Databricks Essentials for Spark Developers (Azure and AWS)
Learn about Databricks Features
- Description
- Curriculum
- FAQ
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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
Databricks Notebook using Scala with Spark
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1
Introduction to the course -
2
Signing up for Databricks Community Edition
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3
Create Azure Databricks Service
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4
Signup For Databricks Full Trial on AWS
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5
Overview of Databricks UI
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6
Upload Files into Databricks
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7
Create Cluster in Databricks Platform
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8
Managing File System using Notebooks
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9
Using Databricks UIAs part of this test you need to perform tasks using Databricks UI.
* Upload Data into Databricks Platform
* Create interactive cluster
* Run file system commands using Notebook
Databricks Notebook using Python (pyspark)
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10
Define Problem Statement
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11
Create Notebook and read orders using Scala
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12
Read order_items and products into DataFrames using Scala
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13
Visualize Data using Display in Scala
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14
Get complete or closed orders using Scala
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15
Join and select data using Scala
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16
Get Daily Product Revenue using Scala
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17
Get Daily Product Revenue Sorted using Scala
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18
Save output to CSV Files using Scala
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19
Exercise - Get the monthly revenue for each Customer using Scala
Databricks Notebook using Spark SQL
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20
Define Problem Statement
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21
Create Notebook and read orders using Python
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22
Read order_items and products into DataFrames using Python
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23
Visualize Data using Display in Python
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24
Get complete or closed orders using Python
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25
Join and select data using Python
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26
Get Daily Product Revenue using Python
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27
Get Daily Product Revenue Sorted using Python
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28
Save output to CSV Files using Python
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29
Exercise - Get the monthly revenue for each Customer using Python
Databricks Jobs and Clusters
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30
Create Notebook and read orders using Spark SQL
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31
Read order_items and products using Spark SQL
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32
Visualize SQL results
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33
Join and Select data using Spark SQL
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34
Get Daily Product Revenue Sorted using Spark SQL
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35
Save output to a table using Spark SQL
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36
Exercise - Get the monthly revenue for each Customer using Spark SQL
Databricks Development and Deployment Life Cycle using Scala
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37
Introduction to Jobs and Cluster
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38
Create Cluster on Azure Databricks
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39
Request to increase CPU Quota on Azure
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40
Creating Job on Databricks using Notebook
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41
Submitting Jobs using Job Cluster
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42
Create Pool in Databricks
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43
Running Job using Interactive Cluster attached to Pool
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44
Running Job using Job Cluster attached to Pool
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45
Exercise - Submit the application as job using interactive cluster
How long do I have access to the course materials?
You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!
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Course details
Video
4 hours
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