Databricks Essentials for Spark Developers (Azure and AWS)

Learn about Databricks Features

Are you an experienced Spark Developer and want to understand about Databricks platform?

What you’ll learn

  • Using Community Edition of Databricks to explore the platform.
  • Signing up for Full Trial using Azure Databricks.
  • Signing up for Full Trial using Databricks on AWS.
  • Develop and Deploy Notebooks using Scala, Python as well as SQL using Databricks Platform.
  • Understand the difference between interactive and job clusters.
  • Formal Development and Deployment Life Cycle.
  • Run jobs by attaching application as jar along with libraries.
  • Overview of Cluster Pools.
  • Installing and using databricks-cli.

Course Content

  • Getting Started with Databricks –> 8 lectures • 46min.
  • Databricks Notebook using Scala with Spark –> 10 lectures • 43min.
  • Databricks Notebook using Python (pyspark) –> 10 lectures • 44min.
  • Databricks Notebook using Spark SQL –> 7 lectures • 23min.
  • Databricks Jobs and Clusters –> 9 lectures • 36min.
  • Databricks Development and Deployment Life Cycle using Scala –> 6 lectures • 38min.

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  • Laptop with decent configuration.
  • Knowledge of Apache Spark is highly desired.

Are you an experienced Spark Developer and want to understand about Databricks platform?

Conventionally we used to work on Data Engineering with clusters built using distributions. However, with cloud if we can separate storage from compute and leverage pay as you go model, the costs of infrastructure for Big Data Clusters can go down significantly.

Databricks is one such Cloud Choice!!!

As part of this course, you will be learning the essentials of Databricks Essentials.

  • Understand different editions such as Community, Databricks (AWS) and Azure Databricks
  • Signing up for community edition
  • Uploading data to DBFS
  • Developing using Databricks Notebook with Scala, Python as well as Spark SQL
  • Development Life Cycle using Scala with IntelliJ as IDE
  • Configuring jobs using Jar files
  • and many more
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