11 Trip.com SQL Interview Questions (Updated 2024)

Updated on

February 29, 2024

At Trip.com, SQL is used often for analyzing user booking trends and for analyzing the user acquisition funnel. They also put out interesting travel market analysis for content-marketing purposes. Because of this, Trip.com often tests SQL problems during interviews for Data Analyst, Data Science, and BI jobs.

To help you study for the Trip.com SQL interview, we've curated 11 Trip.com SQL interview questions – how many can you solve?

Trip.com SQL Interview Questions

11 Trip.com SQL Interview Questions

SQL Question 1: Identify High Booking Users for Trip.com

For Trip.com, which is a global online travel agency company, we need to identify power users with high booking and purchasing frequency. Power users can be defined as users who have booked more than 10 different hotels or flights in the past six months. We need to rank these customers based on their total number of transactions.

To conduct this analysis, let's assume we have access to the following tables, the and tables.

1701/01/2020John Doe
3602/28/2020Jane Smith
4503/15/2020James Brown



Here is an example PostgreSQL for this task:

This query first creates a temporary table that holds users who have booked more than 10 different hotels or flights within the past six months. Then, it joins the , , and tables together to generate user transaction statistics and finally orders users by their total number of transactions in descending order.

To practice a super-customer analysis question on DataLemur's free online SQL coding environment, try this Microsoft Azure Cloud SQL Interview Question: Microsoft SQL Interview Question: Super Cloud Customer

SQL Question 2: Calculate Monthly Average Reviews

Trip.com, the international online travel agency, hosts millions of reviews on its platform. As an analyst, you are tasked with writing a SQL query to calculate the monthly average stars for each product.

The dataset at your disposal, named , contains the following columns:

  • : a unique identifier for each review
  • : a unique identifier for each user
  • : the date the review was submitted in the format 'MM/DD/YYYY HH:MI:SS'
  • : a unique identifier for each product
  • : the star rating given by the user to the product (ranging from 1 to 5)
Example Input:
617112306/15/2022 00:00:00500014
780226506/20/2022 00:00:00698524
529336206/25/2022 00:00:00500013
635219207/15/2022 00:00:00698523
451798107/20/2022 00:00:00698522

Please also take note of mitigating any potential edge cases, such as months with no reviews.

Example Output:


Here, we calculate the monthly average of stars for all the products by using the and functions in SQL. The function is used to retrieve month from the column and the function is used to calculate the average of stars for that month. is used to aggregate data based on month and product_id.

p.s. Window functions show up super often during SQL interviews, so practice the 27+ window function questions on DataLemur

DataLemur SQL Questions

SQL Question 3: What's the SQL command do, and can you give an example?

Similar to the and / operators, the PostgreSQL INTERSECT operator combines result sets of two or more statements into a single result set. However, only returns the rows that are in BOTH select statements.

For a concrete example, say you were on the Sales Analytics team at Trip.com, and had data on sales leads exported from both HubSpot and Salesforce CRMs in two different tables. To write a query to analyze leads created after 2023 started, that show up in both CRMs, you would use the command:

Trip.com SQL Interview Questions

SQL Question 4: Average Hotel Rating on Trip.com

Can you write a PostgreSQL Query to find the average rating given by users to each hotel on Trip.com platform?

Example Input:
Example Output:


What we're doing here is using the PostgreSQL AVG function to calculate the average rating for each hotel_id from the table. We group by hotel_id so that we get a separate average for each hotel. The AVG function automatically returns a float value for the average.

To practice a very similar question try this interactive Amazon Average Review Ratings Question which is similar for querying average ratings or this LinkedIn Data Science Skills Question which is similar for extracting relevant data from a platform.

SQL Question 5: What is the purpose of the SQL constraint ?


The UNIQUE constraint makes sure that all values in a column are distinct. It is often paired with other constraints, like NOT NULL, to ensure that the data follows certain rules.

For example, say you were an analyst on the marketing team at Trip.com, and had access to a database on marketing campaigns:

In this example, the UNIQUE constraint is applied to the "campaign_name" field to ensure that each campaign has a unique name. This helps to ensure the integrity of the data in the table and prevents errors that could occur if two campaigns had the same name.

SQL Question 6: Calculate Click-Through Conversion Rates

For a company like Trip.com, they are interested in knowing the clickthrough conversion rates of customers looking at hotel deals to add the hotel to a wishlist. For this exercise, we can use two Tables. The 'views' table tracks every time a user views a hotel. The 'wishlist' table tracks every time a user adds a hotel to their wishlist. Both tables have a user ID to identify unique customers and a hotel ID to identify unique hotels.

Write a SQL query to calculate the clickthrough conversion rate for each hotel, defined as the number of times a hotel is added to a wishlist divided by the number of times that hotel has been viewed.

Example Input:
150012006/08/2022 00:00:005001
200236506/10/2022 00:00:005001
350356206/18/2022 00:00:005001
450229207/26/2022 00:00:006985
590118107/05/2022 00:00:006985
Example Input:
250029006/08/2022 00:00:005001
274539206/13/2022 00:00:005001
270856206/18/2022 00:00:006985
365278007/26/2022 00:00:006985
494249807/06/2022 00:00:005001


The SQL query provided performs a LEFT JOIN on the and tables with the user_id and the hotel_id. It then calculates the conversion rate as the total count of each hotel_id in the wishlist divided by the total count of each hotel_id in the views. The CAST function is used to ensure that the division results in a float for accurate conversion rates.

To practice a similar problem on DataLemur's free interactive SQL code editor, solve this Meta SQL interview question: Facebook Click-through-rate SQL Question

SQL Question 7: What is denormalization?

Denormalization is a technique used to improve the read performance of a database, typically at the expense of some write performance.

By adding redundant copies of data or grouping data together in a way that does not follow normalization rules, denormalization improves the performance and scalability of a database by eliminating costly join operations, which is important for OLAP use cases that are read-heavy and have minimal updates/inserts.

SQL Question 8: Average Booking Price by Hotel Category and Month

Given the following tables named and , write a SQL query that calculates the average booking price for each hotel category for each month in the year 2022.

Sample Input:
Sample Input:
Sample Output:


This query first extracts the month from the booking date as well as the associated hotel's category. It then calculates the average booking price for these groups. The clause is used to filter the booking dates to the year 2022. Finally, the results are ordered by the month and then by the average booking price.

SQL Question 9: Obtain Average Stars of Unique Hotels Per Month

As a data analyst at Trip.com, you are tasked to analyze the hotel reviews. You have been given two PostgreSQL tables and . The table with the columns: review_id, user_id, submit_date, hotel_id, and stars. The table has columns: hotel_id, hotel_name, city, start_date, and end_date.

Write a SQL query to determine the average star rating assigned by users to each hotel per month. Only include hotels that have at least one review. Ignore reviews that were submitted after the hotel ended its operation and before the hotel started its operation. Submit your solution in PostgreSQL.

Example Input:
Example Input:
50001Hotel PlazaNew York06/01/202206/30/2023
69852Hotel ZenithLondon07/01/202207/30/2023


The SQL query first join the table with table on . Date truncation 'month' is used to group reviews by the month they were submitted. It then calculates the average star rating for each hotel per month, where it only includes the reviews that were submitted during the hotel's operation period. Ignore reviews submitted after the hotel ended its operation and before it started its operation. The result is then sorted by month () and . Note that, the syntax '1' is used in the clause which refers to the first selected column .

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

SQL Question 10: How can you identify duplicates in a table? Do have any other approaches?

One way to find duplicatesis to use a clause and then use to find groups

You could also use the operator:

SQL Question 11: Calculating Average Rating and Rating Variance for Each Hotel

Given a table of hotel reviews, calculate the average rating for each hotel. Furthermore, calculate the variance of these ratings for each hotel. It is important to calculate the variance as it is a measure of how spread out the numbers are.

The 'reviews' table has the following schema: 'review_id' (int), 'user_id' (int), 'submit_date' (datetime), 'hotel_id' (int), 'rating' (int). The 'rating' field ranges from 1-5 stars.

Example Input:
110106/08/2022 00:00:00100015
210206/10/2022 00:00:00100014
310306/11/2022 00:00:00100013
410406/10/2022 00:00:00100022
510506/14/2022 00:00:00100021


This query first groups the data by 'hotel_id' and then calculates the average 'stars' for each hotel. It also calculates the variance, which is the square root of the average of the squared deviations from the mean (where mean is ). The use of calculates the squared deviation from the mean for each review's 'stars', and completes the variance calculation by dividing it by the count and then taking the square root. Both the average and variance are rounded to 2 decimal places for clarity.

This should provide a clear indication of how the hotel ratings vary and their average.

To practice a very similar question try this interactive Amazon Average Review Ratings Question which is similar for calculating average ratings or this Facebook Histogram of Users and Purchases Question which is similar for grouping and computing statistics on user activity.

How To Prepare for the Trip.com SQL Interview

The best way to prepare for a Trip.com SQL interview is to practice, practice, practice. In addition to solving the above Trip.com SQL interview questions, you should also solve the 200+ SQL Interview Questions on DataLemur which come from companies like Facebook, Google and unicorn tech startups. DataLemur Questions

Each interview 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 interactive coding environment so you can instantly run your SQL query and have it checked.

To prep for the Trip.com SQL interview you can also be wise to solve interview questions from other tech companies like:

In case your SQL query skills are weak, forget about jumping right into solving questions – strengthen your SQL foundations with this free SQL for Data Analytics course.

SQL interview tutorial

This tutorial covers things like LAG window function and manipulating string/text data – both of these come up often in SQL job interviews at Trip.com.

Trip.com Data Science Interview Tips

What Do Trip.com Data Science Interviews Cover?

In addition to SQL interview questions, the other question categories covered in the Trip.com Data Science Interview are:

Trip.com Data Scientist

How To Prepare for Trip.com Data Science Interviews?

The best way to prepare for Trip.com Data Science interviews is by reading Ace the Data Science Interview. The book's got:

  • 201 Interview Questions from Facebook, Google, & Amazon
  • A Refresher on SQL, Product-Sense & ML
  • Great Reviews (900+ 5-star reviews on Amazon)

Acing Data Science Interview