Publicis Sapient Interview Questions, Process, and Tips

Q1. Simple task to fetch cart and display items in the cart
Ans. 
Fetch cart items and display them
• Create a function to fetch cart items from database

• Display the items in the cart on the user interface

• Handle empty cart scenarios

• Consider pagination for large number of items
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Q2. React hooks, life cycle methods, error boundaries, hoc
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Q1. Simple task to fetch characters and their movies
Ans. 
Fetch characters and their movies
• Use API like IMDb or The Movie Database to fetch movie data

• Parse the data to extract characters and their associated movies

• Store the characters and movies in an array of strings
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Q1. Culture based questions
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There were MCQ questions consists of different sections like Design Pattern,Java 8

Q1. Questions related to Multithreading,Design patterns
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Q2. Java coding questions
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Q1. Questions related to Multithreading
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Q2. Java coding questions
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NER training using deep learning

Q1. Describe the approach taken for assignment
Ans. 
I approach assignments by breaking them down into smaller tasks, setting deadlines, and regularly checking progress.
• Break down the assignment into smaller tasks to make it more manageable

• Set deadlines for each task to stay on track

• Regularly check progress to ensure everything is on schedule

• Seek feedback from colleagues or supervisors to improve the quality of work
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Q2. Scenario based questions
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It’s about Pyspark for data engineer position

Q1. About the project
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Q2. About the technologies in azure data engineering
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Q1. It’s all about fitment round
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Q1. What will happen if job has failed in pipeline and data processing cycle is over?
Ans. 
If a job fails in the pipeline and data processing cycle is over, it can lead to incomplete or inaccurate data.
• Incomplete data may affect downstream processes and analysis

• Data quality may be compromised if errors are not addressed

• Monitoring and alerting systems should be in place to detect and handle failures

• Re-running the failed job or implementing error handling mechanisms can help prevent issues in the future
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Q2. What is difference repartition and coalesce
Ans. 
Repartition increases the number of partitions in a DataFrame, while coalesce reduces the number of partitions without shuffling data.
• Repartition involves a full shuffle of the data across the cluster, which can be expensive.

• Coalesce minimizes data movement by only creating new partitions if necessary.

• Repartition is typically used when increasing parallelism or evenly distributing data, while coalesce is used for reduc...read more
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Q1. Write sql code to get the city1 city2 distance of table if city1 and city2 tables can repeat
Ans. 
SQL code to get the city1 city2 distance of table with repeating city1 and city2 values
• Use a self join on the table to match city1 and city2

• Calculate the distance between the cities using appropriate formula

• Consider using a subquery if needed
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Q2. How is data partitioned in pipeline
Ans. 
Data partitioning in a pipeline involves dividing data into smaller chunks for processing and analysis.
• Data can be partitioned based on a specific key or attribute, such as date, location, or customer ID.

• Partitioning helps distribute data processing tasks across multiple nodes or servers for parallel processing.

• Common partitioning techniques include range partitioning, hash partitioning, and list partitioning.

• Example: ...read more
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Q1. Asked about my previous and current project related questions
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Q2. Mostly asked question from my resume
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