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10+ LTIMindtree Data Engineer Interview Questions and Answers for Freshers

Updated 20 Dec 2024

Q1. If you want very less latency - which is better standalone or client mode?

Ans.

Client mode is better for very less latency due to direct communication with the cluster.

  • Client mode allows direct communication with the cluster, reducing latency.

  • Standalone mode requires an additional layer of communication, increasing latency.

  • Client mode is preferred for real-time applications where low latency is crucial.

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Q2. When a spark job is submitted, what happens at backend. Explain the flow.

Ans.

When a spark job is submitted, various steps are executed at the backend to process the job.

  • The job is submitted to the Spark driver program.

  • The driver program communicates with the cluster manager to request resources.

  • The cluster manager allocates resources (CPU, memory) to the job.

  • The driver program creates DAG (Directed Acyclic Graph) of the job stages and tasks.

  • Tasks are then scheduled and executed on worker nodes in the cluster.

  • Intermediate results are stored in memory o...read more

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Q3. How do you do performance optimization in Spark. Tell how you did it in you project.

Ans.

Performance optimization in Spark involves tuning configurations, optimizing code, and utilizing caching.

  • Tune Spark configurations such as executor memory, number of executors, and shuffle partitions.

  • Optimize code by reducing unnecessary shuffles, using efficient transformations, and avoiding unnecessary data movements.

  • Utilize caching to store intermediate results in memory and avoid recomputation.

  • Example: In my project, I optimized Spark performance by increasing executor me...read more

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Q4. How do you optimize SQL queries?

Ans.

Optimizing SQL queries involves using indexes, avoiding unnecessary joins, and optimizing the query structure.

  • Use indexes on columns frequently used in WHERE clauses

  • Avoid using SELECT * and only retrieve necessary columns

  • Optimize joins by using INNER JOIN instead of OUTER JOIN when possible

  • Use EXPLAIN to analyze query performance and make necessary adjustments

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Q5. Calculate second highest salary using SQL as well as pyspark.

Ans.

Calculate second highest salary using SQL and pyspark

  • Use SQL query with ORDER BY and LIMIT to get the second highest salary

  • In pyspark, use orderBy() and take() functions to achieve the same result

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Q6. 2 types of modes for Spark architecture ?

Ans.

The two types of modes for Spark architecture are standalone mode and cluster mode.

  • Standalone mode: Spark runs on a single machine with a single JVM and is suitable for development and testing.

  • Cluster mode: Spark runs on a cluster of machines managed by a cluster manager like YARN or Mesos for production workloads.

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Q7. What factors should be considered when designing a road curve?

Ans.

Factors to consider when designing a road curve

  • Radius of the curve

  • Speed limit of the road

  • Banking of the curve

  • Visibility around the curve

  • Traffic volume on the road

  • Road surface conditions

  • Presence of obstacles or hazards

  • Environmental factors such as weather conditions

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Q8. What is SparkContext and SparkSession?

Ans.

SparkContext is the main entry point for Spark functionality, while SparkSession is the entry point for Spark SQL.

  • SparkContext is the entry point for low-level API functionality in Spark.

  • SparkSession is the entry point for Spark SQL functionality.

  • SparkContext is used to create RDDs (Resilient Distributed Datasets) in Spark.

  • SparkSession provides a unified entry point for reading data from various sources and performing SQL queries.

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Q9. Write the code to sort the array.

Ans.

Code to sort an array of strings

  • Use the built-in sort() function in the programming language of your choice

  • If case-insensitive sorting is required, use a custom comparator

  • Consider the time complexity of the sorting algorithm used

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Q10. Explain ur experience

Ans.

I have 5 years of experience working as a Data Engineer in various industries.

  • Developed ETL pipelines to extract, transform, and load data from multiple sources into a data warehouse

  • Optimized database performance by tuning queries and indexes

  • Implemented data quality checks to ensure accuracy and consistency of data

  • Worked with cross-functional teams to design and implement data solutions for business needs

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Interview Process at LTIMindtree Data Engineer for Freshers

based on 5 interviews
1 Interview rounds
Technical Round
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