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23 lines
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23 lines
1.0 KiB
Markdown
# SQL Server big data clusters
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The new built-in notebooks in Azure Data Studio enables data scientists and data engineers to run Python, R, or Scala code against the cluster.
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## Instructions to open a notebook from Azure Data Studio
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1. Connect to the SQL Server Master instance in a big data cluster
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1. Right-click on the server name, select **Manage**, switch to **SQL Server Big Data Cluster** tab, and use open Notebook
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## __[dataloading](dataloading/)__
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This folder contains samples that show how to load data using Spark.
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[dataloading/transform-csv-files.ipynb](dataloading/transform-csv-files.ipynb/)
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## Instructions
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1. Download and save the notebook file [dataloading/transnform-csv-files.ipynb](dataloading/transform-csv-files.ipynb/) locally.
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1. Open the notebook in Azure Data Studio, wait for the “Kernel” and the target context (“Attach to”) to be populated. Set the “Kernel” to **PySpark3** and **Attach to** needs to be the IP address of your big data cluster endpoint.
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1. Run each cell in the Notebook sequentially. |