Virtusa Consulting Services Data Engineer Interview Questions, Process, and Tips

Q1. What is the architecture of Apache Spark?
Ans. 
Apache Spark architecture includes a cluster manager, worker nodes, and driver program.
• Apache Spark architecture consists of a cluster manager, which allocates resources and schedules tasks.

• Worker nodes execute tasks and store data in memory or disk.

• Driver program coordinates tasks and communicates with the cluster manager.

• Spark applications run as independent sets of processes on a cluster, coordinated by the SparkCon...read more
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Q2. What is the difference between the reduceBy and groupBy transformations in Apache Spark?
Ans. 
reduceBy is used to aggregate data based on key, while groupBy is used to group data based on key.
• reduceBy is a transformation that combines the values of each key using an associative function and a neutral 'zero value'.

• groupBy is a transformation that groups the data based on a key and returns a grouped data set.

• reduceBy is more efficient for aggregating data as it reduces the data before shuffling, while groupBy shu...read more
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Q3. What is the difference between RDD (Resilient Distributed Datasets) and DataFrame in Apache Spark?
Ans. 
RDD is a low-level abstraction representing a distributed collection of objects, while DataFrame is a higher-level abstraction representing a distributed collection of data organized into named columns.
• RDD is more suitable for unstructured data and low-level transformations, while DataFrame is more suitable for structured data and high-level abstractions.

• DataFrames provide optimizations like query optimization and code...read more
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Q4. What are the different modes of execution in Apache Spark?
Ans. 
The different modes of execution in Apache Spark include local mode, standalone mode, YARN mode, and Mesos mode.
• Local mode: Spark runs on a single machine with one executor.

• Standalone mode: Spark runs on a cluster managed by a standalone cluster manager.

• YARN mode: Spark runs on a Hadoop cluster using YARN as the resource manager.

• Mesos mode: Spark runs on a Mesos cluster with Mesos as the resource manager.
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Q1. What is PySpark, and can you explain its features and uses?
Ans. 
PySpark is a Python API for Apache Spark, used for big data processing and analytics.
• PySpark is a Python API for Apache Spark, a fast and general-purpose cluster computing system.

• It allows for easy integration with Python libraries and provides high-level APIs in Python.

• PySpark can be used for processing large datasets, machine learning, real-time data streaming, and more.

• It supports various data sources such as HDFS, ...read more
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Q2. What is the difference between PySpark and Python?
Ans. 
PySpark is a Python API for Apache Spark, while Python is a general-purpose programming language.
• PySpark is specifically designed for big data processing using Spark, while Python is a versatile programming language used for various applications.

• PySpark allows for distributed computing and parallel processing, while Python is primarily used for sequential programming.

• PySpark provides libraries and tools for working wit...read more
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Q1. What is with clause in SQL ?
Ans. 
WITH clause in SQL is used to create temporary named result sets that can be referenced within the main query.
• WITH clause is used to improve the readability and maintainability of complex SQL queries.

• It allows creating subqueries or common table expressions (CTEs) that can be referenced multiple times.

• The result sets created using WITH clause can be used for recursive queries, data transformation, or simplifying comple...read more
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Coding Test and Web Development

Q1. Project related questions
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Q2. Tell about your Projects
Ans. 
I have worked on various projects involving data engineering, including building data pipelines and optimizing data storage.
• Built a data pipeline using Apache Kafka and Apache Spark to process and analyze real-time streaming data.

• Optimized data storage by implementing data partitioning and indexing techniques in a large-scale data warehouse.

• Developed ETL processes to extract data from various sources, transform it, and...read more
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Q3. Tell me about yourself
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I am a data engineer with experience in designing and implementing data pipelines for large-scale projects.
• Experienced in building and optimizing data pipelines using tools like Apache Spark and Hadoop

• Proficient in programming languages like Python and SQL

• Skilled in data modeling and database design

• Familiar with cloud platforms like AWS and GCP

• Strong problem-solving and analytical skills

• Effective communicator and team
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Q4. Questions about core technologies
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