Ingram Micro Software Engineer Interview Questions and Answers

5 sections in the aptitude

Live coding test about sql and python

Q1. Advance coding round
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Q1. Proper HR discussions
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Q1. Basics of Java OOPS
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How to remove duplicates from an array

Q1. Some basic questions on java
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Q2. One coding question on Java
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Q1. C++ fundamental
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Q2. Reverse linked list
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Q1. Write code of palindrome
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Code to check if a given string is a palindrome or not.
• Create a function that takes a string as input

• Remove all non-alphanumeric characters and convert to lowercase

• Compare the original string with its reverse to check for palindrome
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Q2. How to pass data in angular from component to component
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Data can be passed in Angular from component to component using input properties, output properties, services, and state management libraries like NgRx.
• Use @Input decorator to pass data from parent to child component

• Use @Output decorator to emit events from child to parent component

• Use services to share data between components

• Use state management libraries like NgRx for complex data sharing scenarios
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Q1. Basic questions from oops, collections and springboot, basic queries.
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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.
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Q2. Basics about Azure resources like ADF, Azure Databricks. Explained the project architecture and sone questions on that.
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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
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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
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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
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Q1. Compensation decision and clear your doubts regarding organisation.
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All multiple choices consisting of code output based questions and logical reasoning

Q1. All about project
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Q2. Explain in detail about your project
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