67. Hands-On: Orchestrating Databricks Notebooks with ADF: Scheduling and Storing Logs in DB Table

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What we will learn:
Azure Data factory integration with Azure Databricks
Mount data lake storage Gen2 in Databricks
Call Databricks notebook from ADF V2 Pipeline
Configure set variable activity
Pass inputs to databricks notebooks
reading databricks notebook output
Configure notebook activity
Create logs tables and stored procedure
Configure stored procedure activity
Schedule Jobs in Azure Databricks
Required resources
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Azure Databricks for ETL
Azure Databricks for testers
Azure Databricks in one video
Azure Databricks
AWS Databricks real
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AWS Databricks Interview Questions
AWS Databricks tutorial for begineers
AWS Databricks tutorial
AWS Databricks real time scenarios
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AWS Databricks projects in telugu
AWS Databricks projects in tamil
AWS Databricks projects in english
AWS Databricks channel
AWS Databricks for data engineers
AWS Databricks for data begineers
AWS Databricks for power BI
AWS Databricks for ETL
AWS Databricks for testers
AWS Databricks in one video
AWS Databricks

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Databricks for data begineers
Databricks for power BI
Databricks for ETL
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Databricks in one video
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Welcome to the introduction to Apache Spark Architecture, where we will discuss and see how the things really works. Including:
* Driver and workers
* Partitions
* Jobs, stages, tasks
* Transformations and actions
* Data Shuffling
* Optimizations mechanisms in Apache Spark
.., and more :)

Видео 67. Hands-On: Orchestrating Databricks Notebooks with ADF: Scheduling and Storing Logs in DB Table канала Cloudpandith