Bounteous x Accolite Lead Engineer Interview Questions and Answers

Array questions asked with sorting and total count for particular number and index print

Linked list coding, hashmap internal coding demonstration.

Q1. Salary expectation , nothing much why you want to join....
Add your answer

Q1. What do you do for performance improvement while using ajax ?
Ans. 
Use caching, minimize data transfer, optimize server-side code.
• Implement caching to reduce server requests

• Minimize data transfer by sending only necessary data

• Optimize server-side code for faster response time
Answered by AI
Add your answer
Q2. What is transaction in database ?
Ans. 
A transaction in a database is a sequence of operations that are treated as a single unit of work.
• Transactions ensure data consistency and integrity.

• They allow multiple operations to be grouped together and either all succeed or all fail.

• ACID properties (Atomicity, Consistency, Isolation, Durability) are maintained in transactions.

• Examples of transactions include transferring money between bank accounts or updating inv
Answered by AI
Add your answer

Q1. What activities do you perform for any new project?
Add your answer
Q2. Can you connect directly to db using jscript ?
Ans. 
Yes, it is possible to connect to a database using JavaScript.
• JavaScript can connect to databases using APIs such as Web SQL, IndexedDB, and MongoDB.

• It is also possible to use Node.js to connect to databases using JavaScript.

• However, it is not recommended to connect to a database directly from client-side JavaScript due to security concerns.
Answered by AI
Add your answer

Q1. Basics about big data tools. Use case on Pyspark. How to add the new column and what is AQE benefits and Delta table optimisation tenchiques.
Add your answer
Q2. Basics about Azure resources like ADF, Azure Databricks. Explained the project architecture and sone questions on that.
Add your answer
Q3. Pyspark optimisation techniques explain and write scd type 2 sample code.
Ans. 
Optimisation techniques in Pyspark and sample code for SCD type 2
• Use broadcast variables to reduce data shuffling

• Partition data based on key columns to improve performance

• Use cache() or persist() to avoid recomputing data

• Use coalesce() or repartition() to reduce the number of partitions

• For SCD type 2, use merge() function to update or insert new records

• Example code for SCD type 2: https://github.com/awantik/pyspark-101
Answered by AI
Add your answer

Q1. How huge data your are working? What are toughest problem you faced and resolved it ?
Ans. 
I have worked with huge data sets in the past.
• I have experience working with data sets ranging from a few gigabytes to several terabytes.

• One of the toughest problems I faced was optimizing a query that was taking too long to execute.

• I resolved it by analyzing the query plan and identifying the bottleneck, then optimizing the query accordingly.

• Another challenge I faced was dealing with data inconsistencies, which I reso...read more
Answered by AI
Add your answer
Q2. Explain you project architecture ? Show some sample codes of the same.
Ans. 
Our project architecture follows a microservices approach with containerization using Docker and orchestration with Kubernetes.
• We have divided our application into smaller, independent services that communicate with each other through APIs.

• Each service is containerized using Docker, allowing for easy deployment and scaling.

• We use Kubernetes for orchestration, which automates the deployment, scaling, and management of o...read more
Answered by AI
Add your answer

Q1. Compensation decision and clear your doubts regarding organisation.
Add your answer