# 8 Luminar Technologies SQL Interview Questions (Updated 2024)

Updated on

June 23, 2024

Data Analysts & Data Scientists at Luminar write ad-hoc SQL queries daily as part of their job. They use SQL for managing and querying LiDAR sensor data stored in relational databases and analyzing traffic and user behavior data for autonomous vehicle development. That's the reason behind why Luminar Technologies typically asks folks interviewing for data jobs SQL coding interview questions.

Thus, to help you prep for the Luminar Technologies SQL interview, we've curated 8 Luminar Technologies SQL interview questions can you solve them?

## 8 Luminar Technologies SQL Interview Questions

### SQL Question 1: Analyzing Sensor Usage by Lidar Devices

Luminar Technologies heavily utilizes lidar (light detection and ranging) technology. Lidar devices produce large volumes of sensor data. Suppose we're given tables of lidar devices and their daily sensor usage.

##### Example Input:
device_idinstall_datevehicle_id
4202/01/2021108
5305/01/2021192
6407/18/2020158
##### Example Input:
usage_iddevice_idusage_datedistance_scanned_km
1784208/01/2022252
1994208/02/2022298
2036408/01/2022158
2076408/02/2022167
2145308/01/2022213

Your task is to write a SQL query to calculate the daily average distance scanned (in km) by all devices, sorted by date. Also, calculate a running total of the daily average scanned distance.

Use PostgreSQL and its window functions to answer this question.

In the answer, we first create a CTE () where we calculate the average distance scanned per day () and a running total of this daily average (). This is achieved by using window functions where rows are partitioned by . We then select from this CTE and order by .

To solve a related window function SQL problem on DataLemur's free interactive SQL code editor, try this Google SQL Interview Question:

### SQL Question 2: Top Three Salaries

Suppose you had a table of Luminar employee salary data. Write a SQL query to find the top three highest paid employees in each department.

#### Luminar Technologies Example Input:

employee_idnamesalarydepartment_id
1Emma Thompson38001
2Daniel Rodriguez22301
3Olivia Smith20001
4Noah Johnson68002
5Sophia Martinez17501
8William Davis68002
10James Anderson40001

#### Example Input:

department_iddepartment_name
1Data Analytics
2Data Science

#### Example Output:

department_namenamesalary
Data AnalyticsJames Anderson4000
Data AnalyticsEmma Thompson3800
Data AnalyticsDaniel Rodriguez2230
Data ScienceNoah Johnson6800
Data ScienceWilliam Davis6800

Code your solution to this question interactively on DataLemur:

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 detailed solution here: Top 3 Department Salaries.

### SQL Question 3: Can you explain the purpose of UNION?

is used to combine the results of multiple statements into a single result set.

Suppose you were doing an HR Analytics project for Luminar Technologies, and needed to analyze both Luminar Technologies's contractors and employees. You could use in the following way:

This statement would return a combined result set of Luminar Technologies contractors and employees who were hired after the start of the year 2023.

### SQL Question 4: Filter Customers Data Based On Purchase History and Location

For Luminar, a company that specializes in providing autonomous vehicle software, let's consider you have a customer database. This database logs all the purchases of software license upgrades made by customers. As a data analyst, you are asked to filter out the customers from the USA whose most recent purchase was a full self-driving (FSD) upgrade, and who have made more than 5 purchases in total.

You are given two tables: and .

##### Example Input:
customer_idfirst_namelast_namecountry
101JaneDoeUSA
102JohnDoeUSA
104BobJohnsonUSA
##### Example Input:
purchase_idcustomer_idproductpurchase_date
201101Lidar2021-01-01
202102FSD2021-02-01
203101FSD2021-03-01
204102FSD2021-04-01
205103Lidar2021-02-01
206104FSD2021-03-01
207101AP2021-04-01
208102Fsd2021-05-01
209101Fsd2021-05-01
210104FSD2021-06-01

In the above query, the JOIN operation is used to combine rows from and tables based on their customer_id. The WHERE clause filters out customers who are from 'USA' and bought the 'FSD' product as their most recent purchase (as determined by the subquery for max purchase_date). The HAVING clause filters the results of the GROUP BY operation to leave only those customers who have made more than 5 purchases. The result shows the customer id, first name, last name, and the total number of purchases for every customer who meets these criteria.

### SQL Question 5: Can you describe the concept of a database index and the various types of indexes?

A database index is a way to optimize the performance of a database by reducing the amount of data that needs to be searched to retrieve a record.

There are several types of indexes:

• unique & non-inuqie indexes
• primary & composite indexes
• clustered & non-clustered indexes

### SQL Question 6: Average Lidar Points Detected Per Test Run

Luminar Technologies specializes in lidar technology. Lidar sensors are used in self-driving cars to create a 3D map of their surroundings. This map is generated by sending out light signals and measuring how long it takes for them to return, with each returned light signal representing a "point" in the 3D map.

In this scenario, you are tasked to find the average number of lidar points detected per test run. You have one table , with each row representing a single test run and includes the columns (unique identifier for each test run), (unique identifier for each self-driving car), (date of the test run), and (number of lidar points detected during the test run).

##### Example Input:
test_idcar_idrun_datepoints_detected
10015006/08/202250000
10027006/10/202269850
10035006/18/202250010
10047007/26/202269800
10055007/05/202250030
##### Example Output:
car_idavg_points
5050013.33
7069825.00

This query calculates the average number of lidar points detected for each self-driving car. It utilizes the AVG function of SQL to get the average of the 'points_detected' column after grouping the rows by 'car_id'. Notice that the result is rounded off to 2 decimals to make it easier to read.

To practice a very similar question try this interactive Google Odd and Even Measurements Question.

### SQL Question 7: Can you explain the purpose of the constraint and give an example of when you might use it?

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.

For example, say you had Luminar Technologies customer data. You could use a CHECK constraint to ensure that the email column contains only properly formatted email addresses, or that the age column contains only positive integer. Here's an example of that:

### SQL Question 8: Filtering Customer Records

Luminar Technologies would like to analyze their customer records to find those customers who have mentioned "LiDAR" in their customer notes. You have been given the task to find all customers where their notes contain the word "LiDAR". Write a SQL query to filter out these customers.

##### Example Input:
customer_idfirst_namelast_nameemailnotes
761JohnDoejohndoe@example.comInterested in LiDAR technology for his vehicle
965SaraSmithsara@example.comLooking for radar solution, not LiDAR
314PeterParkerpeter@example.comLiDAR technology was recommended by a friend
589JaneDoejane@example.comPrefers camera-based solution over LiDAR
##### Example Output:
customer_idfirst_namelast_nameemailnotes
761JohnDoejohndoe@example.comInterested in LiDAR technology for his vehicle
314PeterParkerpeter@example.comLiDAR technology was recommended by a friend

This SQL query uses the operator along with (wildcard character) to filter out those customers whose notes contain the word "LiDAR". It searches for "LiDAR" within the column and returns all columns () for the matching records.

### Preparing For The Luminar Technologies SQL Interview

Assuming that you've already got basic SQL skills, the next best tip we have to prepare for the Luminar Technologies SQL interview is to solve as many practice SQL interview questions as you can! Beyond just solving the earlier Luminar Technologies SQL interview questions, you should also solve the 200+ tricky sql questions on DataLemur which come from companies like Amazon, Microsoft, Meta, and smaller tech companies.

Each 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 SQL query and have it graded.

To prep for the Luminar Technologies SQL interview you can also be a great idea to solve SQL problems from other tech companies like:

But if your SQL skills are weak, don't worry about going right into solving questions – improve your SQL foundations with this DataLemur SQL tutorial.

This tutorial covers things like handling timestamps and handling NULLs in SQL – both of which show up frequently in Luminar Technologies interviews.

### Luminar Technologies Data Science Interview Tips

#### What Do Luminar Technologies Data Science Interviews Cover?

In addition to SQL interview questions, the other question categories to prepare for the Luminar Technologies Data Science Interview include:

#### How To Prepare for Luminar Technologies Data Science Interviews?

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