Apache Spark with Scala useful for Databricks Certification
What you'll learn
- 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.
Requirements
- 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.
Description
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
Driver,
Core/Slots/Threads,
Executor
Partitions
2) Spark Execution
Jobs
Tasks
Stages
3) Spark Concepts
Caching,
DataFrame Transformations vs. Actions, Shuffling
Partitioning, Wide vs. Narrow Transformations
4) DataFrames API
DataFrameReader
DataFrameWriter
DataFrame [Dataset]
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.
Who this course is for:
- Apache Spark Beginners, Beginner Apache Spark Developer, Bigdata Engineers or Developers, Software Developer, Machine Learning Engineer, Data Scientist
Instructor
![Bigdata Engineer](data:image/svg+xml,%3Csvg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 64 64"%3E%3C/svg%3E){kind=avatar}
- 3.7 Instructor Rating
- 516 Reviews
- 43,123 Students
- 23 Courses
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.
Responsibilities includes,
- 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!!