11 Equinix SQL Interview Questions - How Many Can You Solve?
At Equinix, SQL is used quite frequently for analyzing data center performance metrics and managing data related to customers' interconnection bandwidth requirements. Over 90 million records are created daily in Equnix's Cassandra database. Because of this, Equinix frequently asks SQL problems in interviews for Data Analytics, Data Science, and Data Engineering jobs.
So, in case you're studying for a SQL Interview, we've curated 11 Equinix SQL interview questions to practice – how many can you solve?
11 Equinix SQL Interview Questions
SQL Question 1: Analyzing Data Center Utilization Over Time
Equinix wants to check the usage of its data centers across different regions over time. The data is stored in the table where the is the name of the region where a data center is located, is the unique identifier of each data center, is the date of data usage, and is the amount of space used in terabytes on a given date. With the help of SQL window functions, write a query to calculate the monthly total, average, and maximum used space across all data centers for each region.
Example Input:
| data_center_id | region_name | date | used_space (TB) |
|---|---|---|---|
| 1 | America | 2022-09-01 | 200 |
| 2 | America | 2022-09-01 | 150 |
| 3 | Asia | 2022-09-01 | 100 |
| 1 | America | 2022-09-02 | 250 |
| 2 | America | 2022-09-02 | 200 |
| 3 | Asia | 2022-09-02 | 120 |
Example Output:
| year_month | region_name | total_used_space (TB) | avg_used_space (TB) | max_used_space (TB) |
|---|---|---|---|---|
| 2022-09 | America | 800 | 200 | 250 |
| 2022-09 | Asia | 220 | 110 | 120 |
Answer:
In this solution, we are using the window function , , and to calculate the total, average, and maximum used space for each region per month respectively. We also make use of the clause to make these calculations for each region separately.
For more window function practice, solve this Uber SQL Interview Question on DataLemur's online SQL coding environment:
SQL Question 2: Filter Customer Records Based on Business Relevant Conditions
Suppose you're working as a data analyst at Equinix, a data center company. You're given a task to analyze the data of customers who have leased space in your data centers in different locations worldwide. Each customer may have one or more contracts for space. You need to find the contracts that are renewing in the next quarter and belong to customers whose payments averaged more than $10,000 per month over the last year.
Given two tables, and , you need:
- From the table: , , , .
- From the table: , , , , .
Write a SQL query to find all information based on the criteria mentioned earlier.
Example Input:
| customer_id | name | billing_address | payment_avg |
|---|---|---|---|
| 101 | Acme Corp | 123 Fake St, San Jose, CA | 9500 |
| 102 | Globex Corp | 456 Main St, Los Angeles, CA | 11000 |
| 103 | Soylent Corp | 789 Wall St, New York, NY | 15000 |
Example Input:
| contract_id | customer_id | data_center_location | start_date | end_date |
|---|---|---|---|---|
| 1 | 101 | San Jose, CA | 2018-04-23 | 2022-04-22 |
| 2 | 102 | Los Angeles, CA | 2019-07-01 | 2023-06-30 |
| 3 | 103 | New York, NY | 2019-12-01 | 2022-12-01 |
| 4 | 102 | San Jose, CA | 2021-01-01 | 2025-12-31 |
Example Output:
| customer_id | name | billing_address | payment_avg | contract_id | data_center_location | start_date | end_date |
|---|---|---|---|---|---|---|---|
| 102 | Globex Corp | 456 Main St, Los Angeles, CA | 11000 | 2 | Los Angeles, CA | 2019-07-01 | 2023-06-30 |
| 103 | Soylent Corp | 789 Wall St, New York, NY | 15000 | 3 | New York, NY | 2019-12-01 | 2022-12-01 |
Answer:
The SQL query to achieve the required results would look something like this:
This query joins customers and contracts on the customer_id. It then filters for customers with an average monthly payment over $10,000 and whose contracts are set to renew within the next three months. The SELECT statement includes all the columns we need from the question. undefined
SQL Question 3: How would you improve the performance of a slow SQL query?
There's several steps you can take to troubleshoot a slow SQL query.
First things first, figure out why the query is slow! You can use and commands in PostgreSQL to identify any performance bottlenecks. After that, you can start changing your query, depending on what the source of the query performance issue is.
Generally, indexes can help speed up queries. Also de-normalizing your tables might help, to remove slow joins.
Lastly, you could always just upgrade your hardware! Time and money wasted improving query performance could just be better spent on mroe powerful database servers!
While this is a very surface-level approach to optimizing SQL query performance, it should do the trick for Data Analyst interviews and Data Science interviews at Equinix. Data Engineers should know a bit more about the and before the interview.
SQL Question 4: Average Monthly Bandwidth Usage
At Equinix, a global data center & colocation provider, one critical business metric could be the average monthly bandwidth usage per customer. In this context, you are asked to write a SQL query that calculates the average bandwidth (in GB) used by each customer for each month.
Given the table content as below,
Example Input:
| stat_id | customer_id | usage_date | used_bandwidth_gb |
|---|---|---|---|
| 1001 | 2552 | 01/03/2022 | 300 |
| 1002 | 2555 | 01/15/2022 | 500 |
| 1003 | 2552 | 01/20/2022 | 200 |
| 1004 | 2552 | 02/05/2022 | 400 |
| 1005 | 2555 | 02/17/2022 | 650 |
| 1006 | 2555 | 02/28/2022 | 500 |
You are to return , and as output.
Example Output:
| mth | customer_id | avg_bandwidth_gb |
|---|---|---|
| 1 | 2552 | 250 |
| 1 | 2555 | 500 |
| 2 | 2552 | 400 |
| 2 | 2555 | 575 |
Answer:
This query groups the data based on the month of usage and customer id (from the date_part function) and computes the average bandwidth used by each customer for each month using the AVG function. Output is then ordered by month and customer id for easy viewing.
To practice a very similar question try this interactive Facebook Active User Retention Question which is similar for requiring computation of monthly metrics per user or this Amazon Average Review Ratings Question which is similar for needing to find monthly averages per user.
SQL Question 5: What is the role of the constraint in SQL?
A is like a secret code that unlocks the door to another table. It's a field in one table that points to the (the master key) in another table. This helps keep the data in your database organized and tidy, because it won't let you add new rows to the table unless they have the correct secret code (a corresponding entry in the table).
It's also like a special bond between the two tables - if you try to delete the data, the will be like "Whoa, hold on! I still need that information!" and prevent the deletion from happening.
SQL Question 6: Analyzing Click-Through Conversion Rates for Equinix
Equinix utilizes various digital campaigns to engage its audience and potential customers. These ad campaigns are designed to lead users to click on a link, which then redirects them to a specific page such as a product page. It's also useful to track conversion rates, specifically how many users that view a product page end up adding that product to their cart.
Suppose that you are provided with two tables, and . The table records the user id, the ad id and the timestamp at which a user clicked an ad. The table, on the other hand, reports when a user added a product to their shopping cart. Each product is associated with an ad from which the user was directed.
Your task is to write a PostgreSQL query that calculates the click-through conversion rate, which is the number of products added to the cart divided by the total number of ad clicks. The query should return the conversion rate per ad.
Here are the sample tables:
Example Input:
| ad_id | user_id | click_time |
|---|---|---|
| 1001 | 123 | 06/08/2022 10:30:22 |
| 1002 | 444 | 06/10/2022 14:25:10 |
| 1003 | 362 | 06/18/2022 16:08:02 |
| 1004 | 192 | 07/26/2022 12:27:56 |
| 1002 | 981 | 07/05/2022 09:17:35 |
Example Input:
| ad_id | user_id | add_time |
|---|---|---|
| 1001 | 123 | 06/08/2022 10:31:25 |
| 1002 | 444 | 06/10/2022 14:26:58 |
| 1003 | 362 | 06/18/2022 16:09:40 |
Answer:
This SQL query first establishes a relationship between the table and the table via a LEFT JOIN. It then counts the number of per and divides it by the total number of to calculate the click-through conversion rate. The is used to ensure that the division results in a decimal number. Finally, the query groups the results by to provide a conversion rate for each individual ad.
To practice a similar problem about calculating rates, solve this SQL interview question from TikTok within DataLemur's interactive SQL code editor:
SQL Question 7: What's the main difference between the 'BETWEEN' and 'IN' operators in SQL?
The operator is used to select rows that fall within a certain range of values, while the operator is used to select rows that match values in a specified list.
For example, suppose you are a data analyst at Equinix and have a table of advertising campaign data. To find campaigns with a spend between 5k, you could use BETWEEN:
To find advertising campaigns that were video and image based (as opposed to text or billboard ads), you could use the operator:
SQL Question 8: Data Center Usage Statistics
Equinix customers have data centers with racks filled with servers. Each server is either active (being used) or inactive (not being used). The racks are then typically grouped by data center locations. A report is needed to provide summary statistics including the maximum, minimum and average number of active servers for each data center location on a monthly basis.
Consider the following table, , as input:
Example Input:
| datacenter_id | location | report_date | server_id | status |
|---|---|---|---|---|
| 101 | Amsterdam | 09/01/2022 00:00:00 | 201 | Active |
| 102 | Amsterdam | 09/01/2022 00:00:00 | 202 | Inactive |
| 101 | Amsterdam | 09/02/2022 00:00:00 | 201 | Inactive |
| 105 | Singapore | 09/03/2022 00:00:00 | 301 | Active |
| 105 | Singapore | 09/03/2022 00:00:00 | 302 | Active |
| 105 | Singapore | 09/03/2022 00:00:00 | 303 | Inactive |
Example Output:
| month | location | min_active | max_active | avg_active |
|---|---|---|---|---|
| 9 | Amsterdam | 0 | 1 | 0.5 |
| 9 | Singapore | 2 | 2 | 2.0 |
Answer:
Here is the PostgreSQL query to get this information:
This query works by first generating a subquery where we count the number of active servers on certain dates at certain locations. We use the clause to only count servers that are marked as active. This subquery is then fed into the main query which groups the subquery results into months and locations, finally getting the maximum, minimum, and average number of active servers each month in each location. undefined
SQL Question 9: Retrieve All Customers from California
As an analyst at Equinix, you often have to retrieve information from our customer database. The customer dataset contains the customer's name, email, and their physical location. In our database, the customer's physical location includes the city and state they are from. It's essential to retrieve information about specific types of customers, but sometimes the request is for customers from a specific location.
Given the table with the structure below, write a SQL query that retrieves all records of customers located in California, USA. Use the PostgreSQL SQL dialect.
Example Input:
| customer_id | customer_name | location | |
|---|---|---|---|
| 0001 | John Doe | johndoe@example.com | Los Angeles, California |
| 0002 | Amelia Earhart | amelia@example.com | Atchison, Kansas |
| 0003 | Neil Armstrong | neil@example.com | Cincinnati, Ohio |
| 0004 | George Washington | george@example.com | Mount Vernon, Virginia |
| 0005 | Jane Smith | jane@example.com | San Francisco, California |
Answer:
This query uses the LIKE keyword in PostgreSQL, along with the wildcard character '%' to filter for those records in the table where the location field ends with the word "California". It will return all columns () for these records. undefined
SQL Question 10: Can you describe the difference between a unique and a non-unique index?
Some similarities between unique and non-unique indexes include:
- Both indexes improve the performance of SQL queries by providing a faster way to lookup the desired data.
- Both indexes use an additional data which requires more storage space which impacts write performance.
- Both indexes can be created on one or more columns of a table
Some differences between unique and non-unique indexes include:
- A unique index enforces the uniqueness of the indexed columns, meaning that no duplicate values are allowed in the indexed columns. A non-unique index allows duplicate values in the indexed columns.
- A unique index can be used to enforce the primary key of a table, but a non-unique index cannot.
- A unique index can have a maximum of one NULL value in the indexed columns, but a non-unique index can have multiple NULLs
SQL Question 11: Calculate Power Usage Efficiency (PUE) and total energy cost for data centers
The power usage efficiency (PUE) is a major metric in data center energy efficiency and is calculated as the ratio of total power used by a data center to the power consumed by the IT equipment. The power consumed by the IT equipment is calculated using the SQRT() function on the sum of individual equipment power consumption, and the total power used by data center includes the power consumed by IT equipment, cooling, and other infrastructure. The total energy cost is calculated as the product of total power used and cost per kilowatt hour. The energy costs are rounded to the nearest dollar using the ROUND() function. Create a SQL query that calculates PUE and total energy cost for each data center.
Example Input:
| id | location | power_used | cooling_power | equipment_power | cost_per_kwh |
|---|---|---|---|---|---|
| 1 | London | 2500 | 1000 | 800 | 0.12 |
| 2 | New York | 3200 | 1200 | 1000 | 0.15 |
| 3 | Singapore | 2800 | 1100 | 900 | 0.14 |
Example Input:
| id | data_center_id | power_consumption |
|---|---|---|
| 1 | 1 | 50 |
| 2 | 1 | 60 |
| 3 | 2 | 120 |
| 4 | 2 | 150 |
| 7 | 3 | 100 |
| 8 | 3 | 110 |
Example Output:
| location | PUE | total_energy_cost |
|---|---|---|
| London | 1.8 | $300 |
| New York | 2.0 | $480 |
| Singapore | 2.0 | $392 |
Answer:
This query computes the PUE and total energy costs for each data center. It uses JOIN to combine the data center and equipment tables, GROUP BY to calculate metrics for each data center, ROUND to round the energy costs to the nearest dollar, and SQRT to find the square root of the sum of power consumption for equipment.
To practice a very similar question try this interactive Amazon Server Utilization Time Question which is similar for calculations of total resource usage or this Microsoft Supercloud Customer Question which is similar for handling various product categories.
Preparing For The Equinix SQL Interview
The best way to prepare for a Equinix SQL interview is to practice, practice, practice.
In addition to solving the earlier Equinix SQL interview questions, you should also solve the 200+ SQL questions on DataLemur which come from companies like FAANG and tech startups.
Each DataLemur SQL question has hints to guide you, fully explained answers along with a discussion board to see how others solved it and best of all, there's an online SQL code editor so you can instantly run your query and have it executed.
To prep for the Equinix SQL interview it is also a great idea to solve SQL problems from other datacenter companies like:
In case your SQL query skills are weak, don't worry about diving straight into solving questions – improve your SQL foundations with this SQL tutorial for Data Analytics.
This tutorial covers things like sorting data with ORDER BY and aggregate window functions – both of these pop up often in Equinix SQL assessments.
Equinix Data Science Interview Tips
What Do Equinix Data Science Interviews Cover?
For the Equinix Data Science Interview, beyond writing SQL queries, the other types of questions to prepare for are:
- Probability & Statistics Questions
- Python or R Programming Questions
- Business Sense and Product-Sense Questions
- Machine Learning Questions
- Behavioral Based Interview Questions
How To Prepare for Equinix Data Science Interviews?
The best way to prepare for Equinix Data Science interviews is by reading Ace the Data Science Interview. The book's got:
- 201 Interview Questions from FAANG tech companies
- A Refresher covering Stats, ML, & Data Case Studies
- Great Reviews (900+ reviews, 4.5-star rating)