interface RuleConditionProperty
Language | Type name |
---|---|
![]() | Amazon.CDK.aws_entityresolution.CfnMatchingWorkflow.RuleConditionProperty |
![]() | github.com/aws/aws-cdk-go/awscdk/v2/awsentityresolution#CfnMatchingWorkflow_RuleConditionProperty |
![]() | software.amazon.awscdk.services.entityresolution.CfnMatchingWorkflow.RuleConditionProperty |
![]() | aws_cdk.aws_entityresolution.CfnMatchingWorkflow.RuleConditionProperty |
![]() | aws-cdk-lib » aws_entityresolution » CfnMatchingWorkflow » RuleConditionProperty |
An object that defines the ruleCondition
and the ruleName
to use in a matching workflow.
Example
// The code below shows an example of how to instantiate this type.
// The values are placeholders you should change.
import { aws_entityresolution as entityresolution } from 'aws-cdk-lib';
const ruleConditionProperty: entityresolution.CfnMatchingWorkflow.RuleConditionProperty = {
condition: 'condition',
ruleName: 'ruleName',
};
Properties
Name | Type | Description |
---|---|---|
condition? | string | A statement that specifies the conditions for a matching rule. |
rule | string | A name for the matching rule. |
condition?
Type:
string
(optional)
A statement that specifies the conditions for a matching rule.
If your data is accurate, use an Exact matching function: Exact
or ExactManyToMany
.
If your data has variations in spelling or pronunciation, use a Fuzzy matching function: Cosine
, Levenshtein
, or Soundex
.
Use operators if you want to combine ( AND
), separate ( OR
), or group matching functions (...)
.
For example: (Cosine(a, 10) AND Exact(b, true)) OR ExactManyToMany(c, d)
ruleName?
Type:
string
(optional)
A name for the matching rule.
For example: Rule1