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Timestamp Min

Check: timestamp-min-check

Purpose: Validates that values in timestamp columns are not earlier than a defined minimum. A row fails if any selected column contains a timestamp before min_value.

Use the inclusive parameter to control boundary behavior:

  • inclusive: false (default) — value > min_value
  • inclusive: true — value >= min_value
from sparkdq.checks import TimestampMinCheckConfig
from sparkdq.core import Severity

TimestampMinCheckConfig(
    check_id="event-time-not-before-start",
    columns=["event_time"],
    min_value="2020-01-01 00:00:00",
    inclusive=True,
    severity=Severity.CRITICAL
)

- check: timestamp-min-check
  check-id: event-time-not-before-start
  columns:
    - event_time
  min-value: "2020-01-01 00:00:00"
  inclusive: true
  severity: critical

Typical Use Cases

  • Ensure that event or log timestamps are not older than the defined operational start time.
  • Validate that data collection began after a system go-live or migration cutover point.
  • Reject historically stale records outside the defined processing window.

← Row-Level Checks