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articles/data-explorer/spark-connector.md

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@@ -81,15 +81,15 @@ For more information, see [connector usage](https://github.com/Azure/azure-kusto
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1. Set the following Spark cluster settings, based on Azure Databricks cluster using Spark 2.4.4 and Scala 2.11:
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[Databricks cluster settings](media/spark-connector/databricks-cluster.png)
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1. Install the latest spark-kusto-connector library from Maven::
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![Databricks cluster settings](media/spark-connector/databricks-cluster.png)
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1. Install the latest spark-kusto-connector library from Maven:
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[Import Azure Data Explorer library](media/spark-connector/db-create-library.png)
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![Import Azure Data Explorer library](media/spark-connector/db-create-library.png)
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1. Verify that all required libraries are installed:
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[Verify libraries installed](media/spark-connector/db-libraries-view.png)
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![Verify libraries installed](media/spark-connector/db-libraries-view.png)
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## Authentication
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|**KUSTO_AAD_AUTHORITY_ID** | Azure AD authentication authority. Azure AD Directory (tenant) ID. |
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|**KUSTO_AAD_CLIENT_PASSWORD** | Azure AD application key for the client. |
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### Azure Data Explorer Privileges
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### Azure Data Explorer privileges
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The following privileges must be granted on an Azure Data Explorer Cluster:
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The following privileges must be granted on an Azure Data Explorer cluster:
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* For reading (data source), Azure AD application must have *viewer* privileges on the target database, or *admin* privileges on the target table.
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* For writing (data sink), Azure AD application must have *ingestor* privileges on the target database. It must also have *user* privileges on the target database to create new tables. If the target table already exists, *admin* privileges on the target table can be configured.
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For more information on Azure Data Explorer principal roles, see [role-based authorization](/azure/kusto/management/access-control/role-based-authorization). For managing security roles, see [security roles management](/azure/kusto/management/security-roles).
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## Spark sink: Writing to Azure Data Explorer
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## Spark sink: writing to Azure Data Explorer
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1. Set up sink parameters:
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.option(KustoSinkOptions.KUSTO_WRITE_ENABLE_ASYNC, "true") // Optional, better for streaming, harder to handle errors
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.trigger(Trigger.ProcessingTime(TimeUnit.SECONDS.toMillis(10))) // Sync this with the ingestionBatching policy of the database
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.start()
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```
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## Spark source: Reading from Azure Data Explorer
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## Spark source: reading from Azure Data Explorer
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1. When reading small amounts of data, define the data query:
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