Apache Spark with Scala for Certified Databricks Professional Training
Apache Spark with Scala Crash Course useful for Databricks Certification Unofficial for beginners
Updated on Sep, 2023
Language - English
Apache Spark with Scala useful for Databricks Certification(Unofficial)
Apache Spark with Scala its a Crash Course for Databricks Certification Enthusiast (Unofficial) for beginners
“Big data" analysis is a hot and highly valuable skill – and this course will teach you the hottest technology in big data: Apache Spark. Employers including Amazon, eBay, NASA, Yahoo, and many more. All are using Spark to quickly extract meaning from massive data sets across a fault-tolerant Hadoop cluster. You'll learn those same techniques, using your own Operating system right at home.
So, What are we going to cover in this course then?
Learn and master the art of framing data analysis problems as Spark problems through over 30+ hands-on examples, and then execute them up to run on Databricks cloud computing services (Free Service) in this course. Well, the course is covering topics which are included for certification:
1) Spark Architecture Components
2) Spark Execution
3) Spark Concepts
DataFrame Transformations vs. Actions, Shuffling
Partitioning, Wide vs. Narrow Transformations
4) DataFrames API
5) Row & Column (DataFrame)
6) Spark SQL Functions
In order to get started with the course And to do that you're going to have to set up your environment.
So, the first thing you're going to need is a web browser that can be (Google Chrome or Firefox, or Safari, or Microsoft Edge (Latest version)) on Windows, Linux, and macOS desktop
This is completely Hands-on Learning with the Databricks environment.
What will you learn in this course:
- Apache Spark ( Spark Core, Spark SQL, Spark RDD and Spark DataFrame)
- Databricks Certification syllabus included in the Course
- An overview of the architecture of Apache Spark.
- Work with Apache Spark's primary abstraction, resilient distributed datasets(RDDs) to process and analyze large data sets.
- Develop Apache Spark 3.0 applications using RDD transformations and actions and Spark SQL.
- Analyze structured and semi-structured data using Datasets and DataFrames, and develop a thorough understanding about Spark SQL.
What are the prerequisites for this course?
- Some programming experience is required and Scala fundamental knowledge is also required , but you need to know the fundamentals of programming in order to pick it up.
- You will need a desktop PC and an Internet connection.
- Any flavor of Operating System is fine.
Check out the detailed breakdown of what’s inside the course
Apache Spark with Scala useful for Databricks Certification
- Introduction 02:39 02:39
- Download Resources
- Introduction to Spark 07:21 07:21
- (Old) Free Account creation in Databricks 01:51 01:51
- (New) Free Account Creation in Databricks 01:50 01:50
- Provisioning a Spark Cluster 02:14 02:14
- Basics about notebooks 07:29 07:29
- Why we should learn Apache Spark? 03:08 03:08
- Spark Architecture Components 07:10 07:10
- Driver 02:38 02:38
- Partitions 01:26 01:26
- Executors 02:48 02:48
- Spark Jobs 02:10 02:10
- Spark Stages 00:57 00:57
- Spark Tasks 00:48 00:48
- Practical Demonstration of Jobs, Tasks and Stages 03:14 03:14
- Spark RDD (Create and Display Practical) 18:21 18:21
- Spark Dataframe (Create and Display Practical) 12:06 12:06
- Anonymus Functions in Scala 04:38 04:38
- Extra (Optional on Spark DataFrame) 04:47 04:47
- Extra (Optional on Spark DataFrame) in Details 12:46 12:46
- Spark Datasets (Create and Display Practical) 17:01 17:01
- Caching 02:27 02:27
- Notes on reading files with Spark 04:16 04:16
- Data Source CSV File 08:53 08:53
- Data Source JSON File 06:21 06:21
- Data Source LIBSVM File 03:52 03:52
- Data Source Image File 04:44 04:44
- Data Source Arvo File 02:22 02:22
- Data Source Parquet File 02:50 02:50
- Untyped Dataset Operations (aka DataFrame Operations) 03:52 03:52
- Running SQL Queries Programmatically 02:55 02:55
- Global Temporary View 03:04 03:04
- Creating Datasets 03:42 03:42
- Scalar Functions (Built-in Scalar Functions) Part 1 08:34 08:34
- Scalar Functions (Built-in Scalar Functions) Part 2 14:12 14:12
- Scalar Functions (Built-in Scalar Functions) Part 3 14:32 14:32
- User Defined Scalar Functions 07:15 07:15
I am Solution Architect with 12+ year’s of experience in Banking, Telecommunication and Financial Services industry across a diverse range of roles in Credit Card, Payments, Data Warehouse and Data Center programmes
My role as Bigdata and Cloud Architect to work as part of Bigdata team to provide Software Solution.
- Support all Hadoop related issues
- Benchmark existing systems, Analyse existing system challenges/bottlenecks and Propose right solutions to eliminate them based on various Big Data technologies
- Analyse and Define pros and cons of various technologies and platforms
- Define use cases, solutions and recommendations
- Define Big Data strategy
- Perform detailed analysis of business problems and technical environments
- Define pragmatic Big Data solution based on customer requirements analysis
- Define pragmatic Big Data Cluster recommendations
- Educate customers on various Big Data technologies to help them understand pros and cons of Big Data
- Data Governance
- Build Tools to improve developer productivity and implement standard practices
I am sure the knowledge in these courses can give you extra power to win in life.
All the best!!
User your certification to make a career change or to advance in your current career. Salaries are among the highest in the world.
Our students work
with the Best
Related Video CoursesView More
Become a valued member of Tutorials Point and enjoy unlimited access to our vast library of top-rated Video CoursesSubscribe now
Master prominent technologies at full length and become a valued certified professional.Explore Now