How to deploy an app on SQL Server 2019 big data cluster (preview)

This article describes how to deploy and manage R and Python script as an application inside a SQL Server 2019 big data cluster (preview).

R and Python applications are deployed and managed with the mssqlctl-pre command-line utility which is included in CTP 2.2. This article provides examples of how to deploy these R and Python scripts as apps from the command line.


You must have a SQL Server 2019 big data cluster configured. For more information, see How to deploy SQL Server big data cluster on Kubernetes.


The mssqlctl-pre command-line utility is provided to preview the Python and R application deployment feature. Use the following command to install the utility:

pip install -r --trusted-host


In CTP 2.2 you can create, delete, list, and run an R or Python application. The following table describes the application deployment commands that you can use with mssqlctl-pre.

Command Description
mssqlctl-pre login Log into a SQL Server big data cluster
mssqlctl-pre app create Create an app
mssqlctl-pre app list List deployed apps
mssqlctl-pre app delete Delete an app
mssqlctl-pre app run List running apps

You can get help with the --help parameter as in the following example:

mssqlctl-pre app create --help

The following sections describe these commands in more detail.

Log in

Before configuring R and Python applications, first log into your SQL Server big data cluster with the mssqlctl-pre login command. Specify the external IP address of the service-proxy-lb or service-proxy-nodeport services (for example: https://ip-address:30777) along with the user name and password to the cluster.

You can get the IP address of the service-proxy-lb or service-proxy-nodeport service by running this command in a bash or cmd window:

kubectl get svc service-proxy-lb -n <name of your cluster>
mssqlctl-pre login -e https://<ip-address-of-service-proxy-lb>:30777 -u <user-name> -p <password>

Create an app

To create an application, you pass Python or R code files to mssqlctl-pre with the app create command. These files reside locally on the machine that you are creating the app from.

Use the following syntax to create a new app in your big data cluster:

mssqlctl-pre app create -n <app_name> -v <version_number> -r <runtime> -i <path_to_code_init> -c <path_to_code> --inputs <input_params> --outputs <output_params> 

The following command shows an example of what this command might look like:
def add(x,y):
        result = x+y
        return result;

To try this, save the above lines of code to your local directory as and run the command below

mssqlctl-pre app create --name add-app --version v1 --runtime Python --code ./  --inputs x=int,y=int --outputs result=int 

You can check if the app is deployed using the list command:

mssqlctl-pre app list

If the deployment is not complete you should see the "state" show "Creating":

    "name": "add-app",
    "state": "Creating",
    "version": "v1"

After the deployment is successful you should see the "state" change to "Ready" status:

    "name": "add-app",
    "state": "Ready",
    "version": "v1"

List an app

You can list any apps that were successfully created with the app list command.

The following command lists all available applications in your big data cluster:

mssqlctl-pre app list

If you specify a name and version, it will list that specific app and its state (Creating or Ready):

mssqlctl-pre app list --name <app_name> --version <app_version>

The following example demonstrates this command:

mssqlctl-pre app list --name add-app --version v1

You should see output similar to the following example:

    "name": "add-app",
    "state": "Ready",
    "version": "v1"

Run an app

If the app is in a "Ready" state, you can use it by running it with your specified input parameters. Use the following syntax to run an app:

mssqlctl-pre app run --name <app_name> --version <app_version> --inputs <inputs_params>

The following example command demonstrates the run command:

mssqlctl-pre app run --name add-app --version v1 --inputs x=1,y=2

If the run was successful, you should see your output as specified when you created the app. The following is an example.

  "changedFiles": [],
  "consoleOutput": "",
  "errorMessage": "",
  "outputFiles": {},
  "outputParameters": {
    "result": 3
  "success": true

Delete an app

To delete an app from your big data cluster, use the following syntax:

mssqlctl-pre app delete --name add-app --version v1

Next steps

You can also check out additional samples at

For more information about SQL Server big data clusters, see What are SQL Server 2019 big data clusters?.