How Between Times Checks Work

Definition

Asserts that every value in a Date or Timestamp field falls between a start and an end instant, with both boundaries included.

Overview

The Between Times rule defines a time window on a single date or timestamp field. Each row must hold a value inside the window formed by Min and Max. Unlike the numeric Between rule, both boundaries are always inclusive: a value equal to the start or to the end passes. Both boundaries are stored as UTC instants, and the comparison runs in UTC.

Typical use cases:

• Validate that dates fall inside a reporting period, such as a fiscal quarter.
• Keep event timestamps inside a contract term or a campaign window.
• Catch values outside a plausible range, such as an activity date before the system existed or far in the future.

Field Scope

Single: The rule evaluates exactly one field per check.

Accepted Types

On an array field every element is tested against the window and the row fails as soon as one element falls outside it. That evaluation runs as a field-level check, so it reports a Shape Anomaly for the field instead of per-row Record Anomalies, whatever the coverage is set to.

General Properties

The filter allows you to define a subset of data upon which the rule will operate.

It requires a valid Spark SQL expression that determines the criteria rows in the DataFrame should meet. This means the expression specifies which rows the DataFrame should include based on those criteria. Since it's applied directly to the Spark DataFrame, traditional SQL constructs like WHERE clauses are not supported.

O_TOTALPRICE > 1000

C_MKTSEGMENT = 'BUILDING'

WHERE O_TOTALPRICE > 1000

WHERE C_MKTSEGMENT = 'BUILDING'

O_ORDERPRIORITY = '1-URGENT' AND O_ORDERSTATUS = 'O'

(L_SHIPDATE = '1998-09-02' OR L_RECEIPTDATE = '1998-09-01') AND L_RETURNFLAG = 'R'

WHERE O_ORDERPRIORITY = '1-URGENT' AND O_ORDERSTATUS = 'O'

O_TOTALPRICE > 1000, O_ORDERSTATUS = 'O'

RIGHT(
    O_ORDERPRIORITY,
    LENGTH(O_ORDERPRIORITY) - INSTR('-', O_ORDERPRIORITY)
) = 'URGENT'

LEVENSHTEIN(C_NAME, 'Supplier#000000001') < 7

RIGHT(
    O_ORDERPRIORITY,
    LENGTH(O_ORDERPRIORITY) - CHARINDEX('-', O_ORDERPRIORITY)
) = 'URGENT'

EDITDISTANCE(C_NAME, 'Supplier#000000001') < 7

O_ORDERSTATUS IN (
    SELECT DISTINCT O_ORDERSTATUS
    FROM {{_qualytics_self}}
    WHERE O_TOTALPRICE > 1000
)

O_ORDERSTATUS IN (
    SELECT DISTINCT O_ORDERSTATUS
    FROM ORDERS
    WHERE O_TOTALPRICE > 1000
)

Specific Properties

Between Times has two rule-specific properties:

Anomaly Types

Evaluation Flow

Every Between Times check follows the same four-step evaluation flow:

1. Apply the filter clause. If the check has a filter set, only rows matching the filter expression continue to the next step. Rows outside the filter are ignored and cannot contribute to the violation count.
2. Interpret the field value as a timestamp. The platform reads the row's value as an instant for comparison.
3. Compare against both boundaries. The value must be greater than or equal to Min and less than or equal to Max. Failing either side fails the row.
4. Apply coverage. At 100% coverage, any failing row causes the check to fail. Below 100% coverage, the check fails only when the passing fraction drops below the threshold (see Coverage and Tolerance).

Both Boundaries Are Inclusive

Between Times has no inclusivity toggles: a value equal to Min or to Max always passes. When you need an exclusive edge, pair After Date Time and Before Date Time, which are both strict. Nudging the boundary instead (one day earlier on a Date) only works when the column has no finer resolution than the step you take: on a timestamp with sub-second precision, pulling the upper bound back by a second also rejects the values in between, such as 11:59:59.500.

Time Zone Behavior

Both boundaries are stored as UTC instants and the comparison runs in UTC. Values that carry an explicit time zone are compared directly; values without one are interpreted as UTC (a Date counts as midnight UTC of that day). When the source data was written in a local or mixed time zone, normalize the field upstream with a Computed Field so the window means the same thing for every row.

NULL Handling

The check passes NULL values: a row with NULL in the evaluated field is not counted as a violation. Between Times only asserts that present values fall inside the window.

If the field must also be populated, pair it with a Not Null check on the same field. Values that cannot be interpreted as a timestamp are flagged as violations, which rarely happens because the field picker accepts only Date, Timestamp, and array fields.

Array Fields

On an array field, every element is tested against the window and the row fails as soon as one element falls outside it. Empty arrays and NULL arrays pass, since there is nothing to evaluate.

The Filter Clause

The filter clause is a SQL WHERE expression applied before the evaluation. Filtered-out rows are ignored entirely (they cannot trigger a violation and are not counted in the totals).

When a filter is set, both the Record Anomaly and the Shape Anomaly messages end with [filter: <expression>] so the evaluated scope is visible in the alert.

Coverage and Tolerance

Coverage is a fractional value between 0 and 1 that defines the minimum fraction of evaluated rows that must pass:

• 1.0 (100%, default): every row in the filtered set must pass. Any failing row causes the check to fail. This is the strictest setting.
• < 1.0: the check tolerates a fraction of rows failing. The check fails only when the fraction of passing rows drops below the threshold.

Lower coverage values are useful when a small, known fraction of failures is expected. Use coverage carefully: a 0.5% tolerance can mask a real regression that happens to fall just under the threshold.

See Also