Databricks Essentials for Spark Developers (Azure and AWS)
Learn about Databricks Features
What you will 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
Description
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
Content
Getting Started with Databricks
Databricks Notebook using Scala with Spark
Databricks Notebook using Python (pyspark)
Databricks Notebook using Spark SQL
Databricks Jobs and Clusters
Databricks Development and Deployment Life Cycle using Scala
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