Introduction to Databricks
Lecture
Paul Burpo
Intermediate
0 h 54 m
2018-07-04
Lecture Overview
This training provides an overview of Azure Databricks and Spark. In this course you will learn where Azure Databricks fits in the big data landscape in Azure. Key features of Azure Databricks such as Workspaces and Notebooks will be covered. Students will also learn the basic architecture of Spark and cover basic Spark internals including core APIs, job scheduling and execution. This class will prepare developers and administrators for more advanced work in Azure Databricks such as Python or Scala development. 
Objectives
  • Understanding of the key capabilities of Azure Databricks.
  • Understanding of when to use Azure Databricks vs other big data services in Azure.
  • Learn how to work with Notebooks, Workspaces and Jobs in Azure Databricks.
  • Understanding basic Spark internals and concepts to include Core APIs, Resilient Distributed Datasets (RDDs), Transformations/Actions, and Datasets/DataFrames.
Pre-Requisites
  • Understanding of Lambda architecture in Azure
  • Understanding of big data processing architectures in Azure (completion of Opsgility course Big Data Processing in Azure)
  • Some experience with big data processing is helpful but not required
Lecture Modules
In this module will provide an overview of Azure Databricks. We will cover where Azure Databricks fits in the Azure big data ecosystem. We will talk about what Azure Databricks is and its relationship with Apache Spark. We'll also talk about Databricks' unique advantages over other big data processing platforms. We'll wrap up with a discussion of some common use cases of Azure Databricks and how to choose between Azure Databricks and Azure HDInsight running Spark. 

In this module we will cover Azure Databricks and Spark Architecture. We will start off by discussing some of the administrative features of Azure Databricks. We'll then move into a discussion of the different cluster components of a Spark cluster and look at some basic internals of a Spark cluster. We'll then dive into some of the Databricks and Spark concepts that you will need to understand to move on to more advanced training around Azure Databricks. 


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