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Samples on how to deploy applications to SQL Server big data cluster
Pre-requisites
- SQL Server big data cluster CTP 2.3 or later
mssqlctlCLI familiarity
If you are unfamiliar with mssqlctl please refer to - App Deployment in SQL Server big data cluster for more information.
- Tip mssqlctl app -h will display the various commands to manage the app
Available samples
Python
These samples demonstrates how you can deploy a simple Python app into SQL Server big data cluster as container app as web service that is swagger compliant for building your application.
R
These samples demonstrates how you can deploy a simple R app into SQL Server big data cluster as container app as web service that is swagger compliant for building your application.
This sample demonstrates the use of data frames
MLeap
This sample demonstrates how you use a MLeap bundle (a Spark model serialized in this format) and run it outside of Spark. The sample is based on the MLeap sample available here http://mleap-docs.combust.ml/mleap-serving/. We are using the MLeap Serving container that is published in Docker Hub. The MLeap Serving is deployed as container in SQL Server big data cluster as a container app with a web service that takes the Leap Frame as the input.
Sql Server Integration Services
This sample demonstrates how you can run SSIS applications as a containerized application leveraging the cron capability in Kubernetes. This example uses a Data Transformation Services Package File Format (DTSX) file developed using Visual Studio that, when executed, takes a database backup. This will run as a cron job which creates the backups every minute. Please follow the README.md for detailed instructions.