CfnApplicationReferenceDataSourceV2
- class aws_cdk.aws_kinesisanalytics.CfnApplicationReferenceDataSourceV2(scope, id, *, application_name, reference_data_source)
Bases:
CfnResource
A CloudFormation
AWS::KinesisAnalyticsV2::ApplicationReferenceDataSource
.Adds a reference data source to an existing SQL-based Kinesis Data Analytics application.
Kinesis Data Analytics reads reference data (that is, an Amazon S3 object) and creates an in-application table within your application. In the request, you provide the source (S3 bucket name and object key name), name of the in-application table to create, and the necessary mapping information that describes how data in an Amazon S3 object maps to columns in the resulting in-application table.
- CloudformationResource
AWS::KinesisAnalyticsV2::ApplicationReferenceDataSource
- Link
- ExampleMetadata
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. import aws_cdk.aws_kinesisanalytics as kinesisanalytics cfn_application_reference_data_source_v2 = kinesisanalytics.CfnApplicationReferenceDataSourceV2(self, "MyCfnApplicationReferenceDataSourceV2", application_name="applicationName", reference_data_source=kinesisanalytics.CfnApplicationReferenceDataSourceV2.ReferenceDataSourceProperty( reference_schema=kinesisanalytics.CfnApplicationReferenceDataSourceV2.ReferenceSchemaProperty( record_columns=[kinesisanalytics.CfnApplicationReferenceDataSourceV2.RecordColumnProperty( name="name", sql_type="sqlType", # the properties below are optional mapping="mapping" )], record_format=kinesisanalytics.CfnApplicationReferenceDataSourceV2.RecordFormatProperty( record_format_type="recordFormatType", # the properties below are optional mapping_parameters=kinesisanalytics.CfnApplicationReferenceDataSourceV2.MappingParametersProperty( csv_mapping_parameters=kinesisanalytics.CfnApplicationReferenceDataSourceV2.CSVMappingParametersProperty( record_column_delimiter="recordColumnDelimiter", record_row_delimiter="recordRowDelimiter" ), json_mapping_parameters=kinesisanalytics.CfnApplicationReferenceDataSourceV2.JSONMappingParametersProperty( record_row_path="recordRowPath" ) ) ), # the properties below are optional record_encoding="recordEncoding" ), # the properties below are optional s3_reference_data_source=kinesisanalytics.CfnApplicationReferenceDataSourceV2.S3ReferenceDataSourceProperty( bucket_arn="bucketArn", file_key="fileKey" ), table_name="tableName" ) )
Create a new
AWS::KinesisAnalyticsV2::ApplicationReferenceDataSource
.- Parameters
scope (
Construct
) –scope in which this resource is defined.
id (
str
) –scoped id of the resource.
application_name (
str
) – The name of the application.reference_data_source (
Union
[IResolvable
,ReferenceDataSourceProperty
,Dict
[str
,Any
]]) – For a SQL-based Kinesis Data Analytics application, describes the reference data source by providing the source information (Amazon S3 bucket name and object key name), the resulting in-application table name that is created, and the necessary schema to map the data elements in the Amazon S3 object to the in-application table.
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_depends_on(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_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 intermdediate 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
).- 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 resoure, please consult that specific resource’s documentation.
- Return type
None
- get_att(attribute_name)
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.- 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
- 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
- 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::KinesisAnalyticsV2::ApplicationReferenceDataSource'
- application_name
The name of the application.
- 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.
- 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 construct tree node associated with this construct.
- 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 })
.
- reference_data_source
For a SQL-based Kinesis Data Analytics application, describes the reference data source by providing the source information (Amazon S3 bucket name and object key name), the resulting in-application table name that is created, and the necessary schema to map the data elements in the Amazon S3 object to the in-application table.
- stack
The stack in which this element is defined.
CfnElements must be defined within a stack scope (directly or indirectly).
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(construct)
Check whether the given construct is a CfnResource.
- Parameters
construct (
IConstruct
) –- Return type
bool
- classmethod is_construct(x)
Return whether the given object is a Construct.
- Parameters
x (
Any
) –- Return type
bool
CSVMappingParametersProperty
- class CfnApplicationReferenceDataSourceV2.CSVMappingParametersProperty(*, record_column_delimiter, record_row_delimiter)
Bases:
object
For a SQL-based Kinesis Data Analytics application, provides additional mapping information when the record format uses delimiters, such as CSV.
For example, the following sample records use CSV format, where the records use the ‘n’ as the row delimiter and a comma (“,”) as the column delimiter:
"name1", "address1"
"name2", "address2"
- Parameters
record_column_delimiter (
str
) – The column delimiter. For example, in a CSV format, a comma (“,”) is the typical column delimiter.record_row_delimiter (
str
) – The row delimiter. For example, in a CSV format, ‘n’ is the typical row delimiter.
- Link
- ExampleMetadata
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. import aws_cdk.aws_kinesisanalytics as kinesisanalytics c_sVMapping_parameters_property = kinesisanalytics.CfnApplicationReferenceDataSourceV2.CSVMappingParametersProperty( record_column_delimiter="recordColumnDelimiter", record_row_delimiter="recordRowDelimiter" )
Attributes
- record_column_delimiter
The column delimiter.
For example, in a CSV format, a comma (“,”) is the typical column delimiter.
- record_row_delimiter
The row delimiter.
For example, in a CSV format, ‘n’ is the typical row delimiter.
JSONMappingParametersProperty
- class CfnApplicationReferenceDataSourceV2.JSONMappingParametersProperty(*, record_row_path)
Bases:
object
For a SQL-based Kinesis Data Analytics application, provides additional mapping information when JSON is the record format on the streaming source.
- Parameters
record_row_path (
str
) – The path to the top-level parent that contains the records.- Link
- ExampleMetadata
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. import aws_cdk.aws_kinesisanalytics as kinesisanalytics j_sONMapping_parameters_property = kinesisanalytics.CfnApplicationReferenceDataSourceV2.JSONMappingParametersProperty( record_row_path="recordRowPath" )
Attributes
- record_row_path
The path to the top-level parent that contains the records.
MappingParametersProperty
- class CfnApplicationReferenceDataSourceV2.MappingParametersProperty(*, csv_mapping_parameters=None, json_mapping_parameters=None)
Bases:
object
When you configure a SQL-based Kinesis Data Analytics application’s input at the time of creating or updating an application, provides additional mapping information specific to the record format (such as JSON, CSV, or record fields delimited by some delimiter) on the streaming source.
- Parameters
csv_mapping_parameters (
Union
[IResolvable
,CSVMappingParametersProperty
,Dict
[str
,Any
],None
]) – Provides additional mapping information when the record format uses delimiters (for example, CSV).json_mapping_parameters (
Union
[IResolvable
,JSONMappingParametersProperty
,Dict
[str
,Any
],None
]) – Provides additional mapping information when JSON is the record format on the streaming source.
- Link
- ExampleMetadata
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. import aws_cdk.aws_kinesisanalytics as kinesisanalytics mapping_parameters_property = kinesisanalytics.CfnApplicationReferenceDataSourceV2.MappingParametersProperty( csv_mapping_parameters=kinesisanalytics.CfnApplicationReferenceDataSourceV2.CSVMappingParametersProperty( record_column_delimiter="recordColumnDelimiter", record_row_delimiter="recordRowDelimiter" ), json_mapping_parameters=kinesisanalytics.CfnApplicationReferenceDataSourceV2.JSONMappingParametersProperty( record_row_path="recordRowPath" ) )
Attributes
- csv_mapping_parameters
Provides additional mapping information when the record format uses delimiters (for example, CSV).
- json_mapping_parameters
Provides additional mapping information when JSON is the record format on the streaming source.
RecordColumnProperty
- class CfnApplicationReferenceDataSourceV2.RecordColumnProperty(*, name, sql_type, mapping=None)
Bases:
object
For a SQL-based Kinesis Data Analytics application, describes the mapping of each data element in the streaming source to the corresponding column in the in-application stream.
Also used to describe the format of the reference data source.
- Parameters
name (
str
) – The name of the column that is created in the in-application input stream or reference table.sql_type (
str
) – The type of column created in the in-application input stream or reference table.mapping (
Optional
[str
]) – A reference to the data element in the streaming input or the reference data source.
- Link
- ExampleMetadata
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. import aws_cdk.aws_kinesisanalytics as kinesisanalytics record_column_property = kinesisanalytics.CfnApplicationReferenceDataSourceV2.RecordColumnProperty( name="name", sql_type="sqlType", # the properties below are optional mapping="mapping" )
Attributes
- mapping
A reference to the data element in the streaming input or the reference data source.
- name
The name of the column that is created in the in-application input stream or reference table.
- sql_type
The type of column created in the in-application input stream or reference table.
RecordFormatProperty
- class CfnApplicationReferenceDataSourceV2.RecordFormatProperty(*, record_format_type, mapping_parameters=None)
Bases:
object
For a SQL-based Kinesis Data Analytics application, describes the record format and relevant mapping information that should be applied to schematize the records on the stream.
- Parameters
record_format_type (
str
) – The type of record format.mapping_parameters (
Union
[IResolvable
,MappingParametersProperty
,Dict
[str
,Any
],None
]) – When you configure application input at the time of creating or updating an application, provides additional mapping information specific to the record format (such as JSON, CSV, or record fields delimited by some delimiter) on the streaming source.
- Link
- ExampleMetadata
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. import aws_cdk.aws_kinesisanalytics as kinesisanalytics record_format_property = kinesisanalytics.CfnApplicationReferenceDataSourceV2.RecordFormatProperty( record_format_type="recordFormatType", # the properties below are optional mapping_parameters=kinesisanalytics.CfnApplicationReferenceDataSourceV2.MappingParametersProperty( csv_mapping_parameters=kinesisanalytics.CfnApplicationReferenceDataSourceV2.CSVMappingParametersProperty( record_column_delimiter="recordColumnDelimiter", record_row_delimiter="recordRowDelimiter" ), json_mapping_parameters=kinesisanalytics.CfnApplicationReferenceDataSourceV2.JSONMappingParametersProperty( record_row_path="recordRowPath" ) ) )
Attributes
- mapping_parameters
When you configure application input at the time of creating or updating an application, provides additional mapping information specific to the record format (such as JSON, CSV, or record fields delimited by some delimiter) on the streaming source.
ReferenceDataSourceProperty
- class CfnApplicationReferenceDataSourceV2.ReferenceDataSourceProperty(*, reference_schema, s3_reference_data_source=None, table_name=None)
Bases:
object
For a SQL-based Kinesis Data Analytics application, describes the reference data source by providing the source information (Amazon S3 bucket name and object key name), the resulting in-application table name that is created, and the necessary schema to map the data elements in the Amazon S3 object to the in-application table.
- Parameters
reference_schema (
Union
[IResolvable
,ReferenceSchemaProperty
,Dict
[str
,Any
]]) – Describes the format of the data in the streaming source, and how each data element maps to corresponding columns created in the in-application stream.s3_reference_data_source (
Union
[IResolvable
,S3ReferenceDataSourceProperty
,Dict
[str
,Any
],None
]) – Identifies the S3 bucket and object that contains the reference data. A Kinesis Data Analytics application loads reference data only once. If the data changes, you call the UpdateApplication operation to trigger reloading of data into your application.table_name (
Optional
[str
]) – The name of the in-application table to create.
- Link
- ExampleMetadata
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. import aws_cdk.aws_kinesisanalytics as kinesisanalytics reference_data_source_property = kinesisanalytics.CfnApplicationReferenceDataSourceV2.ReferenceDataSourceProperty( reference_schema=kinesisanalytics.CfnApplicationReferenceDataSourceV2.ReferenceSchemaProperty( record_columns=[kinesisanalytics.CfnApplicationReferenceDataSourceV2.RecordColumnProperty( name="name", sql_type="sqlType", # the properties below are optional mapping="mapping" )], record_format=kinesisanalytics.CfnApplicationReferenceDataSourceV2.RecordFormatProperty( record_format_type="recordFormatType", # the properties below are optional mapping_parameters=kinesisanalytics.CfnApplicationReferenceDataSourceV2.MappingParametersProperty( csv_mapping_parameters=kinesisanalytics.CfnApplicationReferenceDataSourceV2.CSVMappingParametersProperty( record_column_delimiter="recordColumnDelimiter", record_row_delimiter="recordRowDelimiter" ), json_mapping_parameters=kinesisanalytics.CfnApplicationReferenceDataSourceV2.JSONMappingParametersProperty( record_row_path="recordRowPath" ) ) ), # the properties below are optional record_encoding="recordEncoding" ), # the properties below are optional s3_reference_data_source=kinesisanalytics.CfnApplicationReferenceDataSourceV2.S3ReferenceDataSourceProperty( bucket_arn="bucketArn", file_key="fileKey" ), table_name="tableName" )
Attributes
- reference_schema
Describes the format of the data in the streaming source, and how each data element maps to corresponding columns created in the in-application stream.
- s3_reference_data_source
Identifies the S3 bucket and object that contains the reference data.
A Kinesis Data Analytics application loads reference data only once. If the data changes, you call the UpdateApplication operation to trigger reloading of data into your application.
- table_name
The name of the in-application table to create.
ReferenceSchemaProperty
- class CfnApplicationReferenceDataSourceV2.ReferenceSchemaProperty(*, record_columns, record_format, record_encoding=None)
Bases:
object
For a SQL-based Kinesis Data Analytics application, describes the format of the data in the streaming source, and how each data element maps to corresponding columns created in the in-application stream.
- Parameters
record_columns (
Union
[IResolvable
,Sequence
[Union
[IResolvable
,RecordColumnProperty
,Dict
[str
,Any
]]]]) – A list ofRecordColumn
objects.record_format (
Union
[IResolvable
,RecordFormatProperty
,Dict
[str
,Any
]]) – Specifies the format of the records on the streaming source.record_encoding (
Optional
[str
]) – Specifies the encoding of the records in the streaming source. For example, UTF-8.
- Link
- ExampleMetadata
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. import aws_cdk.aws_kinesisanalytics as kinesisanalytics reference_schema_property = kinesisanalytics.CfnApplicationReferenceDataSourceV2.ReferenceSchemaProperty( record_columns=[kinesisanalytics.CfnApplicationReferenceDataSourceV2.RecordColumnProperty( name="name", sql_type="sqlType", # the properties below are optional mapping="mapping" )], record_format=kinesisanalytics.CfnApplicationReferenceDataSourceV2.RecordFormatProperty( record_format_type="recordFormatType", # the properties below are optional mapping_parameters=kinesisanalytics.CfnApplicationReferenceDataSourceV2.MappingParametersProperty( csv_mapping_parameters=kinesisanalytics.CfnApplicationReferenceDataSourceV2.CSVMappingParametersProperty( record_column_delimiter="recordColumnDelimiter", record_row_delimiter="recordRowDelimiter" ), json_mapping_parameters=kinesisanalytics.CfnApplicationReferenceDataSourceV2.JSONMappingParametersProperty( record_row_path="recordRowPath" ) ) ), # the properties below are optional record_encoding="recordEncoding" )
Attributes
- record_columns
A list of
RecordColumn
objects.
- record_encoding
Specifies the encoding of the records in the streaming source.
For example, UTF-8.
- record_format
Specifies the format of the records on the streaming source.
S3ReferenceDataSourceProperty
- class CfnApplicationReferenceDataSourceV2.S3ReferenceDataSourceProperty(*, bucket_arn, file_key)
Bases:
object
For an SQL-based Amazon Kinesis Data Analytics application, identifies the Amazon S3 bucket and object that contains the reference data.
A Kinesis Data Analytics application loads reference data only once. If the data changes, you call the UpdateApplication operation to trigger reloading of data into your application.
- Parameters
bucket_arn (
str
) – The Amazon Resource Name (ARN) of the S3 bucket.file_key (
str
) – The object key name containing the reference data.
- Link
- ExampleMetadata
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. import aws_cdk.aws_kinesisanalytics as kinesisanalytics s3_reference_data_source_property = kinesisanalytics.CfnApplicationReferenceDataSourceV2.S3ReferenceDataSourceProperty( bucket_arn="bucketArn", file_key="fileKey" )
Attributes
- bucket_arn
The Amazon Resource Name (ARN) of the S3 bucket.
- file_key
The object key name containing the reference data.