8 HashiCorp SQL Interview Questions (Updated 2024)
At HashiCorp, SQL is used all the damn time for analyzing product usage data to inform strategic decisions, and for their database secrets engine product. That's why HashiCorp often tests SQL questions in interviews for Data Science, Analytics, and & Data Engineering jobs.
As such, to help you ace the HashiCorp SQL interview, we've curated 8 HashiCorp SQL interview questions – able to answer them all?
8 HashiCorp SQL Interview Questions
SQL Question 1: Calculate Monthly Average Rating For Each Product
HashiCorp has been accumulating reviews for each product from its users and we'd like to explore this data a bit. Specifically, your task is to write a SQL query that calculates the average review rating (stars) for each product, for each month, based on the submit date.
Example Input:
| review_id | user_id | submit_date | product_id | stars |
|---|---|---|---|---|
| 6171 | 123 | 2022-06-08 | 50001 | 4 |
| 7802 | 265 | 2022-06-10 | 69852 | 4 |
| 5293 | 362 | 2022-06-18 | 50001 | 3 |
| 6352 | 192 | 2022-07-26 | 69852 | 3 |
| 4517 | 981 | 2022-07-05 | 69852 | 2 |
The output should be a table where each row represents a specific month and product combination, and the columns contain the product id, month (in the format 'YYYY-MM'), and average stars for that specific month and product.
Example Output:
| mth | product | avg_stars |
|---|---|---|
| 2022-06 | 50001 | 3.50 |
| 2022-06 | 69852 | 4.00 |
| 2022-07 | 69852 | 2.50 |
Answer:
Here is the PostgreSQL query that can solve this problem:
This query first groups the reviews by both the month of submit date (in 'YYYY-MM' format) and the product_id, then it calculates the average stars for each group. It presents the result in a new table with columns for the month, product id, and the calculated average stars. Because AVG() is an aggregate function, it can calculate an average over each group of rows that share the same mth and product value.
p.s. Window functions show up super frequently during SQL interviews, so practice the 27+ window function questions on DataLemur
SQL Question 2: Calculate Average Customer Lifetime Value from Multiple Tables
You are a data analyst at HashiCorp and have been asked to calculate the average customer lifetime value (CLV) for customers who made their first purchase in 2021, and whose CLV is greater than $500. In order to calculate CLV, you need to sum up all the orders' total value of each customer.
You have two tables at your disposal: and .
Example Input:
| customer_id | first_purchase_date |
|---|---|
| 1 | 2021-01-31 |
| 2 | 2021-04-12 |
| 3 | 2020-09-18 |
| 4 | 2021-07-21 |
| 5 | 2020-05-02 |
Example Input:
| order_id | customer_id | order_date | total_value |
|---|---|---|---|
| 1 | 1 | 2021-01-31 | 120.00 |
| 2 | 1 | 2021-02-12 | 220.00 |
| 3 | 2 | 2021-04-15 | 50.00 |
| 4 | 3 | 2020-10-06 | 330.00 |
| 5 | 4 | 2021-08-25 | 510.00 |
| 6 | 5 | 2020-06-01 | 220.00 |
Answer:
This SQL query first joins the and tables based on the field. It then filters records for customers whose was in the year 2021 by using the function. The query then groups the customers by and calculates the total order value of each customer with . The clause is then used to retain only the customers whose calculated total order value is greater than $500. The final results are then ordered in descending order based on the calculated total order values.
SQL Question 3: Can you explain what an index is and the various types of indexes?
An index in a database is a data structure that helps to quickly find and access specific records in a table.
For example, if you had a database of HashiCorp customers, you could create a primary index on the column.
Having a primary index on the column can speed up performance in several ways. For example, if you want to retrieve a specific customer record based on their , the database can use the primary index to quickly locate and retrieve the desired record. The primary index acts like a map, allowing the database to quickly find the location of the desired record without having to search through the entire table.
Additionally, a primary index can also be used to enforce the uniqueness of the column, ensuring that no duplicate values are inserted into the table. This can help to prevent errors and maintain the integrity of the data in the table.
SQL Question 4: Average execution time of Terraform commands
As a data analyst at HashiCorp, you have been tasked with determining the average execution time of commands for performance testing. Your work should provide crucial insights into where Terraform, one of HashiCorp's flagship products, can be improved.
The command execution logs are stored in a table named as shown below:
Example Input:
| log_id | user_id | execution_date | command_name | execution_time_in_sec |
|---|---|---|---|---|
| 4001 | 119 | 06/01/2022 00:00:00 | apply | 12 |
| 8187 | 202 | 06/03/2022 00:00:00 | plan | 6 |
| 3492 | 235 | 06/04/2022 00:00:00 | apply | 15 |
| 6743 | 143 | 07/10/2022 00:00:00 | plan | 10 |
| 3832 | 266 | 07/15/2022 00:00:00 | apply | 9 |
You need to find the average execution time for each unique command [e.g., apply, plan].
Example Output:
| command_name | avg_execution_time |
|---|---|
| apply | 12.0 |
| plan | 8.0 |
Answer:
You can find the average execution time by using the function in . Here is a query that can solve this problem:
This query works by grouping the data according to the name of the command (). For each group of commands with the same name, it calculates the average execution time using the function. As a result, we get the average execution time for each unique command.
To practice a very similar question try this interactive Amazon Server Utilization Time Question which is similar for calculating execution times or this Stripe Repeated Payments Question which is similar for performing temporal analysis.
SQL Question 5: What's the difference between a one-to-one and one-to-many relationship?
In database schema design, a one-to-one relationship between two entities is characterized by each entity being related to a single instance of the other. An example of this is the relationship between a US citizen and their social-security number (SSN) - each citizen has one SSN, and each SSN belongs to one person.
On the other hand, a one-to-many relationship is when one entity can be associated with multiple instances of the other entity. A teacher's relationship with their classes is an example of this - a teacher can teach many classes, but each class is only associated with one teacher.
SQL Question 6: Click-through and Conversion Rates for HashiCorp Products
HashiCorp, a software company that provides cloud infrastructure automation technology, wants to analyze the effectiveness of their various product pages. They measure this by looking at both click-through rates from their general product list page to individual product pages, and the conversion rates from viewing a product page to downloading the product.
Given the following two tables and , write a PostgreSQL query to find out the click-through rate from the product list page to each individual product page, and the conversion rate from viewing a product page to downloading the product for each product.
Example Input:
Example Input:
Answer:
This query calculates the click-through rate as the number of times the previous page was the product list divided by the total number of views for each product. The conversion rate is calculated as the number of times a view results in a download divided by the total number of views for each product. Both rates are then sorted from the highest to lowest.
To solve another question about calculating rates, solve this TikTok SQL Interview Question within DataLemur's interactive coding environment:
SQL Question 7: What do the SQL commands / do?
For a tangible example of in PostgreSQL, suppose you were doing an HR Analytics project for HashiCorp, and had access to HashiCorp's contractors and employees data. Assume that some employees were previously contractors, and vice versa, and thus would show up in both tables.
You could use operator to find all contractors who never were a employee using this query:
Note that is available in PostgreSQL and SQL Server, while is the equivalent operator which is available in MySQL and Oracle (but don't worry about knowing which RDBMS supports which exact commands since HashiCorp interviewers aren't trying to trip you up on memorizing SQL syntax).
SQL Question 8: Computing Total and Average Spend Using Mathematical Functions
At HashiCorp, we are keen to track the total and average orders for multiple products across varying periods. You are expected to solve the given scenario using the mathematical functions and operators in SQL.
The data team provides you the following table which contains order_id, product_id, customer_id, order_date, quantity and unit_price fields. You are expected to calculate the total and average order value by product and month.
Example Input:
| order_id | product_id | customer_id | order_date | quantity | unit_price |
|---|---|---|---|---|---|
| 1001 | 2001 | 3001 | 07/01/2021 00:00:00 | 3 | 15.00 |
| 1002 | 2001 | 3002 | 07/15/2021 00:00:00 | 2 | 15.00 |
| 1003 | 2002 | 3003 | 07/20/2021 00:00:00 | 1 | 25.00 |
| 1004 | 2002 | 3001 | 08/01/2021 00:00:00 | 2 | 25.00 |
| 1005 | 2001 | 3003 | 08/15/2021 00:00:00 | 1 | 15.00 |
Your task is to write an SQL query to compute the total order value () and the average order value () rounded to the nearest whole number for each product by month.
Example Output:
| mth | product | total_order_value | avg_order_value |
|---|---|---|---|
| 7 | 2001 | 75.00 | 37.00 |
| 7 | 2002 | 25.00 | 25.00 |
| 8 | 2001 | 15.00 | 15.00 |
| 8 | 2002 | 50.00 | 50.00 |
Answer:
This query first extracts the month from the order_date, and then groups the data by the month and the product_id. The total_order_value is computed by summing the for each group, and the avg_order_value is found by averaging the for each group. The ROUND function is used to round the average value to the nearest whole number. The final results are ordered by the month and product_id.
To practice a very similar question try this interactive Amazon Highest-Grossing Items Question which is similar for calculating total and highest sales or this CVS Health Pharmacy Analytics (Part 1) Question which is similar for calculating most profitable products.
HashiCorp 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.
Besides solving the above HashiCorp SQL interview questions, you should also solve the 200+ DataLemur SQL Interview Questions which come from companies like Netflix, Google, and Amazon.
Each interview question has multiple hints, detailed solutions and best of all, there's an interactive coding environment so you can instantly run your query and have it executed.
To prep for the HashiCorp SQL interview you can also be a great idea to practice SQL questions from other tech companies like:
But if your SQL query skills are weak, don't worry about jumping right into solving questions – go learn SQL with this DataLemur SQL tutorial.
This tutorial covers things like WHERE vs. HAVING and WHERE with AND/OR/NOT – both of these pop up routinely in SQL job interviews at HashiCorp.
HashiCorp Data Science Interview Tips
What Do HashiCorp Data Science Interviews Cover?
In addition to SQL query questions, the other question categories to prepare for the HashiCorp Data Science Interview are:
- Statistics Interview Questions
- Coding Questions in Python or R
- Data Case Study Questions
- ML Interview Questions
- Behavioral Interview Questions
How To Prepare for HashiCorp Data Science Interviews?
The best way to prepare for HashiCorp Data Science interviews is by reading Ace the Data Science Interview. The book's got:
- 201 Interview Questions from companies like Google, Tesla, & Goldman Sachs
- A Crash Course on Stats, ML, & Data Case Studies
- Amazing Reviews (900+ 5-star reviews on Amazon)