# Average Latency by Status

> Each status code has its own latency story.

Canonical URL: <https://datadriven.io/problems/average_latency_by_status>

Domain: SQL · Difficulty: easy · Seniority: L3

## Problem

During a latency spike investigation, the on-call engineer needs to know whether slow responses correlate with specific HTTP status codes. Show the average latency for each status code across all API calls.

## Worked solution and explanation

### Why this problem exists in real interviews

This challenge targets grouped aggregation against `api_calls`. Getting the grouping wrong on `endpoint`, `method`, `status` produces silently incorrect counts, which is exactly the trap interviewers set.

---

### Break down the requirements

#### Step 1: Group by `method`

`GROUP BY` at the correct grain produces one row per group.

#### Step 2: Compute `AVG(status)`

The AVG function computes the avg per group.

#### Step 3: Order by the metric

Sort by `avg_status` desc for readability.

---

### The solution

**Group-aggregate for average latency status**

```sql
SELECT
    method,
    AVG(status) AS avg_status
FROM api_calls
GROUP BY method
ORDER BY avg_status DESC
```

> **Cost Analysis**
>
> The main table has 100M rows (26 GB). Partitioned on `call_time`, so queries filtering on that column skip most partitions. The GROUP BY reduces the row count early, keeping downstream operations cheap.

> **Interviewers Watch For**
>
> Strong candidates state the correct `GROUP BY` grain before writing any SQL, showing they think about the output shape first.

> **Common Pitfall**
>
> Selecting a non-aggregated column without including it in `GROUP BY` is the most common error. Some engines reject it; others silently return arbitrary values.

---

## Common follow-up questions

- The `err_msg` column in `api_calls` has roughly 94% NULLs. How does your query handle those rows, and would the result change if NULLs were replaced with zeros? _(Tests whether the candidate understands how NULLs propagate through aggregation functions and whether their WHERE/JOIN conditions implicitly filter them out.)_
- Your GROUP BY aggregates `call_id` from `api_calls`. If two groups have the same aggregate value, how is the output ordered, and is that deterministic? _(Tests awareness that ORDER BY on a non-unique value produces non-deterministic row order without a tiebreaker.)_
- `call_id` in `api_calls` has ~100M distinct values. What index strategy keeps your query from doing a full table scan? _(Tests whether the candidate can design indexes for high-cardinality columns and understands selectivity.)_
- Could you express this same logic as a single query without CTEs or subqueries? What readability trade-off does that introduce? _(Tests whether the candidate can flatten nested logic and understands when decomposition aids maintainability.)_

## Related

- [All practice problems](https://datadriven.io/problems)
- [Mock interview mode](https://datadriven.io/interview/average_latency_by_status)
- [SQL Interview Questions](https://datadriven.io/sql-interview-questions)
- [Data Engineering Interview Prep Guide](https://datadriven.io/data-engineer-interview-prep)
- [Daily Challenge](https://datadriven.io/daily)

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