Event contract

Fields the query expects

Field	Type	Why it exists
timestamp_utc	Timestamp	Processing completion time.
provider	Utf8	Webhook provider.
event_type	Utf8	Provider event category.
idempotency_outcome	Utf8	new_event or duplicate.
status	Utf8	success or failed.
latency_ms	Float64	Processing duration.

DataFusion SQL

Copy the query

sql

SELECT
  provider,
  event_type,
  COUNT(*) AS deliveries,
  SUM(CASE WHEN idempotency_outcome = 'duplicate' THEN 1 ELSE 0 END) AS duplicates,
  SUM(CASE WHEN status = 'failed' THEN 1 ELSE 0 END) AS failures,
  100.0 * SUM(CASE WHEN idempotency_outcome = 'duplicate' THEN 1 ELSE 0 END)
    / NULLIF(COUNT(*), 0) AS duplicate_rate_pct,
  approx_percentile_cont(latency_ms, 0.95) AS p95_latency_ms
FROM webhook_deliveries
WHERE timestamp_utc >= now() - INTERVAL '7 days'
GROUP BY provider, event_type
ORDER BY duplicate_rate_pct DESC, failures DESC;

This read-only query is planned and executed against an empty typed table with Apache DataFusion 45.2.0. The deterministic sample output is synthetic and reviewed separately; validate field types, thresholds, and business definitions against your own data. Read the testing methodology.

Query result

Duplicate and failed webhook deliveries

Stripe payment failures have the highest duplicate rate and more terminal failures.

Compare a numeric result field

invoice.payment_failed

push

provider	event_type	deliveries	duplicates	failures	duplicate_rate_pct	p95_latency_ms
stripe	invoice.payment_failed	480	34	9	7.08	1,180
github	push	2,940	42	3	1.43	420

Synthetic example output. Run the query against your own event schema and thresholds before using it for operational decisions.

Duplicate and failed webhook deliveries: static chart of synthetic duplicates values from the Measure Webhook Latency and Duplicate Rate example result — Indexable SVG of the deterministic example output. Download it for an article, runbook, or design review with attribution.

Reproduce the example

Download the public fixture

The JSON bundle includes the typed event contract, illustrative input rows, exact SQL, expected output, review notes, and engine version. The CSV contains the displayed result.

JSON fixture Expected output CSV Static SVG chart

How the SQL works

1CASE expressions compute duplicate and failure counts from the same delivery population.
2The duplicate rate is a delivery characteristic; it does not prove duplicate business effects.
3Tail latency shows whether the handler is approaching a provider timeout or retry boundary.

Edge cases to decide

A duplicate may be successfully deduplicated and should not automatically count as failure.
Provider retry policies and event volumes differ, so preserve provider and event type.
Never store webhook signatures or raw payment payloads in this table.