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Apache Spark

Apache Spark is a powerful open-source framework that has gained immense importance in today's data-driven world. Organizations hire candidates who excel in Apache Spark to leverage its distributed computing capabilities for large-scale data processing, analytics, and machine learning tasks. With its ability to handle massive datasets and perform complex computations in memory, Apache Spark significantly accelerates data processing and enables real-time data analysis. By utilizing Apache Spark, companies can make data-driven decisions faster, gain valuable insights, and improve their overall operational efficiency.

Assessment Details
US $15

Performance Analysis report

40 minutes
40 MCQ

Certificate of Specialization

Credential of Readiness 

Test Syllabus

The Apache Spark Skill Test is a comprehensive evaluation designed to assess a candidate's practical understanding and application of Apache Spark, a powerful distributed computing framework. It measures their proficiency in areas such as data processing, real-time streaming, SQL-based analytics, and graph processing.


Topics covered in the test:


  • Introduction to Spark

  • Spark Standalone Mode

  • Apache Spark RDD programming

  • Spark Streaming Programming

  • Spark SQL, DataFrames, and Datasets

  • Spark Graph

  • XMLlib Concepts

  • DAG

Related Roles

Having verifiable Apache Spark skills can give you an edge in today's data-intensive landscape, where organizations increasingly rely on big data processing and real-time analytics. Roles related to Apache Spark are highly relevant as they involve leveraging the power of distributed computing to handle large-scale data, accelerate data analytics, and drive real-time decision-making.


Internship Roles:


  • Apache Spark Intern

  • Big Data Analytics Intern

  • Data Engineering Intern

  • Data Science Intern

  • Machine Learning Intern


Full-Time Roles:


  • Apache Spark Developer

  • Big Data Engineer

  • Data Scientist

  • Data Engineer

  • Machine Learning Engineer

  • Data Analyst

  • Data Architect

  • Spark Streaming Developer

  • Data Operations Engineer

  • Research Scientist (with Apache Spark expertise)

  • Data Platform Engineer

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