Less Than Field
Definition
Asserts that the field is less than another field.
Field Scope
Single: The rule evaluates a single specified field.
Accepted Types
Type | |
---|---|
Date |
|
Timestamp |
|
Integral |
|
Fractional |
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.
Combining Conditions
Combine multiple conditions using logical operators like AND
and OR
.
Correct usage
Incorrect usage
Utilizing Functions
Leverage Spark SQL functions to refine and enhance your conditions.
Correct usage
Incorrect usage
Using scan-time variables
To refer to the current dataframe being analyzed, use the reserved dynamic variable {{_qualytics_self}}
.
Correct usage
Incorrect usage
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
Allows specifying another field against which the value comparison will be performed.
Name | Description |
---|---|
Field to compare |
Specifies the name of the field against which the value will be compared. |
Inclusive |
If true, the comparison will also allow values equal to the value of the other field. Otherwise, it's exclusive. |
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 all O_DISCOUNT entries in the ORDERS table are less than their respective O_TOTALPRICE.
Sample Data
O_ORDERKEY | O_TOTALPRICE | O_DISCOUNT |
---|---|---|
1 | 105 | 100 |
2 | 500 | 10 |
3 | 121 | 125 |
Anomaly Explanation
In the sample data above, the entry with O_ORDERKEY
3 does not satisfy the rule because its O_DISCOUNT
value is not less than its respective O_TOTALPRICE
value.
graph TD
A[Start] --> B[Retrieve O_TOTALPRICE and O_DISCOUNT]
B --> C{Is O_DISCOUNT < O_TOTALPRICE?}
C -->|Yes| D[Move to Next Record/End]
C -->|No| E[Mark as Anomalous]
E --> D
Potential Violation Messages
Record Anomaly
The O_DISCOUNT
value of 125
is not less than the value of O_TOTALPRICE
.
Shape Anomaly
In O_DISCOUNT
, 33.333% of 3 filtered records (1) is not less than O_TOTALPRICE
.