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About the test:

The PySpark Test evaluates a candidate's knowledge and skills in using PySpark, a Python API for Apache Spark. The test includes coding questions to evaluate programming competency in PySpark, as well as multiple-choice questions to assess understanding of related topics such as Python, SQL, Machine Learning and Data Science.

Covered skills:

  • Installing PySpark
  • PySpark RDD
  • SQL
  • Data Science
  • PySpark UDF
  • Python
  • Machine Learning

9 reasons why
9 reasons why

Adaface PySpark Assessment Test is the most accurate way to shortlist Data Engineers



Reason #1

Tests for on-the-job skills

The PySpark Test helps recruiters and hiring managers identify qualified candidates from a pool of resumes, and helps in taking objective hiring decisions. It reduces the administrative overhead of interviewing too many candidates and saves time by filtering out unqualified candidates at the first step of the hiring process.

The test screens for the following skills that hiring managers look for in candidates:

  • Installing and setting up PySpark
  • Creating and using PySpark UDFs (User Defined Functions)
  • Working with PySpark RDDs (Resilient Distributed Datasets)
  • Strong proficiency in Python programming language
  • Proficiency in SQL querying
  • Understanding of Machine Learning concepts in PySpark
  • Experience with Data Science techniques and tools
  • Ability to analyze and process large volumes of data
  • Knowledge of PySpark's data manipulation and transformation operations
  • Familiarity with PySpark's data visualization tools
  • Understanding of PySpark's distributed computing capabilities
  • Proficiency in debugging and troubleshooting PySpark code
Reason #2

No trick questions

no trick questions

Traditional assessment tools use trick questions and puzzles for the screening, which creates a lot of frustration among candidates about having to go through irrelevant screening assessments.

View sample questions

The main reason we started Adaface is that traditional pre-employment assessment platforms are not a fair way for companies to evaluate candidates. At Adaface, our mission is to help companies find great candidates by assessing on-the-job skills required for a role.

Why we started Adaface
Reason #3

Non-googleable questions

We have a very high focus on the quality of questions that test for on-the-job skills. Every question is non-googleable and we have a very high bar for the level of subject matter experts we onboard to create these questions. We have crawlers to check if any of the questions are leaked online. If/ when a question gets leaked, we get an alert. We change the question for you & let you know.

How we design questions

These are just a small sample from our library of 10,000+ questions. The actual questions on this PySpark Test will be non-googleable.

🧐 Question

Medium

ZeroDivisionError and IndexError
Exceptions
Solve
What will the following Python code output?
 image

Medium

Session
File Handling
Dictionary
Solve
 image
The function high_sess should compute the highest number of events per session of each user in the database by reading a comma-separated value input file of session data. The result should be returned from the function as a dictionary. The first column of each line in the input file is expected to contain the user’s name represented as a string. The second column is expected to contain an integer representing the events in a session. Here is an example input file:
Tony,10
Stark,12
Black,25
Your program should ignore a non-conforming line like this one.
Stark,3
Widow,6
Widow,14
The resulting return value for this file should be the following dictionary: { 'Stark':12, 'Black':25, 'Tony':10, 'Widow':14 }
What should replace the CODE TO FILL line to complete the function?
 image

Medium

Max Code
Arrays
Solve
Below are code lines to create a Python function. Ignoring indentation, what lines should be used and in what order for the following function to be complete:
 image

Medium

Recursive Function
Recursion
Dictionary
Lists
Solve
Consider the following Python code:
 image
In the above code, recursive_search is a function that takes a dictionary (data) and a target key (target) as arguments. It searches for the target key within the dictionary, which could potentially have nested dictionaries and lists as values, and returns the value associated with the target key. If the target key is not found, it returns None.

nested_dict is a dictionary that contains multiple levels of nested dictionaries and lists. The recursive_search function is then called with nested_dict as the data and 'target_key' as the target.

What will the output be after executing the above code?

Medium

Stacking problem
Stack
Linkedlist
Solve
What does the below function ‘fun’ does?
 image
A: Sum of digits of the number passed to fun.
B: Number of digits of the number passed to fun.
C: 0 if the number passed to fun is divisible by 10. 1 otherwise.
D: Sum of all digits number passed to fun except for the last digit.

Medium

Multi Select
JOIN
GROUP BY
Solve
Consider the following SQL table:
 image
How many rows does the following SQL query return?
 image

Medium

nth highest sales
Nested queries
User Defined Functions
Solve
Consider the following SQL table:
 image
Which of the following SQL commands will find the ‘nth highest Sales’ if it exists (returns null otherwise)?
 image

Medium

Select & IN
Nested queries
Solve
Consider the following SQL table:
 image
Which of the following SQL queries would return the year when neither a football or cricket winner was chosen?
 image

Medium

Sorting Ubers
Nested queries
Join
Comparison operators
Solve
Consider the following SQL table:
 image
What will be the first two tuples resulting from the following SQL command?
 image

Hard

With, AVG & SUM
MAX() MIN()
Aggregate functions
Solve
Consider the following SQL table:
 image
How many tuples does the following query return?
 image
🧐 Question🔧 Skill

Medium

ZeroDivisionError and IndexError
Exceptions

2 mins

Python
Solve

Medium

Session
File Handling
Dictionary

2 mins

Python
Solve

Medium

Max Code
Arrays

2 mins

Python
Solve

Medium

Recursive Function
Recursion
Dictionary
Lists

3 mins

Python
Solve

Medium

Stacking problem
Stack
Linkedlist

4 mins

Python
Solve

Medium

Multi Select
JOIN
GROUP BY

2 mins

SQL
Solve

Medium

nth highest sales
Nested queries
User Defined Functions

3 mins

SQL
Solve

Medium

Select & IN
Nested queries

3 mins

SQL
Solve

Medium

Sorting Ubers
Nested queries
Join
Comparison operators

3 mins

SQL
Solve

Hard

With, AVG & SUM
MAX() MIN()
Aggregate functions

2 mins

SQL
Solve
🧐 Question🔧 Skill💪 Difficulty⌛ Time
ZeroDivisionError and IndexError
Exceptions
Python
Medium2 mins
Solve
Session
File Handling
Dictionary
Python
Medium2 mins
Solve
Max Code
Arrays
Python
Medium2 mins
Solve
Recursive Function
Recursion
Dictionary
Lists
Python
Medium3 mins
Solve
Stacking problem
Stack
Linkedlist
Python
Medium4 mins
Solve
Multi Select
JOIN
GROUP BY
SQL
Medium2 mins
Solve
nth highest sales
Nested queries
User Defined Functions
SQL
Medium3 mins
Solve
Select & IN
Nested queries
SQL
Medium3 mins
Solve
Sorting Ubers
Nested queries
Join
Comparison operators
SQL
Medium3 mins
Solve
With, AVG & SUM
MAX() MIN()
Aggregate functions
SQL
Hard2 mins
Solve
Reason #4

1200+ customers in 75 countries

customers in 75 countries
Brandon

With Adaface, we were able to optimise our initial screening process by upwards of 75%, freeing up precious time for both hiring managers and our talent acquisition team alike!


Brandon Lee, Head of People, Love, Bonito

Reason #5

Designed for elimination, not selection

The most important thing while implementing the pre-employment PySpark Test in your hiring process is that it is an elimination tool, not a selection tool. In other words: you want to use the test to eliminate the candidates who do poorly on the test, not to select the candidates who come out at the top. While they are super valuable, pre-employment tests do not paint the entire picture of a candidate’s abilities, knowledge, and motivations. Multiple easy questions are more predictive of a candidate's ability than fewer hard questions. Harder questions are often "trick" based questions, which do not provide any meaningful signal about the candidate's skillset.

Science behind Adaface tests
Reason #6

1 click candidate invites

Email invites: You can send candidates an email invite to the PySpark Test from your dashboard by entering their email address.

Public link: You can create a public link for each test that you can share with candidates.

API or integrations: You can invite candidates directly from your ATS by using our pre-built integrations with popular ATS systems or building a custom integration with your in-house ATS.

invite candidates
Reason #7

Detailed scorecards & benchmarks

Reason #8

High completion rate

Adaface tests are conversational, low-stress, and take just 25-40 mins to complete.

This is why Adaface has the highest test-completion rate (86%), which is more than 2x better than traditional assessments.

test completion rate
Reason #9

Advanced Proctoring


Learn more

About the PySpark Online Test

Why you should use Pre-employment PySpark Test?

The PySpark Test makes use of scenario-based questions to test for on-the-job skills as opposed to theoretical knowledge, ensuring that candidates who do well on this screening test have the relavant skills. The questions are designed to covered following on-the-job aspects:

  • Installing PySpark
  • Creating and using PySpark UDFs
  • Working with PySpark RDDs
  • Python programming skills
  • SQL querying and manipulation
  • Machine learning with PySpark
  • Data science concepts
  • Handling exceptions and errors in PySpark
  • Understanding distributed computing with PySpark
  • Optimizing PySpark jobs for performance

Once the test is sent to a candidate, the candidate receives a link in email to take the test. For each candidate, you will receive a detailed report with skills breakdown and benchmarks to shortlist the top candidates from your pool.

What topics are covered in the PySpark Test?

  • Installing PySpark

    Installing PySpark involves setting up the necessary dependencies and packages to run PySpark applications. It is important to measure this skill in the test to assess the candidate's understanding of the PySpark environment and their ability to navigate the installation process.

  • PySpark UDF

    PySpark UDF refers to User-Defined Functions in PySpark, which allow users to define custom functions to process and manipulate data. Measuring this skill helps evaluate the candidate's proficiency in leveraging PySpark's powerful UDF capabilities for advanced data transformations.

  • PySpark RDD

    PySpark RDD (Resilient Distributed Dataset) is a fundamental data structure used in PySpark for efficient distributed processing. Testing this skill allows recruiters to gauge the candidate's knowledge of RDDs and their ability to perform parallel operations on distributed datasets.

  • Python

    Python is a widely-used programming language known for its simplicity and versatility. Evaluating a candidate's command over Python in the PySpark context helps determine their familiarity with the language and their ability to leverage its libraries and functionalities within PySpark applications.

  • SQL

    SQL (Structured Query Language) is essential for data manipulation and querying in the context of PySpark. Assessing SQL skills ensures that the candidate can effectively interact with databases, perform complex queries, and process data using SQL expressions and operations in PySpark.

  • Machine Learning

    Machine Learning is a branch of artificial intelligence with algorithms, models, and techniques that enable computers to learn from and make predictions or decisions based on data. Testing this skill assists in evaluating the candidate's understanding of machine learning concepts and their ability to apply relevant algorithms to solve real-world data problems within PySpark.

  • Data Science

    Data Science involves the analysis, interpretation, and extraction of valuable insights from structured and unstructured data. Measuring this skill in the test helps identify candidates who can effectively apply statistical and analytical techniques to transform raw data into meaningful information using PySpark.

  • Full list of covered topics

    The actual topics of the questions in the final test will depend on your job description and requirements. However, here's a list of topics you can expect the questions for PySpark Test to be based on.

    PySpark Installation
    PySpark Configuration
    PySpark DataFrames
    PySpark SQL
    PySpark MLlib
    PySpark Streaming
    PySpark GraphX
    PySpark DataFrame API
    PySpark RDD API
    PySpark UDFs
    PySpark Data preprocessing
    PySpark Data visualization
    PySpark Machine Learning algorithms
    PySpark Pipeline
    PySpark Model Evaluation
    PySpark Feature Engineering
    Python Basics
    Python Control Flow
    Python Functions
    Python Classes and Objects
    Python File I/O
    Python Error Handling
    Python Modules and Packages
    Python List Manipulation
    Python String Manipulation
    Python Dictionary Manipulation
    Python File Manipulation
    Python Regular Expressions
    Python NumPy
    Python Pandas
    Python Matplotlib
    SQL Basics
    SQL SELECT Queries
    SQL JOIN Queries
    SQL Aggregate Functions
    SQL Subqueries
    SQL Constraints
    SQL Views
    SQL Indexes
    SQL Triggers
    SQL Stored Procedures
    Machine Learning Concepts
    Supervised Learning
    Unsupervised Learning
    Regression
    Classification
    Clustering
    Feature Extraction
    Data Preprocessing
    Evaluation Metrics
    Data Visualization
    Data Cleaning
    Data Transformation
    Data Sampling
    Data Splitting
    Model Training
    Model Evaluation
    Model Deployment
    Data Science Concepts
    Exploratory Data Analysis
    Data Manipulation
    Data Visualization
    Statistical Analysis
    Data Mining
    Data Wrangling
    Data Integration

What roles can I use the PySpark Test for?

  • Data Engineer
  • Data Analyst
  • Data Scientist
  • Big Data Engineer
  • Business Analyst

How is the PySpark Test customized for senior candidates?

For intermediate/ experienced candidates, we customize the assessment questions to include advanced topics and increase the difficulty level of the questions. This might include adding questions on topics like

  • Building and evaluating machine learning models with PySpark
  • Working with PySpark DataFrames
  • Implementing feature engineering techniques in PySpark
  • Applying statistical analysis with PySpark
  • Tuning and optimizing PySpark ML pipelines
  • Performing data preprocessing and cleaning with PySpark
  • Understanding PySpark SQL and DataFrame API
  • Using PySpark to interact with various data sources
  • Applying advanced analytics techniques with PySpark
  • Deploying PySpark applications to production environments

The coding question for experienced candidates will be of a higher difficulty level to evaluate more hands-on experience.

Singapore government logo

The hiring managers felt that through the technical questions that they asked during the panel interviews, they were able to tell which candidates had better scores, and differentiated with those who did not score as well. They are highly satisfied with the quality of candidates shortlisted with the Adaface screening.


85%
reduction in screening time

PySpark Hiring Test FAQs

Can I combine multiple skills into one custom assessment?

Yes, absolutely. Custom assessments are set up based on your job description, and will include questions on all must-have skills you specify. Here's a quick guide on how you can request a custom test.

Do you have any anti-cheating or proctoring features in place?

We have the following anti-cheating features in place:

  • Non-googleable questions
  • IP proctoring
  • Screen proctoring
  • Web proctoring
  • Webcam proctoring
  • Plagiarism detection
  • Secure browser
  • Copy paste protection

Read more about the proctoring features.

How do I interpret test scores?

The primary thing to keep in mind is that an assessment is an elimination tool, not a selection tool. A skills assessment is optimized to help you eliminate candidates who are not technically qualified for the role, it is not optimized to help you find the best candidate for the role. So the ideal way to use an assessment is to decide a threshold score (typically 55%, we help you benchmark) and invite all candidates who score above the threshold for the next rounds of interview.

What experience level can I use this test for?

Each Adaface assessment is customized to your job description/ ideal candidate persona (our subject matter experts will pick the right questions for your assessment from our library of 10000+ questions). This assessment can be customized for any experience level.

Does every candidate get the same questions?

Yes, it makes it much easier for you to compare candidates. Options for MCQ questions and the order of questions are randomized. We have anti-cheating/ proctoring features in place. In our enterprise plan, we also have the option to create multiple versions of the same assessment with questions of similar difficulty levels.

I'm a candidate. Can I try a practice test?

No. Unfortunately, we do not support practice tests at the moment. However, you can use our sample questions for practice.

What is the cost of using this test?

You can check out our pricing plans.

Can I get a free trial?

Yes, you can sign up for free and preview this test.

I just moved to a paid plan. How can I request a custom assessment?

Here is a quick guide on how to request a custom assessment on Adaface.

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40 min tests.
No trick questions.
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