Palantir Interview Questions (11+ Questions)

We have web server that is Nix web server and that Nix web server is running multiple worker processes and some of those worker processes are consuming excess CPU resources. This question is asking us just to record that process ID in the solution txt file. In order to solve this question, we will use ps aux and sort everything by CPU usage. We have list of running processes. Grab everything by word nix. This process at the bottom is using 97% of CPU. Other nginx workers are actually idling at zero. And this nginx worker has process ID of 25. We'll type echo 25 and we will send that into solutions txt.

Troubleshoot 503 Service Unavailable errors by fixing endpoint discovery and backend pod routing. Resolve empty endpoint slices, ensure pods match service selectors, verify pod health, and restore service connectivity. Essential for service reliability, traffic routing, load balancing, and ensuring services can successfully reach healthy backend pods.

Build Kubernetes StatefulSet with leader election: implement high-availability services, configure headless services, and automate failover with sidecar patterns.

We have a deployment workflow where a validation step should only run when a specific configuration file exists. If the file isn't there, the validation should be skipped entirely. We need to check for the file's existence in one step, use that result to conditionally run another step. In GitHub Act...

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We need to create a composite action that bundles common CI/CD steps, like install, build and artifact creation, into one reusable unit. A composite action is a way to bundle multiple steps into a single reusable action. A reusable workflow is called at the job level with something called as uses, w...

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def max_profit(prices: list[int]) -> int:
l, r = 0, 1
max_p = 0

while r < len(prices):
    if prices[l] < prices[r]:
        profit = prices[r] - prices[l]
        max_p = max(max_p, profit)
    else:
        l = r
        
    r += 1
    
return max_p

SQL Query to Retrieve Names and Prices of Products Included in Orders

Objective

Craft a SQL query to retrieve the names and prices of all products that have been included in at least one order.

Additional Information

There are two tables involved: Products and Orders.

The `Produ...

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We'll extract schema information from Parquet file using PyArrow. PyArrow is a Python library that works with columnar data formats, especially with Parquet files. It gives more access to files' metadata, things like schema, row groups, file statistics, and so on. Parquet stores data column by column instead of doing that row by row. It will look at the data stored in each group, analyze the minimum and maximum values for each column, and skip the entire row groups that cannot possibly contain matching data. Here we are required to extract the metadata about the file, column names, data types, amount of rows, size of the file, and type of compression. The result should be saved as JSON report. We will import pyarrow.parquet, that will be aliased as pq. Then we use schema_arrow function to get the full picture of what columns exist and what data type each column has. Num_rows function gives us the total amount of rows in the file. Compression function will return the name of codec, like Snappy or Gzip.

Spark is a big data framework that processes massive amounts of data across multiple machines. Instead of tables, it uses data frames. We have one file, orders.csv, with 50,000 records. Our job here is to cache the data frame, run count twice, measure how long each run takes, and print the results. Spark uses lazy evaluation, which means that it doesn't execute anything when we write a transformation. A transformation is simply an operation that modifies or processes our data. Lazy evaluation doesn't run anything until we specifically ask for a result. If we don't do the caching, then every single iteration reads from the input and produces an output independently. But when we do the caching, then the input is read only once and stored in the distributed memory. The first count reads the CSV file and caches the result, while second one reads from that memory and makes everything much faster.

Objective

To address the interview question, the goal is to formulate an SQL query that effectively retrieves the product_name, sale_date, and amount for all sales within the specific date range of January 1, 2023, to March 31, 2023. The results need to be sorted by sale_date in ascend...

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Master product search testing with Selenium. Learn e-commerce login and search automation for beginners....

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