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SQL Aggregation Practice Problems

Aggregation collapses many rows into per-group summaries with GROUP BY and functions like COUNT, SUM, and AVG, filtered after grouping with HAVING. Interviewers reach for it constantly - "revenue per category", "departments with more than N employees" - because it exposes whether you understand the difference between filtering rows (WHERE) and filtering groups (HAVING). Expect it combined with joins in almost every medium-difficulty screen.

21 problems across 4 schemas · 4 free for registered users. Each runs your query in an isolated SQLite sandbox with instant, graded feedback.

Easy4

Count Employees

EasyAggregation

Departments With High Average Salary

EasyJoinsAggregation

Headcount Per Department

EasyJoinsAggregation

Products Per Category

EasyAggregation

Medium9

Average Salary by DepartmentPremium

MediumJoinsAggregation

Spend Per CustomerPremium

MediumJoinsAggregation

Categories By RevenuePremium

MediumJoinsAggregation

Revenue By Customer CityPremium

MediumJoinsAggregation

Departments With More Than One EmployeePremium

MediumJoinsAggregation

Products With High Unit VolumePremium

MediumJoinsAggregation

Purchaser Counts By Country Via CTEPremium

MediumCTEsJoinsAggregation

Bucket Employees Into Pay BandsPremium

MediumAggregation

Purchaser Counts By Country Via CTEPremium

MediumCTEsJoinsAggregation

Hard8

Rank Customers by SpendPremium

HardWindow FunctionsCTEsAggregation

Employees Paid Above Their Department AveragePremium

HardSubqueriesAggregation

Orders Larger Than The Customer's AveragePremium

HardSubqueriesAggregation

Products Priced Above Their Category AveragePremium

HardSubqueriesAggregation

Rank Products By Total RevenuePremium

HardWindow FunctionsAggregationJoins

Above-Average Earners Via A CTEPremium

HardCTEsJoinsAggregation

Top Revenue Category Via Chained CTEsPremium

HardCTEsJoinsAggregation

Total Quantity Sold Per MonthPremium

HardDates & TimeAggregation

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SQL Aggregation Practice Problems

Aggregation collapses many rows into per-group summaries with GROUP BY and functions like COUNT, SUM, and AVG, filtered after grouping with HAVING. Interviewers reach for it constantly - "revenue per category", "departments with more than N employees" - because it exposes whether you understand the difference between filtering rows (WHERE) and filtering groups (HAVING). Expect it combined with joins in almost every medium-difficulty screen.

21 problems across 4 schemas · 4 free for registered users. Each runs your query in an isolated SQLite sandbox with instant, graded feedback.