LTIMindtree Data Engineer Interview Questions and Answers for Freshers

Q1. 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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Q2. 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 projec...read more
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Q3. 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 ...read more
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Q4. 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 ...read more
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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. 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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Q1. Scenario based. Write SQL and pyspark code for a dataset.
Ans. 
SQL and PySpark code examples for data manipulation and analysis.
• Use SQL for structured queries: SELECT, JOIN, GROUP BY.

• Example SQL: SELECT name, COUNT(*) FROM patients GROUP BY name;

• Use PySpark for big data processing: DataFrame API, RDDs.

• Example PySpark: df.groupBy('name').count().show();

• Optimize queries with indexing in SQL and caching in PySpark.
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Q2. If you have to find latest record based on latest timestamp in a table for a particular customer(table is having history) , how will you do it. Self join and nested query will be expensive. Optimized query...read more
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The first round included aptitude, coding, comprehension.

Q1. 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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Q1. 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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It was a basic aptitude test.

Q1. Can you tell me about yourself?
Ans. 
I am a data engineer with a strong background in programming and database management.
• Experienced in designing and implementing data pipelines

• Proficient in SQL, Python, and ETL tools

• Skilled in data modeling and optimization

• Worked on projects involving big data technologies like Hadoop and Spark
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Q2. 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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Q3. Can you provide details about your project?
Ans. 
Developed a real-time data processing system for analyzing customer behavior
• Used Apache Kafka for real-time data streaming

• Implemented data pipelines using Apache Spark for processing large volumes of data

• Utilized machine learning algorithms to predict customer behavior

• Designed and maintained data warehouse for storing and querying processed data
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Q1. Can you provide an introduction about yourself?
Ans. 
Experienced Data Engineer with a background in computer science and a passion for solving complex problems.
• Bachelor's degree in Computer Science

• Proficient in programming languages such as Python, SQL, and Java

• Experience with big data technologies like Hadoop and Spark

• Strong analytical and problem-solving skills

• Worked on projects involving data pipelines, ETL processes, and data warehousing
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Q2. What are your hobbies?
Ans. 
My hobbies include hiking, photography, and playing the guitar.
• Hiking: I enjoy exploring nature trails and challenging myself with different terrains.

• Photography: I love capturing moments and landscapes through my camera lens.

• Playing the guitar: I find relaxation and creativity in strumming chords and learning new songs.
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Q3. Which is your favorite movie
Ans. 
My favorite movie is The Shawshank Redemption.
• Directed by Frank Darabont

• Based on a Stephen King novella

• Themes of hope, friendship, and redemption

• Critically acclaimed and considered one of the greatest films of all time
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