SQL Server big data clusters

SQL Server Big Data cluster bundles Spark and HDFS together with SQL server. Azure Data Studio IDE provides built in notebooks that enables data scientists and data engineers to run Spark notebooks and job in Python, R, or Scala code against the Big Data Cluster. This folder contains spark sample notebook on using Spark in SQL server Big data cluster

Contents

PySpark Hello World

Scala Hello World

SparkR Hello World

Data Loading - Transforming CSV to Parquet

Data Virtualization - Spark to SQL using MSSQL Spark connector

Data Virtualization - Spark to SQL using Spark JDBC connector

Data Virtualization - Spark with external Object Stores

Configure - Configure a spark session using a notebook

Install - Install 3rd party packages

Restful-Access - Access Spark in BDC via restful Livy APIs

Instructions on how to run in Azure Data Studio

1. From Azure Data Studio Connect to the SQL Server Master instance in a big data cluster.

2. Right-click on the server name, select Manage, switch to SQL Server Big Data Cluster tab, and open the notebook in Azure Data Studio. Wait for the “Kernel” and the target context (“Attach to”) to be populated. If required set the relevant “Kernel” ( e.g PySpark3 ) and Attach to needs to be the IP address of your big data cluster endpoint.

3. Run each cell in the Notebook sequentially.