8 Taboola SQL Interview Questions (Updated 2024)
Taboola employees write SQL queries daily for analyzing data trends to optimize content recommendations and managing databases to ensure efficient data storage and retrieval. That's why Taboola asks SQL problems during interviews for Data Science and Data Engineering positions. Thus, to help you prep, here's 8 Taboola SQL interview questions – can you answer each one?
8 Taboola SQL Interview Questions
SQL Question 1: Calculate the Running Total of Clicks per Publisher
Assume you're working with a dataset at Taboola that tracks the number of clicks that each publisher gets on a daily basis. Taboola would like to see how the total number of clicks per publisher has been increasing over time.
Given the following example input:
Example Input:
| date | publisher_id | clicks |
|---|---|---|
| 2022-01-01 | 1 | 5000 |
| 2022-01-02 | 1 | 7000 |
| 2022-01-03 | 2 | 12000 |
| 2022-01-04 | 2 | 6000 |
| 2022-01-05 | 1 | 8000 |
| 2022-01-06 | 2 | 15000 |
Write a SQL query that returns a table that contains the date, publisher_id, the number of clicks on that day, and the running total of clicks for that publisher until that date, ordered by date per publisher.
Your output should look like this:
Example Output:
| date | publisher_id | clicks | running_total |
|---|---|---|---|
| 2022-01-01 | 1 | 5000 | 5000 |
| 2022-01-02 | 1 | 7000 | 12000 |
| 2022-01-05 | 1 | 8000 | 20000 |
| 2022-01-03 | 2 | 12000 | 12000 |
| 2022-01-04 | 2 | 6000 | 18000 |
| 2022-01-06 | 2 | 15000 | 33000 |
Answer:
Here is the SQL query that would solve this:
The window function with clause is used here to create a running total. By using we ensure that the running total is calculated separately for each publisher. The setting specifies that we want to sum over all previous rows within the current partition. Finally, we order the result by and to get the expected output.
This query helps Taboola understand the accumulated click performance overtime on publisher basis. Hence, they can identify the major contributors for their ad click and shape their marketing strategy accordingly.
For more window function practice, solve this Uber SQL problem within DataLemur's interactive SQL code editor:
SQL Question 2: Top 3 Salaries
Given a table of Taboola employee salary data, write a SQL query to find the top three highest paid employees in each department.
Taboola Example Input:
| employee_id | name | salary | department_id |
|---|---|---|---|
| 1 | Emma Thompson | 3800 | 1 |
| 2 | Daniel Rodriguez | 2230 | 1 |
| 3 | Olivia Smith | 2000 | 1 |
| 4 | Noah Johnson | 6800 | 2 |
| 5 | Sophia Martinez | 1750 | 1 |
| 8 | William Davis | 6800 | 2 |
| 10 | James Anderson | 4000 | 1 |
Example Input:
| department_id | department_name |
|---|---|
| 1 | Data Analytics |
| 2 | Data Science |
Example Output:
| department_name | name | salary |
|---|---|---|
| Data Analytics | James Anderson | 4000 |
| Data Analytics | Emma Thompson | 3800 |
| Data Analytics | Daniel Rodriguez | 2230 |
| Data Science | Noah Johnson | 6800 |
| Data Science | William Davis | 6800 |
You can solve this question and run your code right in DataLemur's online SQL environment:
Answer:
We use the DENSE_RANK() window function to generate unique ranks for each employee's salary within their department, with higher salaries receiving lower ranks. Then, we wrap this up in a CTE and filter the employees with a ranking of 3 or lower.
If the code above is tough, you can find a step-by-step solution with hints here: Top 3 Department Salaries.
SQL Question 3: How do the and window functions differ from each other?
In SQL, both and are used to rank rows within a result set. The key difference between the two functions is how deal with two or more rows having the same value in the ranked column (aka how the break ties).
RANK(): When there's a tie, leaves a gap in the ranking. For example, if three rows are tied for 2nd place, the RANK() function will assign a rank of 2 to the first of these rows, a rank of 3 to the second row, and a rank of 4 to the third row.
DENSE_RANK(): For ties, does not leave a gap in the ranking. Instead, it assigns the same rank to all tied rows, and then makes the next row 1 bigger. Confusing, I know, but here's an example to make it more clear: if three rows are tied for 3rd place, the function will assign a rank of 3 to all three rows, and then assign a rank of 4 to the next row.
SQL Question 4: Average Campaign Click Through Rates
You are a data analyst at Taboola, a company that provides targeted ads. For each campaign, the database records the number of impressions (number of times the ad was displayed) and the number of clicks (number of times the ad was clicked on) each day.
Given a database in the following form, write a query to find the average click through rate (defined as the number of clicks divided by the number of impressions) for each campaign from January 1, 2022, to December 31, 2022.
Example Input:
| campaign_id | date | impressions | clicks |
|---|---|---|---|
| 1001 | 01/01/2022 | 5000 | 50 |
| 1002 | 01/02/2022 | 8000 | 160 |
| 1001 | 01/03/2022 | 4500 | 45 |
| 1003 | 01/04/2022 | 7000 | 140 |
| 1002 | 01/05/2022 | 6000 | 120 |
The output should give the campaign_id and the click through rate, sorted by the campaign_id in ascending order.
Answer:
This SQL query first uses a WHERE clause to filter out all the campaigns that were not held between January 1, 2022, and December 31, 2022. Then, it groups the data by the campaign_id. For each campaign, it calculates the total number of clicks and the total number of impressions, and divides the two to get the average click through rate. Finally, it sorts the output by the campaign_id in ascending order.
SQL Question 5: Can you explain the concept of a cross-join, and their purpose?
A cross-join, also known as a cartesian join, is a type of join that returns the cross-product of two tables. In a cross-join, each row from the first table is paired with every row from the second table, resulting in a new table that has a row for each possible combination of rows from the two input tables.
For example, say you worked on the Marketing Analytics team at Taboola, and needed to understand what advertising copy (text) goes best with what advertising creative (the photo that gets posted with the advertisement copy).
Here is an example of a cross-join between a table of ad_copy and a table of ad_creative:
You could this query to generate all possible combinations of ad copy and ad creative to help you create more effective ads for Taboola. Just be careful: if you had 1,000 rows of ad copy and 1,000 different image creatives, the resulting cross-join would have 1 million rows!
SQL Question 6: Calculate the Average Clicks per Content
Taboola is a content recommendation platform that helps publishers generate revenue by promoting relevant articles, videos, products and more to their readers. Visitors interact with these recommendations, generating clicks which is an essential metric for Taboola's business model.
As an interview question, you might be asked to find the average number of clicks each content item receives. This would involve the AVG function, as well as GROUP BY for the content items, and most likely WHERE to filter on specific date ranges.
Here's a simulation of the problem with the table .
Example Input:
| id | content_id | click_date | clicks |
|---|---|---|---|
| 1 | 101 | 01/08/2022 00:00:00 | 120 |
| 2 | 102 | 01/08/2022 00:00:00 | 98 |
| 3 | 103 | 02/08/2022 00:00:00 | 130 |
| 4 | 101 | 02/08/2022 00:00:00 | 150 |
Your task is to write a SQL query to calculate the average number of clicks per content for the month of August 2022.
Answer:
This query groups the data by the , allowing the function to calculate the average number of clicks for each unique content id. The clause filters the data for clicks occurring in August 2022. The result will give you the average clicks each content received for the given month.
To practice a very similar question try this interactive Facebook App Click-through Rate (CTR) Question which is similar for calculating average click metrics or this Amazon Average Review Ratings Question which is similar for average calculations.
SQL Question 7: How can you determine which records in one table are not present in another?
To find records in one table that aren't in another, you can use a and check for values in the right-side table.
Here is an example using two tables, Taboola employees and Taboola managers:
This will return all rows from Taboola employees where there is no matching row in managers based on the column.
You can also use the operator in PostgreSQL and Microsoft SQL Server to return the records that are in the first table but not in the second. Here is an example:
This will retrieve all rows from employees that do not appear in managers. The operator works by retreivingthe rows that are returned by the first query, but not by the second.
Please note that is not supported by all DBMS systems, such as MySQL and Oracle (however, you can use the operator to achieve a similar outcome).
SQL Question 8: Find Clients Based on Given Pattern
Taboola is a company that deals with a massive amount of client data. Suppose you are an SQL developer at Taboola. Your task is to retrieve the entire records of clients residing in 'New York' and whose names start with 'A'. Use the LIKE keyword in your SQL query for this task.
Example Input:
| client_id | name | city |
|---|---|---|
| 1257 | Alex Watson | New York |
| 2856 | Andy Gibb | New York |
| 3452 | Bryan Adams | Los Angeles |
| 5123 | Aaron Paul | New York |
| 6248 | Zoe Johnson | New York |
| 7351 | Annabelle Smith | Los Angeles |
| 8236 | Amelia Harper | New York |
Answer:
This query filters the records from the 'clients' table based on the conditions provided in the WHERE clause. The LIKE keyword used here allows pattern matching. 'New York' exactly matches the city name and 'A%' signifies any string starting with 'A'. So, this query will fetch all the records of clients from New York whose names start with 'A'.
Please note that SQL is case sensitive, so it's best to use functions to convert to upper or lower case if you're unsure of how the data is formatted.
Taboola SQL Interview Tips
The best way to prepare for a SQL interview, besides making sure you have strong SQL fundamentals, is to practice a ton of real SQL questions that were asked in recent job interviews.
Beyond just solving the above Taboola SQL interview questions, you should also solve the 200+ SQL questions on DataLemur which come from companies like Google, Microsoft and Silicon Valley startups.
Each DataLemur SQL question has hints to guide you, full answers and most importantly, there is an interactive coding environment so you can easily right in the browser your query and have it checked.
To prep for the Taboola SQL interview you can also be a great idea to practice interview questions from other tech companies like:
In case your SQL skills are weak, forget about jumping right into solving questions – go learn SQL with this DataLemur SQL Tutorial.
This tutorial covers SQL topics like manipulating string/text data and CASE/WHEN statements – both of which come up routinely during SQL job interviews at Taboola.
Taboola Data Science Interview Tips
What Do Taboola Data Science Interviews Cover?
In addition to SQL query questions, the other types of questions covered in the Taboola Data Science Interview include:
- Probability & Stats Questions
- Python or R Coding Questions
- Product-Sense and Business Case Questions
- ML Modelling Questions
- Resume-Based Behavioral Questions
How To Prepare for Taboola Data Science Interviews?
I'm sort of biased, but I believe the best way to prepare for Taboola Data Science interviews is to read the book I wrote: Ace the Data Science Interview.
The book solves 201 interview questions taken from FAANG (FB, Apple, Amazon, Netflix, Google). It also has a refresher covering Stats, SQL & ML. And finally it's helped a TON of people, which is why it's earned 1000+ reviews on Amazon and a 4.5-star rating.