Hexaware Technologies Azure Data Engineer Interview Questions, Process, and Tips

Sql queries and knowledge of different syntaxes

Q1. Find the student with marks greater than 80 in all subjects
Ans. 
Filter students with marks greater than 80 in all subjects
• Iterate through each student's marks in all subjects

• Check if all marks are greater than 80 for a student

• Return the student if all marks are greater than 80
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Q2. Write the syntax to define the schema of a file for loading.
Ans. 
Syntax to define schema of a file for loading
• Use CREATE EXTERNAL TABLE statement in SQL

• Specify column names and data types in the schema definition

• Example: CREATE EXTERNAL TABLE MyTable (col1 INT, col2 STRING) USING CSV
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Q1. How to do performance tuning in adf
Ans. 
Performance tuning in Azure Data Factory involves optimizing data flows and activities to improve efficiency and reduce processing time.
• Identify bottlenecks in data flows and activities

• Optimize data partitioning and distribution

• Use appropriate data integration patterns

• Leverage caching and parallel processing

• Monitor and analyze performance metrics
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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. What is the main advantage of delta lake?
Ans. 
Delta Lake provides ACID transactions, schema enforcement, and time travel capabilities for data lakes.
• ACID transactions ensure data consistency and reliability.

• Schema enforcement helps maintain data quality and prevent data corruption.

• Time travel allows users to access and revert to previous versions of data for auditing or analysis purposes.
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Q2. It enables time travel and support ACID transactions.
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Q1. What is a catalyst optimizer?
Ans. 
The catalyst optimizer is a query optimization engine in Apache Spark that improves performance by generating optimized query plans.
• It is a query optimization engine in Apache Spark.

• It improves performance by generating optimized query plans.

• It uses rule-based and cost-based optimization techniques.

• It leverages advanced techniques like code generation and adaptive query execution.

• Example: Catalyst optimizer in Spark SQ...read more
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