This PySpark test evaluates candidates' proficiency in integrating with the Python ecosystem, understanding transformations and actions, and mastering PySpark basics. It covers data sources and formats, performance optimization, Apache Spark fundamentals, debugging, streaming, DataFrames, Spark SQL, and MLlib for machine learning.
This PySpark test is designed to assess candidates' expertise in integrating with the Python ecosystem, executing transformations and actions, and grasping PySpark fundamentals. It evaluates knowledge of various data sources and formats, performance optimization techniques, and core Apache Spark concepts. Additionally, the test covers debugging and troubleshooting skills, streaming with Structured Streaming, and proficiency in using DataFrames and Spark SQL. Candidates will also be tested on their ability to implement machine learning models using MLlib, ensuring a comprehensive evaluation of their PySpark capabilities.
Data Engineer (PySpark), Big Data Developer
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Access to Objective Way of Assessments - MCQs, Checboxes, Fill in the blanks, Subjective (Manually Scored), File Upload (Manually Scored)
Access to Practice Way of Assessments - Programming, Debugging, Database, Data Science,
Access to Real-world, work like Assessments - Projects, DevOps, Machine Learning, Subjective (AI Evaluated), Video (Technical Knowledge), Video (Communication Skill), Whiteboarding (AI Evaluated)
Assessment Design consultation services according to Curriculum, Training or Learning Paths
Data Encryption and Secure Transmission: Ensures that the data is securely stored and transmitted, making it hard for hackers to tamper with the results.
Compliance with Legal Standards: Make sure the tool complies with privacy and data protection laws relevant to your location, so that the data captured during proctoring is legally compliant.
User Behavior Analytics Report: Monitors and analyzes mouse movements, keystroke dynamics, and other behaviors to identify anomalies.
Multi-Factor Authentication: Requires multiple forms of verification before granting access to the assessment.
User-Friendly Interface: A clean, intuitive user interface ensures that candidates can focus on the assessment rather than figuring out how to navigate the platform.
Mobile Compatibility: The platform should be responsive and accessible from various devices, including smartphones and tablets, so candidates can take assessments at their convenience.
Clear Instructions: The tool should offer straightforward guidelines before each test or section to ensure that candidates understand what's expected of them.
Time Tracking: A visible yet non-intrusive timer can help candidates manage their time effectively during the test.
Save and Resume: The ability for candidates to save their progress and come back to finish an assessment can reduce stress and improve the overall experience.
