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Cognizant Pyspark Developer Interview Questions, Process, and Tips

Updated 30 Dec 2024

Top Cognizant Pyspark Developer Interview Questions and Answers

  • Q1. What is the difference between coalesce and repartition, as well as between cache and persist?
  • Q2. What is the SQL query to find the second highest rank in a dataset?
  • Q3. What is the SQL code for calculating year-on-year growth percentage with year-wise grouping?
View all 8 questions

Cognizant Pyspark Developer Interview Experiences

2 interviews found

Interview experience
4
Good
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
No response

I applied via Walk-in and was interviewed in Nov 2024. There were 3 interview rounds.

Round 1 - One-on-one 

(2 Questions)

  • Q1. What are the optimization techniques used in Apache Spark?
  • Ans. 

    Optimization techniques in Apache Spark improve performance and efficiency.

    • Partitioning data to distribute work evenly

    • Caching frequently accessed data in memory

    • Using broadcast variables for small lookup tables

    • Optimizing shuffle operations by reducing data movement

    • Applying predicate pushdown to filter data early

  • Answered by AI
  • Q2. What is the difference between coalesce and repartition, as well as between cache and persist?
  • Ans. 

    Coalesce reduces the number of partitions without shuffling data, while repartition increases the number of partitions by shuffling data. Cache and persist are used to persist RDDs in memory.

    • Coalesce is used to reduce the number of partitions without shuffling data, while repartition is used to increase the number of partitions by shuffling data.

    • Coalesce is more efficient when reducing partitions as it avoids shuffling...

  • Answered by AI
Round 2 - One-on-one 

(2 Questions)

  • Q1. What is the SQL query to find the second highest rank in a dataset?
  • Ans. 

    SQL query to find the second highest rank in a dataset

    • Use the ORDER BY clause to sort the ranks in descending order

    • Use the LIMIT and OFFSET clauses to skip the highest rank and retrieve the second highest rank

    • Example: SELECT rank FROM dataset ORDER BY rank DESC LIMIT 1 OFFSET 1

  • Answered by AI
  • Q2. What is the SQL code for calculating year-on-year growth percentage with year-wise grouping?
  • Ans. 

    The SQL code for calculating year-on-year growth percentage with year-wise grouping.

    • Use the LAG function to get the previous year's value

    • Calculate the growth percentage using the formula: ((current year value - previous year value) / previous year value) * 100

    • Group by year to get year-wise growth percentage

  • Answered by AI
Round 3 - One-on-one 

(2 Questions)

  • Q1. What tools are used to connect Google Cloud Platform (GCP) with Apache Spark?
  • Ans. 

    To connect Google Cloud Platform with Apache Spark, tools like Dataproc, Cloud Storage, and BigQuery can be used.

    • Use Google Cloud Dataproc to create managed Spark and Hadoop clusters on GCP.

    • Store data in Google Cloud Storage and access it from Spark applications.

    • Utilize Google BigQuery for querying and analyzing large datasets directly from Spark.

  • Answered by AI
  • Q2. What is the process to orchestrate code in Google Cloud Platform (GCP)?
  • Ans. 

    Orchestrating code in GCP involves using tools like Cloud Composer or Cloud Dataflow to schedule and manage workflows.

    • Use Cloud Composer to create, schedule, and monitor workflows using Apache Airflow

    • Utilize Cloud Dataflow for real-time data processing and batch processing tasks

    • Use Cloud Functions for event-driven serverless functions

    • Leverage Cloud Scheduler for job scheduling

    • Integrate with other GCP services like BigQ...

  • Answered by AI

Interview Preparation Tips

Topics to prepare for Cognizant Pyspark Developer interview:
  • sql
  • spark
  • python
  • Cloud
Interview preparation tips for other job seekers - It is essential to prepare thoroughly before the interview.
Interview experience
5
Excellent
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Technical 

(2 Questions)

  • Q1. What is the difference between coalesce and repartition in data processing?
  • Ans. 

    Coalesce reduces the number of partitions without shuffling data, while repartition reshuffles data to create a specific number of partitions.

    • Coalesce is used to reduce the number of partitions without shuffling data

    • Repartition is used to increase or decrease the number of partitions by shuffling data

    • Coalesce is more efficient when reducing partitions as it avoids shuffling

    • Repartition is useful when you need to explici...

  • Answered by AI
  • Q2. What is the difference between a DataFrame and an RDD (Resilient Distributed Dataset)?
  • Ans. 

    DataFrame is a higher-level abstraction built on top of RDD, providing more structure and optimization capabilities.

    • DataFrames are distributed collections of data organized into named columns, similar to tables in a relational database.

    • RDDs are lower-level abstractions representing a collection of objects distributed across a cluster, with no inherent structure.

    • DataFrames provide optimizations like query optimization a...

  • Answered by AI

Pyspark Developer Interview Questions Asked at Other Companies

asked in TCS
Q1. Tell me about your current project. Difference between managed an ... read more
asked in Cognizant
Q2. What is the difference between coalesce and repartition, as well ... read more
asked in Cognizant
Q3. What is the process to orchestrate code in Google Cloud Platform ... read more
asked in Cognizant
Q4. What is the SQL code for calculating year-on-year growth percenta ... read more
asked in Cognizant
Q5. What is the SQL query to find the second highest rank in a datase ... read more

Interview questions from similar companies

Interview experience
3
Average
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Technical 

(2 Questions)

  • Q1. Why Spark is used?
  • Ans. 

    Spark is used for big data processing due to its speed, scalability, and ease of use.

    • Spark is used for processing large volumes of data quickly and efficiently.

    • It offers in-memory processing which makes it faster than traditional MapReduce.

    • Spark provides a wide range of libraries for diverse tasks like SQL, streaming, machine learning, and graph processing.

    • It can run on various platforms like Hadoop, Kubernetes, and st...

  • Answered by AI
  • Q2. What are RDDs and DataFrames
  • Ans. 

    RDDs and DataFrames are data structures in Apache Spark for processing and analyzing large datasets.

    • RDDs (Resilient Distributed Datasets) are the fundamental data structure of Spark, representing a collection of elements that can be operated on in parallel.

    • DataFrames are distributed collections of data organized into named columns, similar to a table in a relational database.

    • DataFrames are built on top of RDDs, providi...

  • Answered by AI

Skills evaluated in this interview

Interview experience
4
Good
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
No response

I applied via Naukri.com and was interviewed in Sep 2024. There was 1 interview round.

Round 1 - Coding Test 

1. Find duplicate
2. 2,3 highest salary

Interview experience
4
Good
Difficulty level
Moderate
Process Duration
2-4 weeks
Result
No response

I applied via Naukri.com and was interviewed in Jan 2024. There were 2 interview rounds.

Round 1 - Coding Test 

Basic python coding, list, dict, generators etc

Round 2 - HR 

(1 Question)

  • Q1. Salary negotiation

Interview Preparation Tips

Topics to prepare for DXC Technology Pyspark Developer interview:
  • Python
  • Spark
  • RDD
  • SQL
Interview preparation tips for other job seekers - Code well
Interview experience
3
Average
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Technical 

(1 Question)

  • Q1. Conceptual questions
Interview experience
3
Average
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Technical 

(1 Question)

  • Q1. Basic SQL and Python Questions
Interview experience
2
Poor
Difficulty level
Moderate
Process Duration
2-4 weeks
Result
Selected Selected

I was interviewed before Sep 2021.

Round 1 - Technical 

(2 Questions)

  • Q1. Can you tell me about yourself?
  • Q2. What do you know about the Order to Cash (O2C) process?
Round 2 - One-on-one 

(1 Question)

  • Q1. How would you handle a situation in which you receive a difficult query or escalation from a customer?
Interview experience
5
Excellent
Difficulty level
Easy
Process Duration
Less than 2 weeks
Result
Selected Selected
Round 1 - Technical 

(2 Questions)

  • Q1. Previous projects
  • Q2. Spring boot annotations
Round 2 - One-on-one 

(2 Questions)

  • Q1. Coding round swap two numbers without using third variable
  • Q2. Salary expectations
Interview experience
1
Bad
Difficulty level
Easy
Process Duration
Less than 2 weeks
Result
Not Selected

I was interviewed in Feb 2025.

Round 1 - Coding Test 

Coding was conducted using Java.

Round 2 - One-on-one 

(1 Question)

  • Q1. The management is really bad... I had multiple call with the HR they jever mentioned about industrial experience excluding internship. I cleared the first round and in the second round they said they need ...

Interview Preparation Tips

Interview preparation tips for other job seekers - Inquire multiple times regarding the job. Given that management is quite inadequate, they may not provide any information. Instead of wasting your time, seek clarity on the type of candidates they are interested in.

Cognizant Interview FAQs

How many rounds are there in Cognizant Pyspark Developer interview?
Cognizant interview process usually has 2 rounds. The most common rounds in the Cognizant interview process are One-on-one Round and Technical.
How to prepare for Cognizant Pyspark Developer interview?
Go through your CV in detail and study all the technologies mentioned in your CV. Prepare at least two technologies or languages in depth if you are appearing for a technical interview at Cognizant. The most common topics and skills that interviewers at Cognizant expect are Pyspark, Python, Spark, Big Data and Life.
What are the top questions asked in Cognizant Pyspark Developer interview?

Some of the top questions asked at the Cognizant Pyspark Developer interview -

  1. What is the difference between coalesce and repartition, as well as between cac...read more
  2. What is the SQL query to find the second highest rank in a datas...read more
  3. What is the SQL code for calculating year-on-year growth percentage with year-w...read more

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Cognizant Pyspark Developer Interview Process

based on 2 interviews

Interview experience

4.5
  
Good
View more
Cognizant Pyspark Developer Salary
based on 26 salaries
₹4 L/yr - ₹9 L/yr
17% less than the average Pyspark Developer Salary in India
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4.0/5

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