Infosys Senior Data Engineer Interview Questions, Process, and Tips

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Q1. What is vertices and edges on a dag?
Ans. 
Vertices are nodes and edges are connections between nodes in a directed acyclic graph (DAG).
• Vertices represent the tasks or operations in a DAG.

• Edges represent the dependencies between tasks or operations.

• Vertices can have multiple incoming edges and outgoing edges.

• Edges can be weighted to represent the cost or time required to complete a task.

• Examples of DAGs include data processing pipelines and task scheduling syst
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Q2. How do u calculate the resources based on the number of cores and memory given..ex - 16 cores with 64 gb... What is overhead, driver memory etc
Ans. 
Calculating resources based on cores and memory given with overhead and driver memory
• Calculate the total memory available by multiplying the number of cores with memory per core

• Deduct the overhead memory required for the operating system and other processes

• Allocate driver memory for each executor based on the workload

• Consider the memory requirements for other services like Hadoop, Spark, etc.

• Example: For 16 cores with ...read more
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Q1. Rank types in SQL
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Rank types in SQL
• RANK(): assigns a unique rank to each row within the result set

• DENSE_RANK(): assigns a unique rank to each row within the result set, but may have gaps

• ROW_NUMBER(): assigns a unique number to each row within the result set
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Q2. Row_Number in sql server
Ans. 
Row_Number is a function in SQL Server that assigns a unique sequential number to each row in a result set.
• Row_Number is used to generate a unique identifier for each row in a result set

• It is commonly used for pagination, ranking, and partitioning data

• The function requires an ORDER BY clause to determine the order of the rows

• The result of Row_Number is an integer value starting from 1
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Q3. Performance Tuning in sql
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Performance tuning in SQL involves optimizing queries, indexes, and database configurations to improve query execution time.
• Identify and optimize slow-performing queries

• Create and maintain appropriate indexes

• Partition large tables to improve query performance

• Optimize database configurations and server settings

• Use query execution plans to identify bottlenecks

• Consider denormalization for frequently accessed data

• Use appro...read more
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