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Export Lakehouse Notebook Results to SQL Server DB

Export data from Lakehouse to SQL Server DB.

Category: Export Data from Lakehouse | Tags: Export

How it works

Run Databricks Notebook '<<NotebookPath>>' and copy results to SQL Server database table '<<TargetSchemaName>>.<<TargetTableName>>'

To use this activity within the API, use an ActivityCode of DELTA-SQLSERVER.

Available Connections​

SourceConnection:

TargetConnection:

Example JSON​

An example of what the Task Config would look like for a task using this activity. Some of these variables would be set at the group level to avoid duplication between tasks.

{
  "SourceConnection": "MY-SOURCE-CONN",
  "NotebookPath": "/Users/fred.nurks@example.com/MyRepo/My Notebook",
  "TargetConnection": "MY-TARGET-CONN",
  "TargetSchemaName": "example_schema",
  "TargetTableName": "my_table",
  "NotebookParameters": { "Param1": "Value1", "Param2": "Value2" }
}

Variable Reference​

The following variables are supported:

  • AutoCreateTable (Optional) - Should the target table be created automatically?

  • DatabricksClusterId (Optional) - The Databricks Cluster to use for this task.

  • DIUsToUseForCopyActivity (Optional) - Specifies the powerfulness of the copy executor. Value can be between 2 and 256. When left at default, the Data Factory dynamically applies the optimal DIU setting based on the source-sink pair and data pattern.

  • ExtractControlQuery (Optional) - For incremental loads only, a SQL query to get a 'high-water' mark for extract control. For instance, this could be the maximum value of an modified_date or an identity column. NOTE: The column returned must be aliased as ExtractControl e.g. select max(modified_date) as ExtractControl from some_table.

    Show more details

    **Extract Control Query **

    For incremental data extraction, the SQL statement that will be executed on the source database to extract the high-water mark for this data prior to extracting. This could be the maximum value of a modified date or an identity column and will be used in the next data extraction.

    NOTE: The column returned must be aliased as ExtractControl. For example:

    select max(modified_date) as ExtractControl
    from some_table;

  • ExtractControlVariableName (Optional) - For incremental loads only, the name to assign the Extract Control variable in State Config for the ExtractControl value derived from the Extract Control Query above.

  • ExtractControlVariableSeedValue (Optional) - The initial value to set for the Extract Control variable in State Config - this will have no impact beyond the original seeding of the Extract Control variable in State Config.

  • IsFederated (Optional) - Makes task available to other Insight Factories within this organisation.

  • Links (Optional) - NULL

  • MaximumNumberOfAttemptsAllowed (Optional) - The total number of times the running of this Task can be attempted.

  • MinutesToWaitBeforeNextAttempt (Optional) - If a Task run fails, the number of minutes to wait before re-attempting the Task.

  • NotebookParameters (Optional) - Parameters for use in the Databricks Notebook. This is JSON format e.g. { "Param1": "Value1", "Param2": "Value2" }.

  • NotebookPath (Required) - The relative path to the Databricks Notebook.

  • PreCopyScript (Optional) - Script to execute on target database prior to Copy.

  • SaveExportToHistory (Optional) - Save the exported data to history in the Lakehouse?

  • SourceConnection (Required) - Source connection to use.

  • TargetConnection (Required) - Target connection to use.

  • TargetSchemaName (Required) - Name of the schema within target Azure SQL Database (e.g. dbo).

  • TargetTableName (Required) - Name of the table within target Azure SQL Database (e.g. Climate).

  • UpsertKeyColumns (Optional) - A comma-separated list of column names comprising the unique key of the target table.

  • WriteBehaviour (Optional) - The method of writing data to the target table.