Hexaware Technologies Interview Questions, Process, and Tips

Q1. Difference between single & first in linq
Ans. 
Single returns the only element of a sequence, or a default value if the sequence is empty. First returns the first element of a sequence, or a default value if the sequence contains no elements.
• Single throws an exception if the sequence contains more than one element, while First does not.

• Single is useful when you expect only one element in the sequence, while First is used when you just need the first element.

• Example...read more
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Q2. Difference between ref & out keyword
Ans. 
ref is used for passing a variable by reference, out is used for returning a value from a method
• ref keyword is used to pass a variable by reference, allowing the method to modify the variable

• out keyword is used to return a value from a method, the variable passed must be assigned a value within the method

• ref parameters must be initialized before passing to the method, out parameters do not need to be initialized
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Q1. Types of cluster in data bricks??
Ans. 
Types of clusters in Databricks include Standard, High Concurrency, and Single Node clusters.
• Standard cluster: Suitable for running single jobs or workflows.

• High Concurrency cluster: Designed for multiple users running concurrent jobs.

• Single Node cluster: Used for development and testing purposes.
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Q2. Highest 2nd salary in the employee table?
Ans. 
To find the highest 2nd salary in the employee table, you need to use SQL query with the ORDER BY and LIMIT clauses.
• Use SQL query with ORDER BY clause to sort salaries in descending order

• Use LIMIT 1,1 to get the second highest salary
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Q3. Find the duplicate row ?
Ans. 
Use SQL query with GROUP BY and HAVING clause to find duplicate rows.
• Use GROUP BY to group rows with same values

• Use HAVING COUNT(*) > 1 to filter out duplicate rows

• Example: SELECT column1, column2, COUNT(*) FROM table_name GROUP BY column1, column2 HAVING COUNT(*) > 1
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Q4. What is Azure synapse architecture?
Ans. 
Azure Synapse is a cloud-based analytics service that brings together big data and data warehousing.
• Azure Synapse integrates big data and data warehousing capabilities in a single service

• It allows for data ingestion, preparation, management, and serving for BI and machine learning

• Supports both serverless and provisioned resources for data processing

• Offers integration with Azure Machine Learning, Power BI, and Azure Dat
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Q1. Tell me about yourself
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Q2. Tell me about your hobbies
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Verbal reasoning and filling nouns and clusters

Hr final round seems to be about company shift timings and confirmation

Q1. Tell me about your current project? Have you used any AWS services?
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Q2. Can you explain about EMR andEC2 instance?
Ans. 
EMR is a managed Hadoop framework for processing large amounts of data, while EC2 is a scalable virtual server in AWS.
• EMR stands for Elastic MapReduce and is a managed Hadoop framework for processing large amounts of data.

• EC2 stands for Elastic Compute Cloud and is a scalable virtual server in Amazon Web Services (AWS).

• EMR allows for easy provisioning and scaling of Hadoop clusters, while EC2 provides resizable compute...read more
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Q3. What type of schemas did you use for your project. (Star schema, Snowflake Schema)
Ans. 
I have experience working with both Star and Snowflake schemas in my projects.
• Star schema is a denormalized schema where one central fact table is connected to multiple dimension tables.

• Snowflake schema is a normalized schema where dimension tables are further normalized into sub-dimension tables.

• Used Star schema for simpler, smaller datasets where performance is a priority.

• Used Snowflake schema for complex, larger dat...read more
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Q4. Have you used python, pyspark in your projects?
Ans. 
Yes, I have used Python and PySpark in my projects for data engineering tasks.
• I have used Python for data manipulation, analysis, and visualization.

• I have used PySpark for big data processing and distributed computing.

• I have experience in writing PySpark jobs to process large datasets efficiently.
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Q5. Do you have any experience with serverless schema?
Ans. 
Yes, I have experience with serverless schema.
• I have worked with AWS Lambda to build serverless applications.

• I have experience using serverless frameworks like Serverless Framework or AWS SAM.

• I have designed and implemented serverless architectures using services like AWS API Gateway and AWS DynamoDB.
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