Spark SQL and Spark 3 using Scala Hands-On with Labs
Last updated on October 26, 2026 5:44 pmSpark SQL and Spark 3 using Scala Hands-On with Labs
★★★★★
$479.00 in stock
Udemy.com
as of October 26, 2026 5:44 pm
A comprehensive course on Spark SQL as well as Data Frame APIs using Scala with complementary lab access
Created by:
Durga Viswanatha Raju Gadiraju
CEO at ITVersity and CTO at Analytiqs, Inc
CEO at ITVersity and CTO at Analytiqs, Inc
Created by:
Madhuri Gadiraju
Created by:
Sathvika Dandu
Created by:
Pratik Kumar
Created by:
Sai Varma
Created by:
Phani Bhushan Bozzam
Aspiring Project Manager & Creative UI/UX Designer
Aspiring Project Manager & Creative UI/UX Designer
Created by:
Siva Kalyan Geddada
Created by:
Anushka Chakraborty
Rating:4.46 (2928reviews)
21983students enrolled
What Will I Learn?
- All the HDFS Commands that are relevant to validate files and folders in HDFS.
- Enough Scala to work Data Engineering Projects using Scala as Programming Language
- Spark Dataframe APIs to solve the problems using Dataframe style APIs.
- Basic Transformations such as Projection, Filtering, Total as well as Aggregations by Keys using Spark Dataframe APIs
- Inner as well as outer joins using Spark Data Frame APIs
- Ability to use Spark SQL to solve the problems using SQL style syntax.
- Basic Transformations such as Projection, Filtering, Total as well as Aggregations by Keys using Spark SQL
- Inner as well as outer joins using Spark SQL
- Basic DDL to create and manage tables using Spark SQL
- Basic DML or CRUD Operations using Spark SQL
- Create and Manage Partitioned Tables using Spark SQL
- Manipulating Data using Spark SQL Functions
- Advanced Analytical or Windowing Functions to perform aggregations and ranking using Spark SQL
Requirements
- Basic programming skills
- Self support lab (Instructions provided) or ITVersity lab at additional cost for appropriate environment.
- Minimum memory required based on the environment you are using with 64 bit operating system
- 4 GB RAM with access to proper clusters or 16 GB RAM with virtual machines such as Cloudera QuickStart VM
Target audience
- Any IT aspirant/professional willing to learn Data Engineering using Apache Spark
- Python Developers who want to learn Spark using Scala to add additional skill to be a Data Engineer
- Java or Scala Developers to learn Spark using Scala to add Data Engineering Skills to their profile


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