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Given a multi-step product feature, write SQL to see how well this feature is doing (loading times, step completion %). Then use Python to constantly update average step time as new values stream in, given that there are too many to store in memory.
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Data Engineer

Interviewed at Meta

3.5★
Apr 30, 2018

Given a multi-step product feature, write SQL to see how well this feature is doing (loading times, step completion %). Then use Python to constantly update average step time as new values stream in, given that there are too many to store in memory.

SQL: 1. Percentage increase in revenue compared to promoted and non-promoted products. 2. Products classes that has the highest transactions 3. Count of Customers who bought 2 items type (A,B) 4. Don't remember Python: 1. Average length of letters to words. 2. Parse an ip address (This is a favourite FB question) 3. [[A],[A,B],[A,C],[B,D],[C,A]] -- Find the alphabet with highest neighbors? -- (Wasnt able to solve because of time limit but the interviewer was like I get what I want to convey.. I gave her an algo of what I would I have done)
avatar

Data Engineer

Interviewed at Meta

3.5★
Sep 21, 2018

SQL: 1. Percentage increase in revenue compared to promoted and non-promoted products. 2. Products classes that has the highest transactions 3. Count of Customers who bought 2 items type (A,B) 4. Don't remember Python: 1. Average length of letters to words. 2. Parse an ip address (This is a favourite FB question) 3. [[A],[A,B],[A,C],[B,D],[C,A]] -- Find the alphabet with highest neighbors? -- (Wasnt able to solve because of time limit but the interviewer was like I get what I want to convey.. I gave her an algo of what I would I have done)

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