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PySpark test for hiring

See how candidates handle PySpark code, DataFrames, pipelines, and job tuning.

10 menit
15 pertanyaan
Intermediate
Multiple choice
Questions in Inggris
Phone and desktop

Use this test free See the question formats

Jawaban singkat

The PySpark assessment is a 10-minute, 15-question multiple-choice test of practical PySpark knowledge. Candidates read short code snippets and small tables about Spark execution, DataFrame transformations, machine learning pipelines, and job configuration and tuning. Use it when hiring intermediate data engineers, PySpark developers, data scientists, or other roles that need PySpark skills.

Hal yang diukur

Practical PySpark knowledge: Spark fundamentals, DataFrame manipulation, machine learning pipelines, and configuration and performance tuning.

Spark fundamentals

Checks understanding of how Spark executes work through short code snippets and small tables.

DataFrame manipulation

Focuses on interpreting transformations applied to DataFrames.

Machine learning pipelines

Covers how machine learning pipelines are built and evaluated.

Configuration and performance

Tests knowledge of configuring and tuning Spark jobs.

Question formats

Multiple choice

The candidate: Reads a short situation, table or statement and picks the right answer, or every right answer.

You see: Whether the candidate knows the material well enough to apply it, not just recognize it.

15 questions in 10 minutes, served one at a time.

Roles this test fits

Data engineers, big data engineers, PySpark developers, data scientists, machine learning engineers, data analysts, data warehouse managers, analytics consultants, and other roles that need intermediate PySpark skills.

What this assessment adds

Evidence beyond a resume
See responses to PySpark snippets and tables that probe Spark execution and DataFrame transformations.
Broader technical coverage
Check knowledge of pipeline building and evaluation alongside job configuration and performance.
A focused first screen
Use a 10-minute assessment before setting aside time for a work sample and interview.

What you get for each candidate

Example report (fictional data)PySpark

68%Percentile 40. Benchmark: HireValid candidates, n = 2.150

Spark fundamentals59%

DataFrame manipulation64%

Machine learning pipelines81%

Configuration and performance66%

Integrity ScoreTingkat keyakinan tinggi

Stayed on the test tab throughout
No pasted answers
Answered at a steady pace

Scores, profiles and integrity signals are evidence for you to review alongside an interview, never an automatic decision.

Use this test free

Test integrity measures

Each candidate gets a different question set from large pools. Questions appear in a different order for each attempt, and answer options are shuffled. The browser receives one question at a time; answer keys stay on HireValid’s servers. This 10-minute PySpark assessment runs on a server timer. Reloading restores the same question with only the remaining time, and candidates cannot go back to earlier questions. Question text cannot be copied or selected; blocked copy attempts are recorded in the timeline. Invitation links are personal and expire, and a completed test cannot be taken again. HireValid records signals such as time away from the test tab, pastes into answers, and answers faster than a question can be read. An Integrity Score and evidence timeline are provided for employer review; they do not decide on their own. With candidate consent, employers can add webcam photos at random moments.

Cara kami mencegah kecurangan dengan AI · Integrity signals

Use the score as one signal

Review the score as evidence, not as a hiring decision. Pair it with a job-relevant work sample and a structured interview. For the work sample, ask candidates to explain their choices on a small Spark task, then compare their approach with the role’s needs. If the role also calls for adjacent data skills, consider the Pandas, Data Science, or Data Extraction, Transformation, and Loading (ETL) assessment. These cover separate areas and do not replace a review of the candidate’s work.

Pertanyaan wawancara terstruktur

A DataFrame transformation produces unexpected rows. How would you inspect the steps and narrow down the cause?
Listen for a clear, step-by-step way to examine transformations and the resulting data.
How would you build and evaluate a machine learning pipeline for a defined task?
Listen for choices the candidate would make across pipeline building and evaluation.
A Spark job slows after a configuration change. How would you investigate and tune it?
Listen for a reasoned approach to configuration and performance.

Understand scoring and benchmarks

Fairness and accommodations

The test is defined to use neutral data such as orders, sensor readings, shipments and event logs, with no money symbols, idioms or knowledge of a particular industry, and with names from many backgrounds. It covers the open-source Spark API only, leaving out vendor platforms and cluster-manager settings, and its pools are told to avoid behavior that differs between recent Spark versions. As questions are drafted, reviewers work through each code snippet and table line by line, confirm the keyed answers (one for a single_choice question, two or three of five for a multi_select) and check that the question can be read and answered within its 40 seconds.

You can give any candidate extra time as an accommodation. Results are evidence for a person to review, never an automatic decision.

Provisional: no norms exist yet, and reliability is reported once 200 candidates have completed it.

Baca pendekatan kami terhadap keadilan

Test details

A ten-minute multiple-choice test of working knowledge of PySpark, the Python interface to Apache Spark. Candidates read short code snippets and small tables and answer questions on how Spark executes work, how DataFrames are transformed, how machine learning pipelines are built and evaluated, and how jobs are configured and tuned.

Questions are in English.
No aids are needed.
Each question is answered once, in order, with no going back.
4 practice questions, 4 minutes, before the timed test.

Apache Spark, PySpark, Python are trademarks of their owners. HireValid is not affiliated with or endorsed by them.

Pertanyaan yang sering diajukan

What does the PySpark assessment include?+

It has 15 multiple-choice questions in 10 minutes. Candidates read short code snippets and small tables, then answer about Spark execution, DataFrame transformations, machine learning pipelines, and job configuration and tuning.

Which roles suit the PySpark assessment?+

It is intended for intermediate roles that need PySpark skills, including data engineers, big data engineers, PySpark developers, data scientists, machine learning engineers, and data analysts.

Can candidates return to earlier questions in the PySpark assessment?+

No. Candidates cannot go back to earlier questions. They can try a separate practice set of four questions, which has a four-minute limit, before taking the assessment.

How should I interpret PySpark assessment results?+

The test is provisional: norms do not yet exist, and reliability will be reported once 200 candidates have completed it. Review the score alongside a work sample and structured interview, not as the sole basis for a decision.

Does the PySpark assessment cover vendor platforms?+

No. It covers the open-source Spark API only, leaving out vendor platforms and cluster-manager settings, and avoids behavior that differs between recent Spark versions. Questions use neutral data such as orders, sensor readings, shipments and event logs.