Exists In
Definition
Asserts that values assigned to a field exist as values in another field.
In-Depth Overview
The ExistsIn
rule allows you to cross-validate data between different sources, whether it’s object storage systems or databases.
Traditionally, databases might utilize foreign key constraints (if available) to enforce data integrity between related tables. The ExistsIn
rule extends this concept in two powerful ways:
- Cross-System Integrity: it allows for integrity checks to span across different databases or even entirely separate systems. This is particularly advantageous in scenarios where data sources are fragmented across diverse platforms.
- Flexible Data Formats: Beyond just databases, this rule can validate values against various data formats, such as ensuring values in a file align with those in a table.
These enhancements enable businesses to maintain data integrity even in complex, multi-system environments.
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.
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
Define the datastore, table/file, and field where the rule should look for matching values.
Name | Description |
---|---|
Datastore |
The source datastore where the profile of the reference field is located. |
Table/file |
The profile (e.g. table, view or file) containing the reference field. |
Field |
The field name whose values should match those of the selected 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 all NATION_NAME entries in the NATION table match entries under the COUNTRY_NAME column in an external lookup file listing official country names.
Sample Data
N_NATIONKEY | N_NATIONNAME |
---|---|
1 | Algeria |
2 | Argentina |
3 | Atlantida |
{
"description": "Ensure that all NATION_NAME entries in the NATION table match entries under the COUNTRY_NAME column in an external lookup file listing official country names",
"coverage": 1,
"properties": {
"field_name":"COUNTRY_NAME",
"ref_container_id": {ref_container_id},
"ref_datastore_id": {ref_datastore_id}
},
"tags": [],
"fields": ["NATION_NAME"],
"additional_metadata": {"key 1": "value 1", "key 2": "value 2"},
"rule": "existsIn",
"container_id": {container_id},
"template_id": {template_id},
"filter": "1=1"
}
Lookup File Sample
COUNTRY_NAME |
---|
Algeria |
Argentina |
Brazil |
Canada |
... |
Zimbabwe |
Anomaly Explanation
In the sample data above, the entry with N_NATIONKEY
3 does not satisfy the rule because the N_NATIONNAME
"Atlantida" does not match any COUNTRY_NAME
in the official country names lookup file.
graph TD
A[Start] --> B[Retrieve COUNTRY_NAME]
B --> C[Retrieve N_NATIONNAME]
C --> D{Does N_NATIONNAME exists in COUNTRY_NAME?}
D -->|Yes| E[Move to Next Record/End]
D -->|No| F[Mark as Anomalous]
F --> E
Potential Violation Messages
Record Anomaly
The N_NATIONNAME
value of 'Atlantida'
does not exist in COUNTRY_NAME
.
Shape Anomaly
In N_NATIONNAME
, 33.333% of 3 filtered records (1) do not match any COUNTRY_NAME
.