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Required Values

Definition

Asserts that all of the defined values must be present at least once within a field.

Field Scope

Single: The rule evaluates a single specified field.

Accepted Types

Type
Date
Timestamp
Integral
Fractional
String
Boolean

General Properties

Name Supported
Filter
Allows the targeting of specific data based on conditions
Coverage Customization
Allows adjusting the percentage of records that must meet the rule's conditions

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.

Examples

Direct Conditions

Simply specify the condition you want to be met.

Correct usage 
O_TOTALPRICE > 1000

C_MKTSEGMENT = 'BUILDING'
Incorrect usage 
WHERE O_TOTALPRICE > 1000

WHERE C_MKTSEGMENT = 'BUILDING'

Combining Conditions

Combine multiple conditions using logical operators like AND and OR.

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

(L_SHIPDATE = '1998-09-02' OR L_RECEIPTDATE = '1998-09-01') AND L_RETURNFLAG = 'R'
Incorrect usage 
WHERE O_ORDERPRIORITY = '1-URGENT' AND O_ORDERSTATUS = 'O'

O_TOTALPRICE > 1000, O_ORDERSTATUS = 'O'

Utilizing Functions

Leverage Spark SQL functions to refine and enhance your conditions.

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

LEVENSHTEIN(C_NAME, 'Supplier#000000001') < 7
Incorrect usage 
RIGHT(
    O_ORDERPRIORITY,
    LENGTH(O_ORDERPRIORITY) - CHARINDEX('-', O_ORDERPRIORITY)
) = 'URGENT'

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

Using scan-time variables

To refer to the current dataframe being analyzed, use the reserved dynamic variable {{ _qualytics_self }}.

Correct usage 
O_ORDERSTATUS IN (
    SELECT DISTINCT O_ORDERSTATUS
    FROM {{ _qualytics_self }}
    WHERE O_TOTALPRICE > 1000
)
Incorrect usage 
O_ORDERSTATUS IN (
    SELECT DISTINCT O_ORDERSTATUS
    FROM ORDERS
    WHERE O_TOTALPRICE > 1000
)

While subqueries can be useful, their application within filters in our context has limitations. For example, directly referencing other containers or the broader target container in such subqueries is not supported. Attempting to do so will result in an error.

Important Note on {{ _qualytics_self }}

The {{ _qualytics_self }} keyword refers to the dataframe that's currently under examination. In the context of a full scan, this variable represents the entire target container. However, during incremental scans, it only reflects a subset of the target container, capturing just the incremental data. It's crucial to recognize that in such scenarios, using {{ _qualytics_self }} may not encompass all entries from the target container.

Specific Properties

Ensures that a specific set of values is present within a field.

Name Description
Values
 Specifies the list of values that must exist in the field.

Anomaly Types

Type Supported
Record
Flag inconsistencies at the row level
Shape
Flag inconsistencies in the overall patterns and distributions of a field

Example

Objective: Ensure that orders have priorities labeled as '1-URGENT', '2-HIGH', '3-MEDIUM', '4-LOW', and '5-NOT URGENT'.

Sample Data

O_ORDERKEY O_ORDERPRIORITY
1 1-URGENT
2 2-HIGH
3 3-MEDIUM
4 3-MEDIUM 
{
    "description": "Ensure that orders have priorities labeled as '1-URGENT', '2-HIGH', '3-MEDIUM', '4-LOW', and '5-NOT URGENT'",
    "coverage": 1,
    "properties": {
        "list":["1-URGENT","2-HIGH","3-MEDIUM","4-LOW","5-NOT URGENT"]
    },
    "tags": [],
    "fields": ["O_ORDERPRIORITY"],
    "additional_metadata": {"key 1": "value 1", "key 2": "value 2"},
    "rule": "requiredValues",
    "container_id": {container_id},
    "template_id": {template_id},
    "filter": "1=1"
}

Anomaly Explanation

In the sample data above, the rule is violated because the values '4-LOW' and '5-NOT URGENT' are not present in the O_ORDERPRIORITY field of the ORDERS table.

graph TD
A[Start] --> B{Check if all specified values exist in the field}
B -->|Yes| C[End: No Anomalies]
B -->|No| D[Mark as Anomalous: Missing Values]
D --> C
-- An illustrative SQL query demonstrating the rule applied to example dataset(s).
select distinct
    o_orderpriority
from orders
where o_orderpriority in ('1-URGENT', '2-HIGH', '3-MEDIUM', '4-LOW', '5-NOT URGENT');

Potential Violation Messages

Shape Anomaly

In O_ORDERPRIORITY, required values are missing in 40.000% of filtered records.