Big Data Engineer Lead

Big Data Engineer Lead Interview Questions and Answers

Updated 3 Jul 2024
search-icon

Q1. how did you do batch processing. why did you choose that technique

Ans.

I used batch processing by breaking down large data sets into smaller chunks for easier processing.

  • Implemented batch processing using tools like Apache Spark or Hadoop

  • Chose batch processing for its ability to handle large volumes of data efficiently

  • Split data into smaller batches to process sequentially for better resource management

Q2. how will you handle 100 files of 100 GB size files in pyspark. Design end to end pipleline.

Ans.

I will use PySpark to handle 100 files of 100 GB size in an end-to-end pipeline.

  • Use PySpark to distribute processing across a cluster of machines

  • Read files in parallel using SparkContext and SparkSession

  • Apply transformations and actions to process the data efficiently

  • Utilize caching and persisting to optimize performance

  • Implement fault tolerance and recovery mechanisms

  • Use appropriate data storage solutions like HDFS or cloud storage

Q3. Code to print top two highest numbers from an array

Ans.

Code to print top two highest numbers from an array

  • Sort the array in descending order

  • Print the first two elements of the sorted array

Q4. Is passible map-reduce have 0 reducer ?

Ans.

Yes, it is possible to have a MapReduce job with 0 reducers.

  • In some cases, the output of the map phase may not require any further processing or aggregation, so having 0 reducers is sufficient.

  • For example, if the goal of the MapReduce job is simply to filter out certain data points based on a condition, there may be no need for a reducer.

  • Having 0 reducers can also be useful for jobs where the output of the map phase is already in the desired format and does not need any addit...read more

Are these interview questions helpful?

Q5. Optimization techniques

Ans.

Optimization techniques are methods used to improve the performance of algorithms and systems.

  • Use parallel processing to speed up computations

  • Implement caching to reduce data retrieval time

  • Optimize data storage by using efficient data structures

  • Utilize indexing to quickly locate specific data

  • Fine-tune algorithms for better performance

Q6. Write code in spark

Ans.

Code in Spark for Big Data Engineer Lead interview

  • Use SparkSession to create a Spark application

  • Read data from a source like HDFS or S3

  • Perform transformations and actions on the data using Spark RDDs or DataFrames

  • Write the processed data back to a sink like HDFS or S3

Share interview questions and help millions of jobseekers 🌟

man-with-laptop

Big Data Engineer Lead Jobs

Recro.io - Lead Big Data Engineer - Hadoop/Spark (8-13 yrs) 8-13 years
Recro
4.2
Senior / Lead Big Data Engineer 7-12 years
Photon
4.0
Pune
Lead Big Data Engineer - Spark/Scala (10-20 yrs) 10-20 years
Racrosoft Technologies
3.8
Interview Tips & Stories
Ace your next interview with expert advice and inspiring stories

Interview experiences of popular companies

3.7
 • 536 Interviews
3.3
 • 519 Interviews
3.8
 • 214 Interviews
4.1
 • 35 Interviews
View all

Calculate your in-hand salary

Confused about how your in-hand salary is calculated? Enter your annual salary (CTC) and get your in-hand salary

Big Data Engineer Lead Interview Questions
Share an Interview
Stay ahead in your career. Get AmbitionBox app
qr-code
Helping over 1 Crore job seekers every month in choosing their right fit company
65 L+

Reviews

4 L+

Interviews

4 Cr+

Salaries

1 Cr+

Users/Month

Contribute to help millions

Made with ❤️ in India. Trademarks belong to their respective owners. All rights reserved © 2024 Info Edge (India) Ltd.

Follow us
  • Youtube
  • Instagram
  • LinkedIn
  • Facebook
  • Twitter