Step 1: Create the state machine and provision resources Step 2: Run the state machine Example State Machine Code IAM Example

Keep data up to date (Amazon Athena, Amazon S3, Amazon Glue)

This sample project demonstrates how to query a target table to get current data with Amazon Glue Catalog, then update it with new data from other sources using Amazon Athena.

In this project, the Step Functions state machine calls Amazon Glue Catalog to verify if a target table exists in an Amazon S3 Bucket. If no table is found one, it will create a new table. Then, Step Functions runs an Athena query to add rows to the target table from a different data source: first querying the target table to get the most recent date, then querying the source table for more recent data and inserting it into the target table.

Step 1: Create the state machine and provision resources

Open the Step Functions console and choose Create state machine.
Type Keep data up to date in the search box, and then choose Keep data up to date from the search results that are returned.
Choose Next to continue.
Step Functions lists the Amazon Web Services used in the sample project you selected. It also shows a workflow graph for the sample project. Deploy this project to your Amazon Web Services account or use it as a starting point for building your own projects. Based on how you want to proceed, choose Run a demo or Build on it.

This sample project deploys the following resources:
- An Amazon S3 bucket
- Amazon Athena queries
- An Amazon Glue Data Catalog call
- An Amazon Step Functions state machine
- Related Amazon Identity and Access Management (IAM) roles
The following image shows the workflow graph for the Keep data up to date sample project:
Choose Use template to continue with your selection.
Do one of the following:
- If you selected Build on it, Step Functions creates the workflow prototype for the sample project you selected. Step Functions doesn't deploy the resources listed in the workflow definition.
  
  In Workflow Studio's Design mode, drag and drop states from the States browser to continue building your workflow protoype. Or switch to the Code mode that provides an integrated code editor similar to VS Code for updating the Amazon States Language (ASL) definition of your state machine within the Step Functions console. For more information about using Workflow Studio to build your state machines, see Using Workflow Studio.
  
  Important
  Remember to update the placeholder Amazon Resource Name (ARN) for the resources used in the sample project before you run your workflow.
- If you selected Run a demo, Step Functions creates a read-only sample project which uses an Amazon CloudFormation template to deploy the Amazon resources listed in that template to your Amazon Web Services account.
  
  Tip
  To view the state machine definition of the sample project, choose Code.
  
  When you're ready, choose Deploy and run to deploy the sample project and create the resources.
  
  It can take up to 10 minutes for these resources and related IAM permissions to be created. While your resources are being deployed, you can open the CloudFormation Stack ID link to see which resources are being provisioned.
  
  After all the resources in the sample project are created, you can see the new sample project listed on the State machines page.
  
  Important
  Standard charges may apply for each service used in the CloudFormation template.

Step 2: Run the state machine

On the State machines page, choose your sample project.
On the sample project page, choose Start execution.
In the Start execution dialog box, do the following:
1. (Optional) To identify your execution, you can specify a name for it in the Name box. By default, Step Functions automatically generates a unique execution name.
  
  Note
  Step Functions allows you to create names for state machines, executions, activities, and labels that contain non-ASCII characters. These non-ASCII names don't work with Amazon CloudWatch. To ensure that you can track CloudWatch metrics, choose a name that uses only ASCII characters.
2. (Optional) In the Input box, enter input values in JSON format to run your workflow.
  
  If you chose to Run a demo, you need not provide any execution input.
3. Choose Start execution.
4. The Step Functions console directs you to a page that's titled with your execution ID. This page is known as the Execution Details page. On this page, you can review the execution results as the execution progresses or after it's complete.
  
  To review the execution results, choose individual states on the Graph view, and then choose the individual tabs on the Step details pane to view each state's details including input, output, and definition respectively. For details about the execution information you can view on the Execution Details page, see Execution Details page – Interface overview.

Example State Machine Code

The state machine in this sample project integrates with Amazon S3, Amazon Glue, and Amazon Athena by passing parameters directly to those resources.

Browse through this example state machine to see how Step Functions controls Amazon S3, Amazon Glue, and Amazon Athena by connecting to the Amazon Resource Name (ARN) in the Resource field, and by passing Parameters to the service API.

For more information about how Amazon Step Functions can control other Amazon services, see Using Amazon Step Functions with other services.


{
    "Comment": "An example demonstrates how to use Athena to query a target table to get current data, then update it with new data from other sources.",
    "StartAt": "Get Target Table",
    "States": {
      "Get Target Table": {
        "Type": "Task",
        "Parameters": {
          "DatabaseName": "<GLUE_DATABASE_NAME>",
          "Name": "target"
        },
        "Catch": [
          {
            "ErrorEquals": [
              "Glue.EntityNotFoundException"
            ],
            "Next": "Create Target Table"
          }
        ],
        "Resource": "arn:aws-cn:states:::aws-sdk:glue:getTable",
        "Next": "Update Target Table"
      },
      "Create Target Table": {
        "Resource": "arn:aws-cn:states:::athena:startQueryExecution.sync",
        "Parameters": {
            "QueryString": "<ATHENA_QUERYSTRING>",
            "WorkGroup": "<ATHENA_WORKGROUP>"
        },
        "Type": "Task",
        "Next": "Update Target Table"
      },
      "Update Target Table": {
        "Resource": "arn:aws-cn:states:::athena:startQueryExecution.sync",
        "Parameters": {
            "QueryString": "<ATHENA_QUERYSTRING>",
            "WorkGroup": "<ATHENA_WORKGROUP>"
        },
        "Type": "Task",
        "End": true
      }
    }
  }

IAM Example

This example Amazon Identity and Access Management (IAM) policy generated by the sample project includes the least privilege necessary to execute the state machine and related resources. We recommend that you include only those permissions that are necessary in your IAM policies.

AthenaStartQueryExecution



    "Version": "2012-10-17",
    "Statement": [
        {
            "Effect": "Allow",
            "Action": [
                "athena:startQueryExecution",
                "athena:stopQueryExecution",
                "athena:getQueryExecution",
                "athena:getDataCatalog"
            ],
            "Resource": [
                "arn:aws-cn:athena:us-west-2:123456789012:workgroup/stepfunctions-athena-sample-project-workgroup-26ujlyawxg",
                "arn:aws-cn:athena:us-west-2:123456789012:datacatalog/*"
            ]
        },
        {
            "Effect": "Allow",
            "Action": [
                "s3:GetBucketLocation",
                "s3:GetObject",
                "s3:ListBucket",
                "s3:ListBucketMultipartUploads",
                "s3:ListMultipartUploadParts",
                "s3:AbortMultipartUpload",
                "s3:CreateBucket",
                "s3:PutObject"
            ],
            "Resource": [
                "arn:aws:s3:::*"
            ]
        },
        {
            "Effect": "Allow",
            "Action": [
                "glue:CreateDatabase",
                "glue:GetDatabase",
                "glue:GetDatabases",
                "glue:UpdateDatabase",
                "glue:DeleteDatabase",
                "glue:CreateTable",
                "glue:UpdateTable",
                "glue:GetTable",
                "glue:GetTables",
                "glue:DeleteTable",
                "glue:BatchDeleteTable",
                "glue:BatchCreatePartition",
                "glue:CreatePartition",
                "glue:UpdatePartition",
                "glue:GetPartition",
                "glue:GetPartitions",
                "glue:BatchGetPartition",
                "glue:DeletePartition",
                "glue:BatchDeletePartition"
            ],
            "Resource": [
                "arn:aws-cn::glue:us-west-2:123456789012:catalog",
                "arn:aws-cn::glue:us-west-2:123456789012:database/*",
                "arn:aws-cn::glue:us-west-2:123456789012:table/*",
                "arn:aws-cn::glue:us-west-2:123456789012:userDefinedFunction/*"
            ]
        },
        {
            "Effect": "Allow",
            "Action": [
                "lakeformation:GetDataAccess"
            ],
            "Resource": [
                "*"
            ]
        }
    ]
}

For information about how to configure IAM when using Step Functions with other Amazon services, see IAM Policies for integrated services.

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Query large datasets (Amazon Athena, Amazon S3, Amazon Glue, Amazon SNS)

Manage an Amazon EKS cluster