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Bucket deliveries into quartiles · SQL scenario · D8LooP

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Bucket deliveries into quartiles

Before setting a target, the team wants to see the deliveries split into four equal groups from fastest to slowest, and to know what range of times each group covers. That framing — "the slowest quarter of deliveries" — is how the conversation is actually held. Return one row per quartile with the number of deliveries in it and its fastest and slowest time. Order by quartile.

Result columns · in this order

`quartile`	1 for the fastest quarter through 4 for the slowest.
`deliveries`	How many deliveries landed in this bucket.
`fastest`	Shortest delivery time in the bucket, in minutes.
`slowest`	Longest delivery time in the bucket, in minutes.

How to approach it

Compute the bucket in a CTE, then group by it in the outer query.

Sample input

deliveriesOne row per completed delivery. Twenty-six rows across three cities and five days. Most deliveries land in twenty to forty-five minutes; a few take far longer.

delivery_id	city	courier	minutes	delivered_on
1	Bengaluru	Asha	18	2026-03-01
2	Bengaluru	Asha	22	2026-03-01
3	Bengaluru	Rohit	26	2026-03-02
4	Bengaluru	Asha	28	2026-03-02
5	Bengaluru	Rohit	30	2026-03-03
6	Bengaluru	Meera	30	2026-03-03
7	Bengaluru	Meera	34	2026-03-04
8	Bengaluru	Rohit	41	2026-03-04
9	Bengaluru	Asha	150	2026-03-05
10	Pune	Kabir	20	2026-03-01
11	Pune	Kabir	24	2026-03-01
12	Pune	Nita	26	2026-03-02
13	Pune	Nita	30	2026-03-02
14	Pune	Kabir	33	2026-03-03
15	Pune	Nita	36	2026-03-03
16	Pune	Kabir	45	2026-03-04
17	Pune	Nita	62	2026-03-05
18	Pune	Kabir	240	2026-03-05
19	Chennai	Vikram	19	2026-03-01
20	Chennai	Priya	23	2026-03-01
21	Chennai	Vikram	27	2026-03-02
22	Chennai	Priya	30	2026-03-03
23	Chennai	Vikram	38	2026-03-03
24	Chennai	Priya	52	2026-03-04
25	Chennai	Vikram	71	2026-03-04
26	Chennai	Priya	96	2026-03-05

26 rows — scroll inside the table to see them all.

Expected output

The exact result your query should return for this input.

quartile	deliveries	fastest	slowest
1	7	18	26
2	7	26	30
3	6	33	45
4	6	52	240

4 rows — all rows shown.

Constraints

1Use NTILE(4) over all deliveries ordered by minutes, ascending — quartile 1 is the fastest quarter.
2NTILE is a window function, so it is computed after GROUP BY. You cannot group by it in the same SELECT that produces it; it has to come from a subquery or CTE.
3Do not filter anything out. The two outliers belong in quartile 4 — that is the point of the bucket.
4Report fastest and slowest per bucket so the reader can see the ranges are not equal in width.
5Four rows, ordered by quartile.

Worked example

Twenty-six deliveries into four buckets does not divide evenly. NTILE gives the earlier buckets the extra rows: 7, 7, 6, 6. Now look at what that costs. Deliveries 3 and 12 both took exactly 26 minutes, and they sit at ranks 7 and 8 — either side of the boundary. One lands in quartile 1 and the other in quartile 2, on nothing but their row number. NTILE balances by row count, never by value. If equal values must stay together, NTILE is the wrong tool and a CASE over explicit thresholds is the right one.

What this tests

That you know NTILE splits by row count rather than by value, and that you can see where a window function is allowed to appear in a query.

SQL

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