action"": [
                                ""s3:GetObject"",
                                ""s3:PutObject"",
                                ""s3:ListBucket"",
                                ""glue:GetTable"",
                                ""glue:GetTables"",
                                ""glue:BatchGetPartition""
                            ],
                            ""Effect"": ""Allow"",
                            ""Resource"": ""*""
                        }
                    ]
                }"
        });

        // Create a Glue job
        var myGlueJob = new Aws.Glue.Job("myGlueJob", new Aws.Glue.JobArgs
        {
            Command = new Aws.Glue.Inputs.JobCommandArgs
            {
                Name = "glueetl",
                ScriptLocation = "s3://my-bucket/my-etl-script.py" // replace with your script location
            },
            RoleArn = glueJobRole.Arn,
            DefaultArguments = 
            {
                // Enable bookmarking feature to track data that has already been processed during previous runs of an ETL job
                { "--job-bookmark-option", "job-bookmark-enable" }
            },
        });

    }
}

class Program
{
    static void Main(string[] args)
    {
        Deployment.RunAsync<MyStack>().Wait();
    }
}

In this code:

1. An IAM Role is created for AWS Glue.
2. The necessary permissions for the Role are added in an IAM Role Policy.
3. An AWS Glue ETL Job is created which uses an ETL script from an S3 location and runs with a role that has the necessary permissions. The command name glueetl is used to denote that the AWS Glue ETL engine should be used to run the script.

Please replace "s3://my-bucket/my-etl-script.py" with the actual location of your ETL script.

You can learn more about the aws.glue.Job and aws.Iam.Role and aws.Iam.RolePolicy on the Pulumi Registry.