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Date Max

Check: date-max-check

Purpose: Validates that values in date columns do not exceed a defined maximum date. A row fails if any selected column contains a date after max_value.

Use the inclusive parameter to control boundary behavior:

  • inclusive: false (default) — value < max_value
  • inclusive: true — value <= max_value
from sparkdq.checks import DateMaxCheckConfig
from sparkdq.core import Severity

DateMaxCheckConfig(
    check_id="record-date-not-in-future",
    columns=["record_date"],
    max_value="2023-12-31",
    inclusive=True,
    severity=Severity.CRITICAL
)

- check: date-max-check
  check-id: record-date-not-in-future
  columns:
    - record_date
  max-value: "2023-12-31"
  inclusive: true
  severity: critical

Typical Use Cases

  • Ensure that event or transaction dates do not lie in the future.
  • Enforce a cutoff date for a reporting period or fiscal year end.
  • Detect future-dated records caused by data entry errors or timezone misconfiguration.

← Row-Level Checks