How Max Value Checks Work

Definition

Asserts that every value in a numeric field is less than or equal to a configured maximum.

Overview

The Max Value rule caps a single numeric field. Each row passes when its value is less than or equal to the configured Value. The ceiling itself is accepted, so a row holding exactly the maximum passes. There is no inclusivity toggle on this rule: when the ceiling must be rejected, configure a slightly lower one or use Less Than, which offers the choice.

Typical use cases:

• Cap a monetary amount at a contractual or regulatory limit.
• Keep a percentage or a ratio from exceeding its natural maximum.
• Catch quantities that exceed what the business or the physical process allows.

Field Scope

Single: The rule evaluates exactly one field per check.

Accepted Types

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

Max Value has one rule-specific property:

Anomaly Types

Evaluation Flow

Every Max Value 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. Read the field value. The platform reads the numeric value for the current row.
3. Compare against the ceiling. The row passes when the value is less than or equal to Value, and fails when it is above it.
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).

The Ceiling Is Inclusive

A value exactly equal to Value passes: the comparison is value <= maximum. Max Value has no inclusivity toggle, which makes it asymmetric with Min Value, whose floor is exclusive. When you need the ceiling itself rejected, either configure a ceiling just below it or use Less Than, where inclusivity is a setting.

NULL Handling

The check passes NULL values: a row with NULL in the evaluated field is not counted as a violation. Max Value only asserts that present values respect the ceiling.

If the field must also be populated, pair it with a Not Null check on the same field.

Numeric Fields Inside an Array

An array column itself cannot be selected: the rule accepts Integral and Fractional only, and anything else is rejected with 422. A numeric field nested inside an array of structs can be selected, and there the rule is evaluated element-wise: every element is tested against the ceiling and the row fails as soon as one element exceeds it. Empty arrays and NULL arrays pass, since there is nothing to evaluate.

Element-wise 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.

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