Window function: running total over category
Last updated: December 5, 2025
Quick Overview
Use window functions to compute running total partitioned by date.
Shopify
December 5, 202510
7
3,897 solved
Use window functions to compute running total partitioned by date.
Data manipulation questions at Shopify test your ability to work with real-world datasets. This Technical Screen question evaluates your SQL proficiency, understanding of data modeling, and ability to derive insights from raw data.
What the Interviewer Expects
- Use advanced SQL features: window functions, CTEs, subqueries
- Write efficient queries that avoid common performance pitfalls
- Handle complex data transformations with multiple joins and aggregations
- Discuss indexing strategy and query optimization
- Address data quality issues: duplicates, missing values, outliers
Key Topics to Cover
How to Approach This
- Clarify the schema and expected output format before writing queries.
- Use CTEs (WITH clauses) to break complex queries into readable steps.
- Consider window functions (ROW_NUMBER, RANK, LAG, LEAD) for ranking and sequential analysis.
- Watch for NULLs, duplicates, and edge cases in JOINs and GROUP BY.
- For pandas, prefer vectorized operations over row-by-row iteration.
Possible Follow-up Questions
- How would you handle this if the data was spread across multiple databases?
- What indexes would you create to support this query?
- Can you rewrite this without using subqueries?
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Practice SQL ProblemsSample Answer
Problem Understanding
In this problem, we are tasked with calculating a running total of sales partitioned by date for different product categories. The dataset consists of sales records with at least the following columns...
Approach
To solve this problem, we will follow these steps:
- Identify the main dataset: Ensure we have the correct sales data with relevant columns.
- Use a Common Table Expression (CTE): First, we ...
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