Netflix Interview Questions (11+ Questions)

Learn how to test TCP connectivity to multiple service ports on a remote host using Linux Bash commands. This guide covers verifying reachability of critical services (SSH, DNS, HTTP, HTTPS, MySQL, gRPC) and generating structured connectivity reports, essential for diagnosing intermittent service failures and firewall configuration issues.

We've committed file secrets env, which contains some sensitive credentials and we have to remove this from entire git history. First we'll need to move to the repository directory. Check logs that contains secret env file. For this we'll type git log all to see all logs, one line to see them in one line. In order to filter it by the file name we type hyphen and then name of the file. To see exactly what was changed in those commits we can add hyphen p flag. We need to delete this from our current git history and for this we'll run command called git filter branch. We'll run force flag to change this in entire git history. And we'll use the filter flag that lets us run certain command. And the command is basic Linux syntax rm to remove file. Prune empty flag is used in certain cases that removing this will make the commit useless. Finally, we need to delete the history file, meaning we need to run rm rf to delete everything in the git refs original. In case if we'd like to change also this on the remote origin, we need to run git push force all.

def group_anagrams(strs: list[str]) -> list[list[str]]:
anagram_map = {}
for s in strs:
count = [0] * 26
for c in s:
count[ord(c) - ord('a')] += 1
signature = tuple(count)
if signature not in anagram_map:
anagram_map[signature] = []
anagram_map[signature].append(s)
return list(anagram_map.values())

def max_area_of_island(grid: list[list[int]]) -> int:
ROWS, COLS = len(grid), len(grid[0])
max_area = 0

def dfs(r, c):
    if r < 0 or r >= ROWS or c < 0 or c >= COLS or grid[r][c] == 0:
        return 0
        
    grid[r][c] = 0
    
    return (1 + 
            dfs(r + 1, c) + 
            dfs(r - 1, c) + 
            dfs(r, c + 1) + 
            dfs(r, c - 1))
            
for r in range(ROWS):
    for c in range(COLS):
        if grid[r][c] == 1:
            max_area = max(max_area, dfs(r, c))
            
return max_area

Generate a self-signed X.509 certificate and private key for a development HTTPS service with a specific validity period and Common Name.

How to Write a SQL Query to Retrieve Employee Names, Department Names, and Salaries

Objective

In this article, we will learn how to write a SQL query to retrieve the names of employees, their corresponding department names, and their salaries from the given employees and departments tabl...

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We will need to filter popular videos. Spark is a framework that processes large amounts of data across multiple machines. Instead of tables, it uses data frames. We are given one CSV file that is called Videos. The data frame contains six columns: title of the video, its ID, genre, release year, duration, and number of views. We need to filter everything and keep only videos that have more than one million views and were released in 2019 or later. The result should be saved as result_df. We read the CSV file to a given path and store it in a variable called df for data frame. When header is set to true, it uses first row as column names. At the same time, inferSchema automatically detects data types of those columns. For the condition, we use filter method within data frame and store it in result_df. The condition consists of two statements. First one checks if number of views is greater than one million, and second one ensures that the release year is after 2019. In between, we use AND operator that requires both of the statements to be true.

Master time series calculations in PySpark. Learn how to combine datasets, use the lag window function to retrieve previous row values, and handle gaps in chronological data using conditional logic.

SELECT
SUM(
CASE
WHEN device_type = 'laptop' THEN 1
ELSE 0
END
) AS laptop_views,
SUM(
CASE
WHEN device_type IN ('tablet', 'phone') THEN 1
ELSE 0
END
) AS mobile_views
FROM
viewership;

Google Cloud Storage handles petabytes of data for millions of users worldwide. QA testing of Cloud Storage APIs requires comprehensive validation of bucket operations, permission management, and metrics monitoring to ensure reliable cloud infrastructure services....

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LinkedIn connects over 900 million professionals worldwide, serving as the leading platform for professional networking, career development, and business relationships. QA testing of LinkedIn APIs requires comprehensive validation of profile management, connection requests, content sharing, and comp...

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