Nvidia Interview Questions (11+ Questions)

In production systems alerts often come as a process Id saying certain process IDs are having troubles, difficulties beyond the memory limits and so on. Often we need a script that will let us debug problems that are hinted to us via process id and go to the service name. We need to create a trace service sh batch script that will give us the status, the service name, its last 20 logs and all that just by providing the process id. We will try system CTL status 2031, which will show us the status of this system and the name data processing service. Since we know the name of the service, we can run system CTL status by the name of the service. We'll have first argument as variable PID. We need to extract the service name. We can use awk and print the second column, which was the name of the service. We need to print status and logs. Make this executable.

We have a container image net are broken, built from this file and this container has connectivity issues and cannot connect to example.com. We need to review Docker file, entry point, Docker configuration JSON file. And once it's done we need to rebuild this image and retry connecting to example.co...

🔒 Premium Content

Detailed explanation and solution available for premium members.

Upgrade to Premium →

We have a deployment workflow that sometimes fails. When it fails, the values.yaml config file has already been updated with the bad image tag, and the team has to manually revert it. If the deployment fails, automatically restore values.yaml to the version from the previous commit, and commit the fix. A rollback is reverting to a known good state after something breaks. If we say needs deploy and if failure, the rollback job only runs when the deploy job has failed. By default, actions/checkout only fetches the latest commit, which is with the shallow clone of fetch depth one by default. So we set fetch depth to zero to fetch the full Git history, and this lets us use Git checkout HEAD 1 on values.yaml to restore the file from one commit back. So needs and if failure creates a backup plan pattern. The double hyphen separates the revision from the file path. Then we are running git add values.yaml, which stages the restored file.

Parse and deep merge two YAML configuration files in Python, extract a specific nested section from the merged result, and save it as JSON output.

def check_valid_string(s: str) -> bool:
left_min = 0
left_max = 0

for c in s:
    if c == "(":
        left_min += 1
        left_max += 1
    elif c == ")":
        left_min -= 1
        left_max -= 1
    else:
        left_min -= 1
        left_max += 1
        
    if left_max < 0:
        return False
        
    if left_min < 0:
        left_min = 0
        
return left_min == 0

Generating Departmental Salary Reports in SQL: A Comprehensive Guide

When preparing for data-centric roles or refining your SQL skills, complex queries can be an important part of the learning curve. One often encountered challenge is generating detailed reports from relational databases. Here,...

🔒 Premium Content

Detailed explanation and solution available for premium members.

Upgrade to Premium →

Comprehensive Guide to Answering the SQL Interview Question: Filtering Shipped or Delivered Orders

Objective

To excel at this SQL interview question, you need to craft a query that retrieves the order ID, customer name, status, and total amount for orders with statuses of either 'Shipped' ...

🔒 Premium Content

Detailed explanation and solution available for premium members.

Upgrade to Premium →

WITH aggregated AS (
SELECT
md.mortgage_type,
ROUND(SUM(md.interest_rate) / COUNT(um.user_id), 2) AS rate_of_mortgage
FROM {{ ref("mortgage_details") }} md
INNER JOIN {{ ref("user_mortgages") }} um
ON md.mortgage_id = um.mortgage_id
GROUP BY md.mortgage_type
)
SELECT * FROM aggregated

Master PySpark full outer joins by combining Private Equity firms, funds, and investment DataFrames. Learn how to retain unmatched records and handle null values cleanly.

Practice basic data transformations in PySpark. Learn how to filter rows based on numerical conditions and standardize text columns by converting strings to uppercase.

Optimize Your Interview Preparation with This Comprehensive Guide on a SQL Sales Calculation Query

Objective

Imagine you're preparing for your next SQL interview, and you encounter a question that requires you to calculate total sales across multiple regions and product categories. The ma...

🔒 Premium Content

Detailed explanation and solution available for premium members.

Upgrade to Premium →