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Wipro Big Data Engineer Interview Questions, Process, and Tips
Top Wipro Big Data Engineer Interview Questions and Answers
- Q1. how do you tune sparks configuration setting's to optimize query performance
- Q2. what strategies do you use to handle data skew and partition imbalance in spark
- Q3. how to handle large spark datasets
Wipro Big Data Engineer Interview Experiences
3 interviews found
Anonymous
Selected
I applied via Naukri.com and was interviewed in Aug 2024. There were 2 interview rounds.
(2 Questions)
- Q1. All type of joins with example
- Ans.
Different types of joins in SQL with examples
Inner Join: Returns rows when there is a match in both tables
Left Join: Returns all rows from the left table and the matched rows from the right table
Right Join: Returns all rows from the right table and the matched rows from the left table
Full Outer Join: Returns all rows when there is a match in either table
- Q2. How to handle large spark datasets
- Ans.
Large Spark datasets can be handled by partitioning, caching, optimizing transformations, and tuning resources.
Partitioning data to distribute workload evenly across nodes
Caching frequently accessed data to avoid recomputation
Optimizing transformations to reduce unnecessary processing
Tuning resources like memory allocation and parallelism for optimal performance
(2 Questions)
- Q1. How do you tune sparks configuration setting's to optimize query performance
- Ans.
Spark configuration settings can be tuned to optimize query performance by adjusting parameters like memory allocation, parallelism, and caching.
Increase executor memory and cores to allow for more parallel processing
Adjust shuffle partitions to optimize data shuffling during joins and aggregations
Enable dynamic allocation to scale resources based on workload demands
Utilize caching to store intermediate results and avo...
- Q2. What strategies do you use to handle data skew and partition imbalance in spark
- Ans.
To handle data skew and partition imbalance in Spark, strategies include using salting, bucketing, repartitioning, and optimizing join operations.
Use salting to evenly distribute skewed keys across partitions
Implement bucketing to pre-partition data based on a specific column
Repartition data based on a specific key to balance partitions
Optimize join operations by broadcasting small tables or using partitioning strategi
Skills evaluated in this interview
I applied via Recruitment Consultant and was interviewed in Jul 2021. There were 3 interview rounds.
Interview Questionnaire
1 Question
- Q1. Basic concepts of big data technologies such as schemas on read and write
Interview Preparation Tips
Interview Questionnaire
2 Questions
- Q1. Spark internal architecture and processing.
- Q2. Hive partition and bucketing real scenarios
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Interview questions from similar companies
I applied via Company Website and was interviewed in Sep 2024. There was 1 interview round.
(3 Questions)
- Q1. Big Data fundamentals concepts on rdd, dataframe and datasets.
- Q2. Spark optimization techniques
- Ans.
Spark optimization techniques involve partitioning, caching, and tuning resource allocation.
Partitioning data to distribute workload evenly
Caching frequently accessed data to avoid recomputation
Tuning resource allocation for optimal performance
- Q3. SQL queries on windows function and joins.
Interview Preparation Tips
Skills evaluated in this interview
I applied via Company Website and was interviewed in Apr 2024. There were 3 interview rounds.
(2 Questions)
- Q1. Mostly about spark topics like shuffeling joins, data skew, and pyspark scenarios
- Q2. Mostly about python and sql scenarios
(2 Questions)
- Q1. About behavioural questions
- Q2. Day to day work and workflow model based questions
(2 Questions)
- Q1. Why you need to join infosys
- Ans.
I want to join Infosys because of its reputation for innovation and growth opportunities.
Infosys is known for its cutting-edge technology solutions and innovative projects.
I am impressed by Infosys' commitment to employee development and career growth.
I believe that joining Infosys will provide me with the opportunity to work on challenging projects and enhance my skills.
- Q2. Self introduction
Interview Preparation Tips
I applied via Company Website and was interviewed in Apr 2024. There were 3 interview rounds.
Questions on software and system designs
Helps employer identify particular personality traits like leadership, confidence, interpersonal and teamwork skills of potential employees
(2 Questions)
- Q1. Why do you want this job? Again, companies want to hire people who are passionate about the job, so you should have a great answer about why you want the ...
- Q2. This opportunity can help me in many ways to boost my confidence as well as drive my career forward
Interview Preparation Tips
- The role of technology in educat
Job Search Tips & Resources
More questions about coding in sql & pyspark
Interview Preparation Tips
Murugan R
Selected
I applied via Job Portal and was interviewed in Sep 2023. There were 3 interview rounds.
Easy only so prepare well that's it
(5 Questions)
- Q1. What method you use
- Ans.
I use a combination of programming languages, tools, and frameworks to analyze and process large datasets.
Utilize programming languages like Python, Java, or Scala for data processing
Leverage tools like Hadoop, Spark, or Kafka for distributed computing
Implement frameworks like MapReduce or Apache Flink for data analysis
Use SQL or NoSQL databases for data storage and retrieval
- Q2. Why you lleave current company
- Q3. What skill you have
- Q4. Tell about ur project
- Q5. What you implemented
- Ans.
Implemented a real-time data processing system using Apache Kafka and Spark for analyzing customer behavior.
Developed data pipelines to ingest, process, and analyze large volumes of data
Utilized Apache Kafka for real-time data streaming
Implemented machine learning algorithms for predictive analytics
Optimized data storage and retrieval for faster query performance
Interview Preparation Tips
Skills evaluated in this interview
Manshi Raghuvanshi
(1 Question)
- Q1. Coalesce vs repartition
- Ans.
Coalesce is used to reduce the number of partitions in a DataFrame, while repartition is used to increase the number of partitions.
Coalesce is a narrow transformation that can only decrease the number of partitions without shuffling data.
Repartition is a wide transformation that can both increase or decrease the number of partitions and involves shuffling data across the cluster.
Coalesce is more efficient for reducing ...
Rank vs dense rank quetions ctes
Python data structure
I applied via Naukri.com and was interviewed in Jul 2023. There were 2 interview rounds.
(2 Questions)
- Q1. Basic Questions of Scala Functional Programming concepts.
- Q2. Spark internal working and optimization techniques
- Ans.
Spark internal working and optimization techniques
Spark uses Directed Acyclic Graph (DAG) for optimizing workflows
Lazy evaluation helps in optimizing transformations by combining them into a single stage
Caching and persistence of intermediate results can improve performance
Partitioning data can help in parallel processing and reducing shuffle operations
Interview Preparation Tips
Skills evaluated in this interview
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