SQL Window Functions Interview Questions

Master the world of data! Dive into SQL & Python interview questions and get ready for your SQL interview!

affirm afterpay airbnb amazon apple doordash dropbox ebay facebook google linkedin lyft microsoft netflix robinhood roblox snap spotify tiktok twitter uber visa walmart

Chapter 4: Window Functions

ID	Title	Level	FTPR	Lecture
58	Percentage of revenue per movie	hard	8%	4.1
59	Percentage of revenue per movie by category	medium	6%	4.1
60	Movie rentals and average rentals in the same category	hard	9%	4.1
61	Customer spend vs average spend in the same store	hard	11%	4.1
62	Shortest film by category	medium	8%	4.2
63	Top 5 customers by store	hard	8%	4.2
64	Top 2 films by category	hard	14%	4.2
65	Movie revenue percentiles	easy	16%	4.3
66	Movie percentiles by revenue by category	medium	18%	4.3
67	Quartile by number of rentals	easy	24%	4.3
68	Spend difference between first and second rentals	hard	12%	4.4
69	Number of happy customers	hard	7%	4.4
70	Cumulative spend	easy	13%	4.1
71	Cumulative rentals	easy	21%	4.1
72	Days when they became happy customers	medium	10%	4.2
73	Number of days to become a happy customer	hard	11%	4.2
74	The most productive actors by category	hard	7%	4.2
75	Top customer by movie category	medium	26%	4.2
76	Districts with the most and least customers	easy	12%	4.2
77	Movie revenue percentiles by category	easy	18%	4.3
78	Quartiles buckets by number of rentals	medium	25%	4.3
79	Spend difference between the last and the second last rentals	hard	16%	4.4
80	DoD revenue growth for each store	hard	19%	4.4
83	Top search_query in US and UK on new year's day facebook	medium	6%	4.2
88	Top song report spotify	medium	22%	4.2
90	Top artist report spotify	medium	21%	4.2
103	Median and average session duration by day of the week google	medium	20%	4.3
105	Number of days gap between last two actions google	hard	8%	4.2
108	Free premium membership amazon	hard	16%	4.1
109	Top 3 most popular product categories amazon	easy	11%	4.2
110	Most popular product by category amazon	medium	12%	4.2
113	Daily cumulative spend amazon	easy	11%	4.1
114	Dod revenue change rate amazon	easy	15%	4.4
115	Rolling average revenue amazon	hard	28%	4.1
116	Top answers day by device amazon	easy	14%	4.2
117	Rolling 7 days total answers amazon	easy	35%	4.1
119	Top 2 countries by bookings airbnb	hard	10%	4.2
120	First ever booking airbnb	hard	10%	4.2
121	Week over week change of first ever bookings airbnb	hard	14%	4.4
122	Top country by wow growth airbnb	hard	13%	4.2
123	Top listing in the United States, United Kingdom and Canada airbnb	medium	10%	4.2
127	Average rating after 10th trip uber	hard	11%	4.2
135	Unlucky employees robinhood	easy	16%	4.2
137	Extremely late first orders doordash	medium	9%	4.2
139	Poor first delivery experience doordash	medium	17%	4.2
141	Cumulative sales of restaurant 100011 doordash	hard	15%	4.1
142	First order date afterpay	easy	40%	4.2
144	Third order afterpay	medium	9%	4.2
145	Returning customers after first buy afterpay	hard	16%	4.2
147	2 days streak customers google	hard	13%	4.4
148	Most popular video category google	medium	13%	4.2
157	Number of trips before a driver got banned lyft	medium	10%	4.2
158	First trip completion rate lyft	medium	22%	4.2
165	Session stitching walmart	hard	17%	4.2
166	Top 10 customers based on spend growth walmart	medium	11%	4.2
180	Members moved from Microsoft to Google directly. linkedin	hard	21%	4.4
182	Top 5 content by number of watchers netflix	medium	9%	4.1
188	Top 1 popular question by department google	hard	14%	4.2
189	Campaign activation date twitter	medium	19%	4.1
195	MoM user growth snap	hard	14%	4.4
199	Students improvement snap	hard	67%	4.4
201	Top 3 students for each subject snap	hard	67%	4.2
203	Top product by country by month apple	hard	100%	4.2
208	Top 3 urls by testing groups apple	hard	10%	4.2
211	Top issuer by category visa	medium	30%	4.2
212	Highest spender's issuers visa	hard	0%	4.2
229	Time Between Repeat Purchases microsoft	hard	-	4.4
230	Customer Purchase Trend Analysis microsoft	easy	-	4.4

Disclaimer: SQLPad collects questions and their associated data from the internet, but we are not associated with any of the companies or organizations that may be mentioned in these questions. While we strive to provide accurate and up-to-date information, we cannot guarantee the accuracy or completeness of the information provided. Users should exercise their own discretion when using the platform and should not rely solely on the information provided. By using SQLPad, you acknowledge and agree that we are not responsible for any errors or inaccuracies in the information, and that you assume all risks associated with using the platform. You also agree to our terms and conditions.