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```r
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library(magrittr)
@@ -376,7 +376,7 @@ Azure Synapse Analytics integrates deeply with Power BI allowing data engineers
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Azure Synapse Analytics allows the different workspace computational engines to share databases and tables between its Spark pools and serverless SQL pool. Using the [shared metadata model](../metadata/overview.md),you can query your Apache Spark tables using SQL on-demand. Once done, you can connect your SQL on-demand endpoint to Power BI to easily query your synced Spark tables.
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## Next steps
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- For more information on how to set up the Spark SQL DW Connector: [Synapse SQL connector](./spark/../synapse-spark-sql-pool-import-export.md)
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- View the default libraries: [Azure Synapse Analytics runtime](../spark/apache-spark-version-support.md)
Copy file name to clipboardExpand all lines: articles/synapse-analytics/spark/apache-spark-manage-session-packages.md
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@@ -63,7 +63,7 @@ We recommend you to run the %%configure at the beginning of your notebook. You c
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Azure Synapse Analytics pools include many popular R libraries out-of-the-box. You can also install additional 3rd party libraries during your Apache Spark notebook session.
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Session-scoped R libraries allow you to customize the R environment for a specific notebook session. When you install an R session-scoped library, only the notebook associated with that notebook session will have access to the newly installed libraries. Other notebooks or sessions using the same Spark pool definition will not be impacted. In addition, session-scoped R libraries do not persist across sessions. These libraries will be installed at the start of each session when the related installation commands are executed. Last, session-scoped R libraries are automatically installed across both the driver and worker nodes
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Session-scoped R libraries allow you to customize the R environment for a specific notebook session. When you install an R session-scoped library, only the notebook associated with that notebook session will have access to the newly installed libraries. Other notebooks or sessions using the same Spark pool definition will not be impacted. In addition, session-scoped R libraries do not persist across sessions. These libraries will be installed at the start of each session when the installation commands are executed. Last, session-scoped R libraries are automatically installed across both the driver and worker nodes.
To learn more about how to manage session R libraries, you can visit the following article:
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- [Manage R session packages](./apache-spark-manage-session-packages.md#session-scoped-r-packages-preview)
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To learn more about how to manage session R libraries, you can visit the following article: [manage R session packages](./apache-spark-manage-session-packages.md#session-scoped-r-packages-preview)
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## Notebook Utilities
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mssparkutils.fs.help()
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```
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You can learn more about the supported MSSparkUtils commands by vising the following article:
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- [Use Microsoft Spark Utilities](./microsoft-spark-utilities.md)
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You can learn more about the supported MSSparkUtils commands by visiting the following article: [use Microsoft Spark Utilities](./microsoft-spark-utilities.md)
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