Clock
Test duration:
20
min
Notes
No. of questions:
10
Tie
Level of experience:

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%.

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Candidates
Assessed
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Organizations Served
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About

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.

Why use iMocha’s PySpark skill test?

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.

Two important use cases for Pyspark assessment test

#1 Identifying job-fit candidates based on job roles

You can create customized skill assessments for any required job role. Using this feature, you can choose questions from different skill types, including functional, technical, and soft skills. For example, with our customized Pyspark test, you can evaluate candidates’ knowledge of Big Data Formation, Programming language (Python/Scala/Java), Spark SQL, MLlib, and GraphX Library and assess the best individuals for the job.

#2 Skill-gap analysis of your employees

iMocha allows you to measure employees' skill competency through SAP training assessments. It determines the existing skill level and identifies the areas for growth. It also measures the knowledge and impact of the training and traces individual employees’ progress. For example, you can use our Pyspark training assessments to identify a consultant’s knowledge about Datasets, Data Transformation, Machine Learning and other skills and perform a skill gap analysis.

Use iMocha's assessment to hire skill fit, remove bias, and save money!
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How it works

Test Summary

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

• Excellent knowledge of Apache Spark with Python and Hadoop Ecosystems

• 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

• Familiarity with Hadoop distributed frameworks

• Experience in design and architecture review

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.

Test Creation Process

We provide different types of PySpark coding tests to help you evaluate candidates' specific skills. These questions are created by Subject Matter Experts (SMEs) based on their knowledge and expertise. For example, only PySpark specialists will create questions about the Spark streaming or Elastic Map Reduce based on the difficulty level of easy, medium, and hard.

You can - choose which questions to include in the PySpark online test or ask us to create customized assessments according to your requirements.

Test Analytics Report

The recruiter/hiring manager can obtain detailed reports for each candidate, allowing them to view candidate's performance in each aspect at a glance. Furthermore, the Test Insights section, with its score distribution and section analysis tools, assists in identifying job match applicants effectively.

Test Question Format

This test may contain MCQs (Multiple Choice Questions), MAQs (Multiple Answer Questions), Fill in the Blanks, Whiteboard Questions, Audio / Video Questions, AI-LogicBox (AI-based Pseudo-Coding Platform), Coding Simulators, True or False Questions, etc.

Test Design Guidelines

This test is designed considering EEOC guidelines; it will help you assess and hire diverse talent without any bias

Test Duration
20
No. of Questions
10
Level of Expertise
Useful for hiring
  • PySpark Developer
  • Python Developer
Topics Covered
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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.
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Merging Datasets

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

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

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

Multiple Option

Topic:

Difficulty:

Hard


Q 1. You have been asked to train « Naive Bayes model for spam detection dataset

Using Python command, what wil you add in the given code at XXXX to deciore, it and train your modal for the given dataset?

import numpy os np

X= nporroyll 3. 2b[1 21 [2.21.[3,21)
Y= nporray(fi.a,a.1))

XXXX

from skinamnaive_bayas import

Gaussianna

otf = Gaussianne()

ceataie(x ¥)

from skinamnaive_bayas import

Gaussianna

otf = Gaussianne()

ceataie(x ¥)

from skinamnaive_bayas import

Gaussianna

otf = Gaussianne()

ceataie(x ¥)

from skinamnaive_bayas import

Gaussianna

otf = Gaussianne()

ceataie(x ¥)

Question types :

Multiple Option

Topic:

Machine teaming

Difficulty:

Hard


Q 1. Q2 Lets assume that you have 6 Pandas DataFrome(af) in the below tole.

Index Code Open High
0 AAPL 19877 70074
1 AAPL 19877 70074
2 AAPL 19877 70074
3 AAPL 19877 70074
4 AAPL 19877 70074

When the following commend is executed, what hoppens to the DatoFrome?

df= defiinat()
Y= nporray(fi.a,a.1))

Index Code Open High
0 AAPL 19877 70074
1 AAPL 19877 70074
2 AAPL 19877 70074
3 AAPL 19877 70074
4 AAPL 19877 70074
Index Code Open High
0 AAPL 19877 70074
1 AAPL 19877 70074
2 AAPL 19877 70074
3 AAPL 19877 70074
4 AAPL 19877 70074
it gives an error becouse of the third row which has on empty string.
None of these

Question types :

Multiple Option

Topic:

Data Transformation

Difficulty:

Mediam

Question:

What is the outcome of the following code?spark.sparkContext.parallelize(["this", "is", "a", "test."]).flatMap(lambda x: [x,x]).collect()Options['this', 'is', 'a', 'test.'][['this', 'this'], ['is', 'is'], ['a', 'a'], ['test.', 'test.']]['this', 'this', 'is', 'is', 'a', 'a', 'test.', 'test.']None of the options

What is the outcome of the following code?

spark.sparkContext.parallelize(["this", "is", "a", "test."]).flatMap(lambda x: [x,x]).collect()


Options

  • ['this', 'is', 'a', 'test.']
  • [['this', 'this'], ['is', 'is'], ['a', 'a'], ['test.', 'test.']]
  • ['this', 'this', 'is', 'is', 'a', 'a', 'test.', 'test.']
  • None of the options

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You can customize this test by
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Setting the difficulty level of the test

Choose easy, medium, or tricky questions from our skill libraries to assess candidates of different experience levels.
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Combining multiple skills into one test

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Adding your own
questions to the test

Add, edit, or bulk upload your coding, MCQ, and whiteboard questions.
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Requesting a tailor-made test

Receive a tailored assessment created by our subject matter experts to ensure adequate screening.

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Now my team of 25 recruiters has adopted this measure and it has done wonders for our clients. Thanks to the Customer Success Team of iMocha. They have shared the best practices of quick test creation and also helped us in training all our recruiters for various functionalities of the tool.
Client

Vipin Sharma,

Mobile Programming
FAQ
What is Data Science?
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.NET Design Pattern test helps recruiters to evaluate candidates' ability to work on GOF Decorator Design Pattern to solve recurring design problems and design flexible and reusable object-oriented software

Why use iMocha’s online data science test?
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What are the key skills that recruiter should look for while hiring a Data Scientist?
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What are few interview questions that recruiter/hiring manager should ask while hiring a data scientist?
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How do you assess the data scientists?
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How is PySpark test customized?
Down Arrow Circle

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.

What are the certifications required for this role?
Down Arrow Circle

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

What are the most common interview questions for this role?
Down Arrow Circle

Some of the common questions asked for this role are:

• 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?

What are the roles and responsibilities of PySpark Developer?
Down Arrow Circle

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

• 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

What are the required skillsets of PySpark Developer?
Down Arrow Circle

You can consider these hard as well as soft skills while hiring PySpark Developer:

Hard Skills:

• Big Data Formation

• SQL

• Python

• Streaming Data

• Data Exploration

• Deep understanding of distributed systems

Soft Skills:

• Strategic and analytical skills

• Problem-solving skills

• Critical Thinking

What is the package of PySpark Developer?
Down Arrow Circle

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.