10 F5 Networks SQL Interview Questions (Updated 2024)

At F5 Networks, SQL crucial for analyzing network traffic data and managing databases for client security optimization. That's why F5 Networks often tests SQL coding questions during interviews for Data Analytics, Data Science, and Data Engineering jobs.

To help you study for the F5 Networks SQL interview, we've curated 10 F5 Networks SQL interview questions – how many can you solve?

10 F5 Networks SQL Interview Questions

SQL Question 1: Calculate the Monthly Average Sales of Products

F5 Networks is a tech company that handles application services and application delivery networking (ADN). Suppose you are given a list of sales records from F5 Networks' sales department. Your task is to write a SQL query to find the average monthly sales for each product.

For simplicity, consider the fiscal month to be equivalent to the calendar month. Sales are recorded in terms of units sold. Suppose we have a table that stores sales records of products, structured as follows:

Example Input:

Answer:

In PostgreSQL, you could answer the question using window functions with PARTITION BY clause. Here´s the SQL query:

In this query, the DATE_TRUNC function is used to truncate the date to its month. The PARTITION BY clause is then used to divide the data into partitions based on the product_id and month. The AVG function is then applied to each partition to compute the average sales for each product on a monthly basis.

This query will give you the average monthly sales for each product as per the records available in the table.

For more window function practice, try this Uber SQL problem on DataLemur's interactive coding environment:

SQL Question 2: Network Traffic Analysis

F5 Networks is a company that specializes in application services and application delivery networking (ADN). Suppose you are tasked with analyzing the network traffic flowing through F5 Network devices. You have two tables, a table that stores all the devices in the network and their details, and a table that logs every single network exchange that goes through these devices.

The table has the following structure:

Example Structure:

The table has the following structure:

Example Structure:

Your task is to find out the total amount of data processed (data_size) by each device over the past week, sorted by the amount of data processed in descending order.

Answer:

This query first joins the device and traffic tables based on their common attribute (). It then filters for traffic data from the past week using a WHERE clause. It uses the SUM function to calculate the total data processed by each device, and groups the result by . Finally, it orders the result in descending order of the calculated total data processed.

SQL Question 3: What is the purpose of the constraint, and when might it be helpful to use it?

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The CHECK constraint is used to set a rule for the data in a column. If a row is inserted or updated and the data in the column does not follow the rule specified by the CHECK constraint, the operation will be unsuccessful.The CHECK constraint is often used in conjunction with other constraints, such as NOT NULL or UNIQUE.

You might consider implementing the CHECK constraint in your database if you want to ensure that certain data meets specific conditions. This can be helpful for maintaining the quality and reliability of your data.

For example, you might use a CHECK constraint to ensure that a column contains only positive numbers, or that a date is within a certain range.

SQL Question 4: Calculate the Average Network Traffic

F5 Networks is a company that provides application delivery networking products like load balancing, network traffic management, etc. to optimize network traffic. Let’s say F5 Networks wants to improve their network performance and plan their network capacity by understanding the average network traffic that they handle. For this purpose, they have the following table which captures traffic data every hour for different network paths identified by their route_id. Your task is to find the average traffic per route.

Example Input:

Example Output:

Answer:

This query calculates the average amount of network traffic for each of the network path. It uses the AVG function, which calculates the average of a set of values. To calculate this average for each network route separately, we use the GROUP BY clause, which groups the data_volume measurements by the route_id. This way, we get the average data_volume for each network route. F5 Networks can use this information to understand their network load better and to strategize on optimizing their network performance.

To practice a very similar question try this interactive Amazon Server Utilization Time Question which is similar for calculating utilization time or this Twitter Tweets' Rolling Averages Question which is similar for handling time series data.

SQL Question 5: Why should you normalize your database?

Normalization can reduce redundancy and improve performance and flexibility in a database.

By dividing larger tables into smaller, more specific ones linked by foreign keys, it is often possible to improve query speed. Note: it is not always the case that query speed will be improved due to costly nature of joins. Still, we think normalization is a good idea because it can also increase flexibility by making it easier to alter individual tables without affecting others, which can be useful for adapting F5 Networks's database to ever-changing business needs.

SQL Question 6: Average Network Traffic by Month

As a networking company, F5 Networks wants to check the average data traffic across its networks every month. Write a SQL query that determines the average data traffic (in MB) by month for each of their routers.

Example Input:

Example Output:

Answer:

This query extracts the month from the 'date_time' column and groups by it along with 'router_id'. It then computes the average data traffic (in MB) for these groups which enables F5 Networks to easily view the average network traffic by month per router. It finally sorts the output by the 'month' and 'router_id' for an organized view.

SQL Question 7: In the context of a database transaction, what does ACID mean?

ACID refers to the four key properties that are essential to the reliable and correct execution of database transactions. These properties are:

Atomicity: ensures that a transaction is treated as a single operation, and either all of the changes are made or none of them are! Basically, the database version of a "-FULL SEND-"

Consistency: ensures that the data is in a consistent state before and after a transaction is completed. For example, if wiring money to a friendly Nigerian prince whose fallen on hard times, consistency ensures that the total value of funds lost in my account is the same amount that's gained in the prince's account!

Isolation: ensures that the intermediate state of a transaction is invisible to other transactions. Back to the wiring-the-prince-some-money example, isolation ensures that another transaction sees the transferred funds in my account OR the princes, but not in both accounts at the same time

Durability: ensures that once a transaction has been completed successfully, the changes made by the transaction are permanent and cannot be undone, even in the event of a system failure. Basically, no taksies backsies (even if your system has a meltdown!).

SQL Question 8: Find Customers from a Specific Region

Consider we have a database of customers for F5 Networks, which includes the names of the customers and the regions they come from. You are given the task to select only those customer records where the region starts with the string "Asia".

Example Input:

Example Output:

Answer:

To solve the problem, we'll use the SQL LIKE keyword in the WHERE clause: .

Your PostgreSQL query for this problem would be:

This query returns all columns () for records in the customers table where the region field starts with ("") the string "Asia". The '%' wildcard character is used after "Asia" to account for additional characters in the region string, like "Asia-Pacific".

SQL Question 9: Join and Analyze Customer and Sales Data

You are analyzing the performance of F5 Network's customer sales. You have two tables - 'customers' and 'sales'. The 'customers' table holds information like customer_id, name, email, and signup_date. The 'sales' table has sales_id, customer_id, product_id, purchase_date, and purchase_amount.

Write a SQL query that provides the name, email, and total purchase amount of each customer who has signed up in the last 30 days.

Assume that today's date is '2022-08-01'.

Example Input:

Example Input:

Answer:

This query joins and on and filters for customers who signed up in the last 30 days. It then sums the purchase amount of each customer by grouping the result by customer name and email.

Because joins come up so often during SQL interviews, try this interactive Snapchat SQL Interview question using JOINS:

SQL Question 10: What is a self-join?

A self-join is a type of join in which a table is joined to itself. To perform a self-join, you need to specify the table name twice in the FROM clause, and give each instance of the table a different alias. You can then join the two instances of the table using a JOIN clause, and use a WHERE clause to specify the relationship between the rows.

Self-joins are the go-to technique for any data analysis that involves pairs of the same thing, like identifying pairs of products that are frequently purchased together like in this Walmart SQL interview question.

For another example, say you were doing an HR analytics project and needed to analyze how much all F5 Networks employees in the same department interact with each other. Here's a self-join query you could use to retrieve all pairs of F5 Networks employees who work in the same department:

This query returns all pairs of F5 Networks employees who work in the same department, and excludes pairs where the employee's id is the same (since this would represent the same F5 Networks employee being paired with themselves).

Preparing For The F5 Networks SQL Interview

Assuming that you've already got basic SQL skills, the next best tip we have to prepare for the F5 Networks SQL interview is to solve as many practice SQL interview questions as you can! Besides solving the above F5 Networks SQL interview questions, you should also solve the 200+ SQL questions on DataLemur which come from companies like Netflix, Airbnb, and Amazon.

Each problem on DataLemur has hints to guide you, fully explained answers along with a discussion board to see how others solved it and most importantly, there is an interactive SQL code editor so you can right in the browser run your query and have it checked.

To prep for the F5 Networks SQL interview you can also be useful to solve SQL questions from other tech companies like:

• Cisco SQL questions

• Palo Alto Networks SQL questions

• Cloudflare SQL questions

• Akamai SQL questions

In case your SQL query skills are weak, don't worry about jumping right into solving questions – strengthen your SQL foundations with this DataLemur SQL Tutorial.

This tutorial covers topics including CASE/WHEN/ELSE statements and math functions like ROUND()/CEIL() – both of these show up routinely in SQL job interviews at F5 Networks.

F5 Networks Data Science Interview Tips

What Do F5 Networks Data Science Interviews Cover?

In addition to SQL query questions, the other types of problems to practice for the F5 Networks Data Science Interview are:

• Statistics Interview Questions
• Coding Questions in Python or R
• Data Case Study Questions
• ML Interview Questions
• Resume-Based Behavioral Questions

How To Prepare for F5 Networks Data Science Interviews?

To prepare for F5 Networks Data Science interviews read the book Ace the Data Science Interview because it's got:

• 201 interview questions taken from Google, Microsoft & tech startups
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