Certificate in Apache Spark

Apache Spark

About Apache Spark

An open-source unified analytics engine for analyzing enormous amounts of data is Apache Spark. This allows clusters to be programmed with implicit data parallelism and fault tolerance. On single-node workstations or clusters, this multi-language engine may be used to execute data engineering, data science, and machine learning operations.

Why is Apache Spark important?

The benefits of Apache Spark are:

• Use Python, SQL, Scala, Java, or R to combine the processing of your data in batches and in real-time streaming.
• Run quick, distributed ANSI SQL queries for ad-hoc reporting and dashboarding. quicker than the majority of data warehouses.
• Without using downsampling, do exploratory data analysis (EDA) on petabyte-scale data.
• The same code can be used to scale to fault-tolerant clusters of thousands of machines after training machine learning algorithms on a laptop.

Who should take the Apache Spark Exam?

•  
• Software engineers looking to improve their Big Data competencies.
• ETL developers and data engineers.
• Professionals in data analytics and data science.
• Recent graduates who want to work with big data.

Apache Spark Certification Course Outline

1. Introduction to Scala
2. Pattern Matching
3. Executing the Scala Code
4. Case Classes and Pattern Matching
5. Concepts of Traits
6. Scala–Java Interoperability and Scala Collections
7. Mutable Collections Vs. Immutable Collections
8. Use Case Bobsrockets Package