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PySpark Coding Test
Test duration:
20
min
No. of questions:
10
Level of experience:
Mid

PySpark Coding Test

The Pyspark online test assists recruiters and hiring managers in assessing applicant skills. The Pyspark evaluation aids in the hiring process for various employment positions, including Pyspark Developer, Python Developer, IT Analyst, and others. Our tests help to develop winning teams by improving the interview-to-selection ratio by up to 62% and reducing hiring time by up to 45%.

Black and orange logo featuring a star, representing PySpark

PySpark Coding Test

The combination of Apache Spark and Python technology creates PySpark. Python is a general-purpose, high-level programming language, whereas Apache Spark is an open-source cluster-computing platform focused on speed, ease of use, and streaming analytics. PySpark is Python's library to use Spark. By using PySpark, one can easily integrate and further work with RDD in python programming language too. Numerous features make PySpark a fantastic framework for working with massive datasets and data exploration techniques.

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Why use iMocha’s PySpark skill test?

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This PySpark skill test helps employers in many ways, including hiring a job-fit candidate within a short period, taking unbiased employee performance appraisal decisions, and reducing hassle in mass recruitment. You can reduce hiring time by up to 40% with the PySpark programming test.

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How it works

Test Summary

PySpark programmer test helps to screen candidates who possess skills as follows:

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  • Excellent knowledge of Apache Spark with Python and Hadoop Ecosystems.
  • Familiarity with Hadoop distributed frameworks.
  • Experience in design and architecture review.
  • Ability to develop data processing tasks using PySpark, such as reading data from external sources, merging data, performing data enrichment, and loading into target data destinations.

Assessing candidates with a PySpark technical test is secure and reliable. You can use our role-based access control feature to restrict system access based on the roles of individual users within the recruiting team. Features like window violation and image and video proctoring help detect cheating during the test.

Useful for hiring
  • PySpark Developer
  • Python Developer
Test Duration
20
min
No. of Questions
10
Level of Expertise
Mid
Topics Covered
Shuffle

Data Exploration

This assessment helps recruiters to assess candidates' ability to describe the data using statistics and graphical approach.

Data Transformation

Our PySpark coding test helps recruiters to check candidates' knowledge of transforming or updating data from one RDD into another.
Shuffle

Merging Datasets

This PySpark test assesses candidates’ understanding of using different Join types on two or more Data Frames and Datasets.
Shuffle

Machine Learning

PySpark Machine Learning checks knowledge of PySpark MLlib to do data analysis using the machine-learning algorithm.
Shuffle

Datasets

This assessment helps recruiters check candidates' knowledge of assessing distributed data collection.
Shuffle

Spark Streaming

This skill test allows recruiters to check candidates' proficiency using Spark streaming to support both batch and streaming workloads.
Sample Question
Choose from our 100,000+ questions library or add your own questions to make powerful custom tests.
Question type
Multiple Option
Topics covered
Data Transformation
Difficulty
Medium

Question:

Q 1. What will be the output of the following code?
spark.sparkContext.parallelize(["this", "is", "a", "test."]).flatMap(lambda x: [x,x]).collect()
['this', 'is', 'a', 'test.']
[['this', 'this'], ['is', 'is'], ['a', 'a'], ['test.', 'test.']]
['this', 'this', 'is', 'is', 'a', 'a', 'test.', 'test.']
None of the options
A helicopter view of the employee's progress
Test Report
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FAQ
How is PySpark test customized?
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Our SMEs can tailor the assessment to the required primary and secondary abilities, such as Tabular Data, SQL, Data Framework, Python, Streaming Data, and many more. Similarly, questions can be customized to candidates' skill levels and experience.

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What are the certifications required for this role?
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Some popular certifications for PySpark-related job roles are:

• HDP Certified Apache Spark Developer

• Databricks Certification for Apache Spark

• O'Reilly Developer Certification for Apache Spark

• Cloudera Spark and Hadoop Developer

• MapR Certified Spark Developer

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What are the most common interview questions for this role?
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Some of the common questions asked for this role are:

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• What's the difference between an RDD, a DataFrame, and a DataSet?

• What are the different ways to handle row duplication in a PySpark DataFrame?

• Discuss the map () transformation in PySpark DataFrame with the help of an example.

• What is the function of PySpark's pivot () method?

• What steps are involved in calculating the executor memory?

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What are the roles and responsibilities of PySpark Developer?
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Listed below are some common roles and responsibilities that are expected to be performed by a PySpark Developer:

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• Design, develop test, deploy, maintain and improve data integration pipeline

• Experience in Python and common python libraries

• Handling Data Warehousing/ Business Intelligence projects

• Knowledge of Hadoop technology

• Creating and loading tables in Hive tables

• Experience in optimizing SQL queries

• Innovate for data integration in Apache Spark-based Platform to ensure the technology solutions leverage cutting-edge integration capabilities

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What are the required skillsets of PySpark Developer?
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You can consider these hard as well as soft skills while hiring PySpark Developer:

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Hard Skills:

• Big Data Formation

• SQL

• Python

• Streaming Data

• Data Exploration

• Deep understanding of distributed systems

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Soft Skills:

• Strategic and analytical skills

• Problem-solving skills

• Critical Thinking

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What is the package of PySpark Developer?
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In the United States, the average PySpark Developer’s salary is $144,435 per year. Starting salaries for entry-level employment start at $129,188 per year.

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