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Unit testing Databricks notebooks

A simple way to unit test notebooks is to write the logic in a notebook that accepts parameterized inputs, and a separate test notebook that contains assertions. The sample project https://github.com/algattik/databricks-unit-tests/ contains two demonstration notebooks: The normalize_orders notebook processes a list of Orders and a list of OrderDetails into a joined list, taking into account […]

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Monitoring and Logging in Azure Databricks with Azure Log Analytics and Grafana

Connecting Azure Databricks with Log Analytics allows monitoring and tracing each layer within Spark workloads, including the performance and resource usage on the host and JVM, as well as Spark metrics and application-level logging. You can easily test this integration end-to-end by following the accompanying tutorial on Monitoring Azure Databricks with Azure Log Analytics and […]

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DevOps in Azure with Databricks and Data Factory

Building simple deployment pipelines to synchronize Databricks notebooks across environments is easy, and such a pipeline could fit the needs of small teams working on simple projects. Yet, a more sophisticated application includes other types of resources that need to be provisioned in concert and securely connected, such as Data Factory pipeline, storage accounts and […]