CfnMatchingWorkflow
- class aws_cdk.aws_entityresolution.CfnMatchingWorkflow(scope, id, *, input_source_config, output_source_config, resolution_techniques, role_arn, workflow_name, description=None, incremental_run_config=None, tags=None)
Bases:
CfnResource
Creates a
MatchingWorkflow
object which stores the configuration of the data processing job to be run.It is important to note that there should not be a pre-existing
MatchingWorkflow
with the same name. To modify an existing workflow, utilize theUpdateMatchingWorkflow
API.- See:
- CloudformationResource:
AWS::EntityResolution::MatchingWorkflow
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. from aws_cdk import aws_entityresolution as entityresolution cfn_matching_workflow = entityresolution.CfnMatchingWorkflow(self, "MyCfnMatchingWorkflow", input_source_config=[entityresolution.CfnMatchingWorkflow.InputSourceProperty( input_source_arn="inputSourceArn", schema_arn="schemaArn", # the properties below are optional apply_normalization=False )], output_source_config=[entityresolution.CfnMatchingWorkflow.OutputSourceProperty( output=[entityresolution.CfnMatchingWorkflow.OutputAttributeProperty( name="name", # the properties below are optional hashed=False )], output_s3_path="outputS3Path", # the properties below are optional apply_normalization=False, kms_arn="kmsArn" )], resolution_techniques=entityresolution.CfnMatchingWorkflow.ResolutionTechniquesProperty( provider_properties=entityresolution.CfnMatchingWorkflow.ProviderPropertiesProperty( provider_service_arn="providerServiceArn", # the properties below are optional intermediate_source_configuration=entityresolution.CfnMatchingWorkflow.IntermediateSourceConfigurationProperty( intermediate_s3_path="intermediateS3Path" ), provider_configuration={ "provider_configuration_key": "providerConfiguration" } ), resolution_type="resolutionType", rule_based_properties=entityresolution.CfnMatchingWorkflow.RuleBasedPropertiesProperty( attribute_matching_model="attributeMatchingModel", rules=[entityresolution.CfnMatchingWorkflow.RuleProperty( matching_keys=["matchingKeys"], rule_name="ruleName" )], # the properties below are optional match_purpose="matchPurpose" ) ), role_arn="roleArn", workflow_name="workflowName", # the properties below are optional description="description", incremental_run_config=entityresolution.CfnMatchingWorkflow.IncrementalRunConfigProperty( incremental_run_type="incrementalRunType" ), tags=[CfnTag( key="key", value="value" )] )
- Parameters:
scope (
Construct
) – Scope in which this resource is defined.id (
str
) – Construct identifier for this resource (unique in its scope).input_source_config (
Union
[IResolvable
,Sequence
[Union
[IResolvable
,InputSourceProperty
,Dict
[str
,Any
]]]]) – A list ofInputSource
objects, which have the fieldsInputSourceARN
andSchemaName
.output_source_config (
Union
[IResolvable
,Sequence
[Union
[IResolvable
,OutputSourceProperty
,Dict
[str
,Any
]]]]) – A list ofOutputSource
objects, each of which contains fieldsOutputS3Path
,ApplyNormalization
, andOutput
.resolution_techniques (
Union
[IResolvable
,ResolutionTechniquesProperty
,Dict
[str
,Any
]]) – An object which defines theresolutionType
and theruleBasedProperties
.role_arn (
str
) – The Amazon Resource Name (ARN) of the IAM role. AWS Entity Resolution assumes this role to create resources on your behalf as part of workflow execution.workflow_name (
str
) – The name of the workflow. There can’t be multipleMatchingWorkflows
with the same name.description (
Optional
[str
]) – A description of the workflow.incremental_run_config (
Union
[IResolvable
,IncrementalRunConfigProperty
,Dict
[str
,Any
],None
]) – An object which defines an incremental run type and has onlyincrementalRunType
as a field.tags (
Optional
[Sequence
[Union
[CfnTag
,Dict
[str
,Any
]]]]) – The tags used to organize, track, or control access for this resource.
Methods
- add_deletion_override(path)
Syntactic sugar for
addOverride(path, undefined)
.- Parameters:
path (
str
) – The path of the value to delete.- Return type:
None
- add_dependency(target)
Indicates that this resource depends on another resource and cannot be provisioned unless the other resource has been successfully provisioned.
This can be used for resources across stacks (or nested stack) boundaries and the dependency will automatically be transferred to the relevant scope.
- Parameters:
target (
CfnResource
) –- Return type:
None
- add_depends_on(target)
(deprecated) Indicates that this resource depends on another resource and cannot be provisioned unless the other resource has been successfully provisioned.
- Parameters:
target (
CfnResource
) –- Deprecated:
use addDependency
- Stability:
deprecated
- Return type:
None
- add_metadata(key, value)
Add a value to the CloudFormation Resource Metadata.
- Parameters:
key (
str
) –value (
Any
) –
- See:
- Return type:
None
https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/metadata-section-structure.html
Note that this is a different set of metadata from CDK node metadata; this metadata ends up in the stack template under the resource, whereas CDK node metadata ends up in the Cloud Assembly.
- add_override(path, value)
Adds an override to the synthesized CloudFormation resource.
To add a property override, either use
addPropertyOverride
or prefixpath
with “Properties.” (i.e.Properties.TopicName
).If the override is nested, separate each nested level using a dot (.) in the path parameter. If there is an array as part of the nesting, specify the index in the path.
To include a literal
.
in the property name, prefix with a\
. In most programming languages you will need to write this as"\\."
because the\
itself will need to be escaped.For example:
cfn_resource.add_override("Properties.GlobalSecondaryIndexes.0.Projection.NonKeyAttributes", ["myattribute"]) cfn_resource.add_override("Properties.GlobalSecondaryIndexes.1.ProjectionType", "INCLUDE")
would add the overrides Example:
"Properties": { "GlobalSecondaryIndexes": [ { "Projection": { "NonKeyAttributes": [ "myattribute" ] ... } ... }, { "ProjectionType": "INCLUDE" ... }, ] ... }
The
value
argument toaddOverride
will not be processed or translated in any way. Pass raw JSON values in here with the correct capitalization for CloudFormation. If you pass CDK classes or structs, they will be rendered with lowercased key names, and CloudFormation will reject the template.- Parameters:
path (
str
) –The path of the property, you can use dot notation to override values in complex types. Any intermediate keys will be created as needed.
value (
Any
) –The value. Could be primitive or complex.
- Return type:
None
- add_property_deletion_override(property_path)
Adds an override that deletes the value of a property from the resource definition.
- Parameters:
property_path (
str
) – The path to the property.- Return type:
None
- add_property_override(property_path, value)
Adds an override to a resource property.
Syntactic sugar for
addOverride("Properties.<...>", value)
.- Parameters:
property_path (
str
) – The path of the property.value (
Any
) – The value.
- Return type:
None
- apply_removal_policy(policy=None, *, apply_to_update_replace_policy=None, default=None)
Sets the deletion policy of the resource based on the removal policy specified.
The Removal Policy controls what happens to this resource when it stops being managed by CloudFormation, either because you’ve removed it from the CDK application or because you’ve made a change that requires the resource to be replaced.
The resource can be deleted (
RemovalPolicy.DESTROY
), or left in your AWS account for data recovery and cleanup later (RemovalPolicy.RETAIN
). In some cases, a snapshot can be taken of the resource prior to deletion (RemovalPolicy.SNAPSHOT
). A list of resources that support this policy can be found in the following link:- Parameters:
policy (
Optional
[RemovalPolicy
]) –apply_to_update_replace_policy (
Optional
[bool
]) – Apply the same deletion policy to the resource’s “UpdateReplacePolicy”. Default: truedefault (
Optional
[RemovalPolicy
]) – The default policy to apply in case the removal policy is not defined. Default: - Default value is resource specific. To determine the default value for a resource, please consult that specific resource’s documentation.
- See:
- Return type:
None
- get_att(attribute_name, type_hint=None)
Returns a token for an runtime attribute of this resource.
Ideally, use generated attribute accessors (e.g.
resource.arn
), but this can be used for future compatibility in case there is no generated attribute.- Parameters:
attribute_name (
str
) – The name of the attribute.type_hint (
Optional
[ResolutionTypeHint
]) –
- Return type:
- get_metadata(key)
Retrieve a value value from the CloudFormation Resource Metadata.
- Parameters:
key (
str
) –- See:
- Return type:
Any
https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/metadata-section-structure.html
Note that this is a different set of metadata from CDK node metadata; this metadata ends up in the stack template under the resource, whereas CDK node metadata ends up in the Cloud Assembly.
- inspect(inspector)
Examines the CloudFormation resource and discloses attributes.
- Parameters:
inspector (
TreeInspector
) – tree inspector to collect and process attributes.- Return type:
None
- obtain_dependencies()
Retrieves an array of resources this resource depends on.
This assembles dependencies on resources across stacks (including nested stacks) automatically.
- Return type:
List
[Union
[Stack
,CfnResource
]]
- obtain_resource_dependencies()
Get a shallow copy of dependencies between this resource and other resources in the same stack.
- Return type:
List
[CfnResource
]
- override_logical_id(new_logical_id)
Overrides the auto-generated logical ID with a specific ID.
- Parameters:
new_logical_id (
str
) – The new logical ID to use for this stack element.- Return type:
None
- remove_dependency(target)
Indicates that this resource no longer depends on another resource.
This can be used for resources across stacks (including nested stacks) and the dependency will automatically be removed from the relevant scope.
- Parameters:
target (
CfnResource
) –- Return type:
None
- replace_dependency(target, new_target)
Replaces one dependency with another.
- Parameters:
target (
CfnResource
) – The dependency to replace.new_target (
CfnResource
) – The new dependency to add.
- Return type:
None
- to_string()
Returns a string representation of this construct.
- Return type:
str
- Returns:
a string representation of this resource
Attributes
- CFN_RESOURCE_TYPE_NAME = 'AWS::EntityResolution::MatchingWorkflow'
- attr_created_at
The time of this MatchingWorkflow got created.
- CloudformationAttribute:
CreatedAt
- attr_updated_at
The time of this MatchingWorkflow got last updated at.
- CloudformationAttribute:
UpdatedAt
- attr_workflow_arn
The default MatchingWorkflow arn.
- CloudformationAttribute:
WorkflowArn
- cdk_tag_manager
Tag Manager which manages the tags for this resource.
- cfn_options
Options for this resource, such as condition, update policy etc.
- cfn_resource_type
AWS resource type.
- creation_stack
return:
the stack trace of the point where this Resource was created from, sourced from the +metadata+ entry typed +aws:cdk:logicalId+, and with the bottom-most node +internal+ entries filtered.
- description
A description of the workflow.
- incremental_run_config
An object which defines an incremental run type and has only
incrementalRunType
as a field.
- input_source_config
A list of
InputSource
objects, which have the fieldsInputSourceARN
andSchemaName
.
- logical_id
The logical ID for this CloudFormation stack element.
The logical ID of the element is calculated from the path of the resource node in the construct tree.
To override this value, use
overrideLogicalId(newLogicalId)
.- Returns:
the logical ID as a stringified token. This value will only get resolved during synthesis.
- node
The tree node.
- output_source_config
A list of
OutputSource
objects, each of which contains fieldsOutputS3Path
,ApplyNormalization
, andOutput
.
- ref
Return a string that will be resolved to a CloudFormation
{ Ref }
for this element.If, by any chance, the intrinsic reference of a resource is not a string, you could coerce it to an IResolvable through
Lazy.any({ produce: resource.ref })
.
- resolution_techniques
An object which defines the
resolutionType
and theruleBasedProperties
.
- role_arn
The Amazon Resource Name (ARN) of the IAM role.
- stack
The stack in which this element is defined.
CfnElements must be defined within a stack scope (directly or indirectly).
- tags
The tags used to organize, track, or control access for this resource.
- workflow_name
The name of the workflow.
Static Methods
- classmethod is_cfn_element(x)
Returns
true
if a construct is a stack element (i.e. part of the synthesized cloudformation template).Uses duck-typing instead of
instanceof
to allow stack elements from different versions of this library to be included in the same stack.- Parameters:
x (
Any
) –- Return type:
bool
- Returns:
The construct as a stack element or undefined if it is not a stack element.
- classmethod is_cfn_resource(x)
Check whether the given object is a CfnResource.
- Parameters:
x (
Any
) –- Return type:
bool
- classmethod is_construct(x)
Checks if
x
is a construct.Use this method instead of
instanceof
to properly detectConstruct
instances, even when the construct library is symlinked.Explanation: in JavaScript, multiple copies of the
constructs
library on disk are seen as independent, completely different libraries. As a consequence, the classConstruct
in each copy of theconstructs
library is seen as a different class, and an instance of one class will not test asinstanceof
the other class.npm install
will not create installations like this, but users may manually symlink construct libraries together or use a monorepo tool: in those cases, multiple copies of theconstructs
library can be accidentally installed, andinstanceof
will behave unpredictably. It is safest to avoid usinginstanceof
, and using this type-testing method instead.- Parameters:
x (
Any
) – Any object.- Return type:
bool
- Returns:
true if
x
is an object created from a class which extendsConstruct
.
IncrementalRunConfigProperty
- class CfnMatchingWorkflow.IncrementalRunConfigProperty(*, incremental_run_type)
Bases:
object
An object which defines an incremental run type and has only
incrementalRunType
as a field.- Parameters:
incremental_run_type (
str
) – The type of incremental run. It takes only one value:IMMEDIATE
.- See:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. from aws_cdk import aws_entityresolution as entityresolution incremental_run_config_property = entityresolution.CfnMatchingWorkflow.IncrementalRunConfigProperty( incremental_run_type="incrementalRunType" )
Attributes
- incremental_run_type
The type of incremental run.
It takes only one value:
IMMEDIATE
.
InputSourceProperty
- class CfnMatchingWorkflow.InputSourceProperty(*, input_source_arn, schema_arn, apply_normalization=None)
Bases:
object
An object containing
InputSourceARN
,SchemaName
, andApplyNormalization
.- Parameters:
input_source_arn (
str
) – An object containingInputSourceARN
,SchemaName
, andApplyNormalization
.schema_arn (
str
) – The name of the schema.apply_normalization (
Union
[bool
,IResolvable
,None
]) – Normalizes the attributes defined in the schema in the input data. For example, if an attribute has anAttributeType
ofPHONE_NUMBER
, and the data in the input table is in a format of 1234567890, AWS Entity Resolution will normalize this field in the output to (123)-456-7890.
- See:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. from aws_cdk import aws_entityresolution as entityresolution input_source_property = entityresolution.CfnMatchingWorkflow.InputSourceProperty( input_source_arn="inputSourceArn", schema_arn="schemaArn", # the properties below are optional apply_normalization=False )
Attributes
- apply_normalization
Normalizes the attributes defined in the schema in the input data.
For example, if an attribute has an
AttributeType
ofPHONE_NUMBER
, and the data in the input table is in a format of 1234567890, AWS Entity Resolution will normalize this field in the output to (123)-456-7890.
- input_source_arn
An object containing
InputSourceARN
,SchemaName
, andApplyNormalization
.
IntermediateSourceConfigurationProperty
- class CfnMatchingWorkflow.IntermediateSourceConfigurationProperty(*, intermediate_s3_path)
Bases:
object
The Amazon S3 location that temporarily stores your data while it processes.
Your information won’t be saved permanently.
- Parameters:
intermediate_s3_path (
str
) – The Amazon S3 location (bucket and prefix). For example:s3://provider_bucket/DOC-EXAMPLE-BUCKET
- See:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. from aws_cdk import aws_entityresolution as entityresolution intermediate_source_configuration_property = entityresolution.CfnMatchingWorkflow.IntermediateSourceConfigurationProperty( intermediate_s3_path="intermediateS3Path" )
Attributes
- intermediate_s3_path
The Amazon S3 location (bucket and prefix).
For example:
s3://provider_bucket/DOC-EXAMPLE-BUCKET
OutputAttributeProperty
- class CfnMatchingWorkflow.OutputAttributeProperty(*, name, hashed=None)
Bases:
object
A list of
OutputAttribute
objects, each of which have the fieldsName
andHashed
.Each of these objects selects a column to be included in the output table, and whether the values of the column should be hashed.
- Parameters:
name (
str
) – A name of a column to be written to the output. This must be anInputField
name in the schema mapping.hashed (
Union
[bool
,IResolvable
,None
]) – Enables the ability to hash the column values in the output.
- See:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. from aws_cdk import aws_entityresolution as entityresolution output_attribute_property = entityresolution.CfnMatchingWorkflow.OutputAttributeProperty( name="name", # the properties below are optional hashed=False )
Attributes
- hashed
Enables the ability to hash the column values in the output.
- name
A name of a column to be written to the output.
This must be an
InputField
name in the schema mapping.
OutputSourceProperty
- class CfnMatchingWorkflow.OutputSourceProperty(*, output, output_s3_path, apply_normalization=None, kms_arn=None)
Bases:
object
A list of
OutputAttribute
objects, each of which have the fieldsName
andHashed
.Each of these objects selects a column to be included in the output table, and whether the values of the column should be hashed.
- Parameters:
output (
Union
[IResolvable
,Sequence
[Union
[IResolvable
,OutputAttributeProperty
,Dict
[str
,Any
]]]]) – A list ofOutputAttribute
objects, each of which have the fieldsName
andHashed
. Each of these objects selects a column to be included in the output table, and whether the values of the column should be hashed.output_s3_path (
str
) – The S3 path to which AWS Entity Resolution will write the output table.apply_normalization (
Union
[bool
,IResolvable
,None
]) – Normalizes the attributes defined in the schema in the input data. For example, if an attribute has anAttributeType
ofPHONE_NUMBER
, and the data in the input table is in a format of 1234567890, AWS Entity Resolution will normalize this field in the output to (123)-456-7890.kms_arn (
Optional
[str
]) – Customer KMS ARN for encryption at rest. If not provided, system will use an AWS Entity Resolution managed KMS key.
- See:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. from aws_cdk import aws_entityresolution as entityresolution output_source_property = entityresolution.CfnMatchingWorkflow.OutputSourceProperty( output=[entityresolution.CfnMatchingWorkflow.OutputAttributeProperty( name="name", # the properties below are optional hashed=False )], output_s3_path="outputS3Path", # the properties below are optional apply_normalization=False, kms_arn="kmsArn" )
Attributes
- apply_normalization
Normalizes the attributes defined in the schema in the input data.
For example, if an attribute has an
AttributeType
ofPHONE_NUMBER
, and the data in the input table is in a format of 1234567890, AWS Entity Resolution will normalize this field in the output to (123)-456-7890.
- kms_arn
Customer KMS ARN for encryption at rest.
If not provided, system will use an AWS Entity Resolution managed KMS key.
- output
A list of
OutputAttribute
objects, each of which have the fieldsName
andHashed
.Each of these objects selects a column to be included in the output table, and whether the values of the column should be hashed.
- output_s3_path
The S3 path to which AWS Entity Resolution will write the output table.
ProviderPropertiesProperty
- class CfnMatchingWorkflow.ProviderPropertiesProperty(*, provider_service_arn, intermediate_source_configuration=None, provider_configuration=None)
Bases:
object
An object containing the
providerServiceARN
,intermediateSourceConfiguration
, andproviderConfiguration
.- Parameters:
provider_service_arn (
str
) – The ARN of the provider service.intermediate_source_configuration (
Union
[IResolvable
,IntermediateSourceConfigurationProperty
,Dict
[str
,Any
],None
]) – The Amazon S3 location that temporarily stores your data while it processes. Your information won’t be saved permanently.provider_configuration (
Union
[IResolvable
,Mapping
[str
,str
],None
]) – The required configuration fields to use with the provider service.
- See:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. from aws_cdk import aws_entityresolution as entityresolution provider_properties_property = entityresolution.CfnMatchingWorkflow.ProviderPropertiesProperty( provider_service_arn="providerServiceArn", # the properties below are optional intermediate_source_configuration=entityresolution.CfnMatchingWorkflow.IntermediateSourceConfigurationProperty( intermediate_s3_path="intermediateS3Path" ), provider_configuration={ "provider_configuration_key": "providerConfiguration" } )
Attributes
- intermediate_source_configuration
The Amazon S3 location that temporarily stores your data while it processes.
Your information won’t be saved permanently.
- provider_configuration
The required configuration fields to use with the provider service.
- provider_service_arn
The ARN of the provider service.
ResolutionTechniquesProperty
- class CfnMatchingWorkflow.ResolutionTechniquesProperty(*, provider_properties=None, resolution_type=None, rule_based_properties=None)
Bases:
object
An object which defines the
resolutionType
and theruleBasedProperties
.- Parameters:
provider_properties (
Union
[IResolvable
,ProviderPropertiesProperty
,Dict
[str
,Any
],None
]) – The properties of the provider service.resolution_type (
Optional
[str
]) – The type of matching. There are three types of matching:RULE_MATCHING
,ML_MATCHING
, andPROVIDER
.rule_based_properties (
Union
[IResolvable
,RuleBasedPropertiesProperty
,Dict
[str
,Any
],None
]) – An object which defines the list of matching rules to run and has a fieldRules
, which is a list of rule objects.
- See:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. from aws_cdk import aws_entityresolution as entityresolution resolution_techniques_property = entityresolution.CfnMatchingWorkflow.ResolutionTechniquesProperty( provider_properties=entityresolution.CfnMatchingWorkflow.ProviderPropertiesProperty( provider_service_arn="providerServiceArn", # the properties below are optional intermediate_source_configuration=entityresolution.CfnMatchingWorkflow.IntermediateSourceConfigurationProperty( intermediate_s3_path="intermediateS3Path" ), provider_configuration={ "provider_configuration_key": "providerConfiguration" } ), resolution_type="resolutionType", rule_based_properties=entityresolution.CfnMatchingWorkflow.RuleBasedPropertiesProperty( attribute_matching_model="attributeMatchingModel", rules=[entityresolution.CfnMatchingWorkflow.RuleProperty( matching_keys=["matchingKeys"], rule_name="ruleName" )], # the properties below are optional match_purpose="matchPurpose" ) )
Attributes
- provider_properties
The properties of the provider service.
- resolution_type
The type of matching.
There are three types of matching:
RULE_MATCHING
,ML_MATCHING
, andPROVIDER
.
- rule_based_properties
An object which defines the list of matching rules to run and has a field
Rules
, which is a list of rule objects.
RuleBasedPropertiesProperty
- class CfnMatchingWorkflow.RuleBasedPropertiesProperty(*, attribute_matching_model, rules, match_purpose=None)
Bases:
object
An object which defines the list of matching rules to run in a matching workflow.
RuleBasedProperties contain a
Rules
field, which is a list of rule objects.- Parameters:
attribute_matching_model (
str
) – The comparison type. You can either chooseONE_TO_ONE
orMANY_TO_MANY
as theattributeMatchingModel
. If you chooseMANY_TO_MANY
, the system can match attributes across the sub-types of an attribute type. For example, if the value of theEmail
field of Profile A and the value ofBusinessEmail
field of Profile B matches, the two profiles are matched on theEmail
attribute type. If you chooseONE_TO_ONE
, the system can only match attributes if the sub-types are an exact match. For example, for theEmail
attribute type, the system will only consider it a match if the value of theEmail
field of Profile A matches the value of theEmail
field of Profile B.rules (
Union
[IResolvable
,Sequence
[Union
[IResolvable
,RuleProperty
,Dict
[str
,Any
]]]]) – A list ofRule
objects, each of which have fieldsRuleName
andMatchingKeys
.match_purpose (
Optional
[str
]) – An indicator of whether to generate IDs and index the data or not. If you chooseIDENTIFIER_GENERATION
, the process generates IDs and indexes the data. If you chooseINDEXING
, the process indexes the data without generating IDs.
- See:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. from aws_cdk import aws_entityresolution as entityresolution rule_based_properties_property = entityresolution.CfnMatchingWorkflow.RuleBasedPropertiesProperty( attribute_matching_model="attributeMatchingModel", rules=[entityresolution.CfnMatchingWorkflow.RuleProperty( matching_keys=["matchingKeys"], rule_name="ruleName" )], # the properties below are optional match_purpose="matchPurpose" )
Attributes
- attribute_matching_model
The comparison type. You can either choose
ONE_TO_ONE
orMANY_TO_MANY
as theattributeMatchingModel
.If you choose
MANY_TO_MANY
, the system can match attributes across the sub-types of an attribute type. For example, if the value of theEmail
field of Profile A and the value ofBusinessEmail
field of Profile B matches, the two profiles are matched on theEmail
attribute type.If you choose
ONE_TO_ONE
, the system can only match attributes if the sub-types are an exact match. For example, for theEmail
attribute type, the system will only consider it a match if the value of theEmail
field of Profile A matches the value of theEmail
field of Profile B.
- match_purpose
An indicator of whether to generate IDs and index the data or not.
If you choose
IDENTIFIER_GENERATION
, the process generates IDs and indexes the data.If you choose
INDEXING
, the process indexes the data without generating IDs.
- rules
A list of
Rule
objects, each of which have fieldsRuleName
andMatchingKeys
.
RuleProperty
- class CfnMatchingWorkflow.RuleProperty(*, matching_keys, rule_name)
Bases:
object
An object containing
RuleName
, andMatchingKeys
.- Parameters:
matching_keys (
Sequence
[str
]) – A list ofMatchingKeys
. TheMatchingKeys
must have been defined in theSchemaMapping
. Two records are considered to match according to this rule if all of theMatchingKeys
match.rule_name (
str
) – A name for the matching rule.
- See:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. from aws_cdk import aws_entityresolution as entityresolution rule_property = entityresolution.CfnMatchingWorkflow.RuleProperty( matching_keys=["matchingKeys"], rule_name="ruleName" )
Attributes
- matching_keys
A list of
MatchingKeys
.The
MatchingKeys
must have been defined in theSchemaMapping
. Two records are considered to match according to this rule if all of theMatchingKeys
match.
- rule_name
A name for the matching rule.