Big Data Hadoop
- Scala, big data Spark Requirement
- Functional Programming: Proficiency with immutability, higher-order functions (map, flatMap, filter), and pattern matching is essential for writing efficient Spark code.
- Object-Oriented Programming (OOP): Familiarity with classes, traits, and abstract classes to organize complex data pipelines.
- Type Safety: Understanding Scala’s static typing helps catch errors at compile-time, which is critical for long-running big data jobs.
- Build Tools: Experience using sbt (Scala Build Tool) or Maven to manage project dependencies and package JAR files
- Scala, big data Spark Requirement
- Functional Programming: Proficiency with immutability, higher-order functions (map, flatMap, filter), and pattern matching is essential for writing efficient Spark code.
- Object-Oriented Programming (OOP): Familiarity with classes, traits, and abstract classes to organize complex data pipelines.
- Type Safety: Understanding Scala’s static typing helps catch errors at compile-time, which is critical for long-running big data jobs.
- Build Tools: Experience using sbt (Scala Build Tool) or Maven to manage project dependencies and package JAR files
- Scala, big data Spark Requirement
- Functional Programming: Proficiency with immutability, higher-order functions (map, flatMap, filter), and pattern matching is essential for writing efficient Spark code.
- Object-Oriented Programming (OOP): Familiarity with classes, traits, and abstract classes to organize complex data pipelines.
- Type Safety: Understanding Scala’s static typing helps catch errors at compile-time, which is critical for long-running big data jobs.
- Build Tools: Experience using sbt (Scala Build Tool) or Maven to manage project dependencies and package JAR files