CfnApplicationReferenceDataSource
- class aws_cdk.aws_kinesisanalyticsv2.CfnApplicationReferenceDataSource(scope, id, *, application_name, reference_data_source)
Bases:
CfnResource
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.
- See:
- CloudformationResource:
AWS::KinesisAnalyticsV2::ApplicationReferenceDataSource
- 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_kinesisanalyticsv2 as kinesisanalyticsv2 cfn_application_reference_data_source = kinesisanalyticsv2.CfnApplicationReferenceDataSource(self, "MyCfnApplicationReferenceDataSource", application_name="applicationName", reference_data_source=kinesisanalyticsv2.CfnApplicationReferenceDataSource.ReferenceDataSourceProperty( reference_schema=kinesisanalyticsv2.CfnApplicationReferenceDataSource.ReferenceSchemaProperty( record_columns=[kinesisanalyticsv2.CfnApplicationReferenceDataSource.RecordColumnProperty( name="name", sql_type="sqlType", # the properties below are optional mapping="mapping" )], record_format=kinesisanalyticsv2.CfnApplicationReferenceDataSource.RecordFormatProperty( record_format_type="recordFormatType", # the properties below are optional mapping_parameters=kinesisanalyticsv2.CfnApplicationReferenceDataSource.MappingParametersProperty( csv_mapping_parameters=kinesisanalyticsv2.CfnApplicationReferenceDataSource.CSVMappingParametersProperty( record_column_delimiter="recordColumnDelimiter", record_row_delimiter="recordRowDelimiter" ), json_mapping_parameters=kinesisanalyticsv2.CfnApplicationReferenceDataSource.JSONMappingParametersProperty( record_row_path="recordRowPath" ) ) ), # the properties below are optional record_encoding="recordEncoding" ), # the properties below are optional s3_reference_data_source=kinesisanalyticsv2.CfnApplicationReferenceDataSource.S3ReferenceDataSourceProperty( bucket_arn="bucketArn", file_key="fileKey" ), table_name="tableName" ) )
- Parameters:
scope (
Construct
) – Scope in which this resource is defined.id (
str
) – Construct identifier for this resource (unique in its scope).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_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::KinesisAnalyticsV2::ApplicationReferenceDataSource'
- application_name
The name of the application.
- attr_id
Id
- Type:
cloudformationAttribute
- 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 tree node.
- 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(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
.
CSVMappingParametersProperty
- class CfnApplicationReferenceDataSource.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.
- 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_kinesisanalyticsv2 as kinesisanalyticsv2 c_sVMapping_parameters_property = kinesisanalyticsv2.CfnApplicationReferenceDataSource.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 CfnApplicationReferenceDataSource.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.- 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_kinesisanalyticsv2 as kinesisanalyticsv2 j_sONMapping_parameters_property = kinesisanalyticsv2.CfnApplicationReferenceDataSource.JSONMappingParametersProperty( record_row_path="recordRowPath" )
Attributes
- record_row_path
The path to the top-level parent that contains the records.
MappingParametersProperty
- class CfnApplicationReferenceDataSource.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.
- 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_kinesisanalyticsv2 as kinesisanalyticsv2 mapping_parameters_property = kinesisanalyticsv2.CfnApplicationReferenceDataSource.MappingParametersProperty( csv_mapping_parameters=kinesisanalyticsv2.CfnApplicationReferenceDataSource.CSVMappingParametersProperty( record_column_delimiter="recordColumnDelimiter", record_row_delimiter="recordRowDelimiter" ), json_mapping_parameters=kinesisanalyticsv2.CfnApplicationReferenceDataSource.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 CfnApplicationReferenceDataSource.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.
- 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_kinesisanalyticsv2 as kinesisanalyticsv2 record_column_property = kinesisanalyticsv2.CfnApplicationReferenceDataSource.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 CfnApplicationReferenceDataSource.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.
- 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_kinesisanalyticsv2 as kinesisanalyticsv2 record_format_property = kinesisanalyticsv2.CfnApplicationReferenceDataSource.RecordFormatProperty( record_format_type="recordFormatType", # the properties below are optional mapping_parameters=kinesisanalyticsv2.CfnApplicationReferenceDataSource.MappingParametersProperty( csv_mapping_parameters=kinesisanalyticsv2.CfnApplicationReferenceDataSource.CSVMappingParametersProperty( record_column_delimiter="recordColumnDelimiter", record_row_delimiter="recordRowDelimiter" ), json_mapping_parameters=kinesisanalyticsv2.CfnApplicationReferenceDataSource.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 CfnApplicationReferenceDataSource.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.
- 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_kinesisanalyticsv2 as kinesisanalyticsv2 reference_data_source_property = kinesisanalyticsv2.CfnApplicationReferenceDataSource.ReferenceDataSourceProperty( reference_schema=kinesisanalyticsv2.CfnApplicationReferenceDataSource.ReferenceSchemaProperty( record_columns=[kinesisanalyticsv2.CfnApplicationReferenceDataSource.RecordColumnProperty( name="name", sql_type="sqlType", # the properties below are optional mapping="mapping" )], record_format=kinesisanalyticsv2.CfnApplicationReferenceDataSource.RecordFormatProperty( record_format_type="recordFormatType", # the properties below are optional mapping_parameters=kinesisanalyticsv2.CfnApplicationReferenceDataSource.MappingParametersProperty( csv_mapping_parameters=kinesisanalyticsv2.CfnApplicationReferenceDataSource.CSVMappingParametersProperty( record_column_delimiter="recordColumnDelimiter", record_row_delimiter="recordRowDelimiter" ), json_mapping_parameters=kinesisanalyticsv2.CfnApplicationReferenceDataSource.JSONMappingParametersProperty( record_row_path="recordRowPath" ) ) ), # the properties below are optional record_encoding="recordEncoding" ), # the properties below are optional s3_reference_data_source=kinesisanalyticsv2.CfnApplicationReferenceDataSource.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 CfnApplicationReferenceDataSource.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.
- 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_kinesisanalyticsv2 as kinesisanalyticsv2 reference_schema_property = kinesisanalyticsv2.CfnApplicationReferenceDataSource.ReferenceSchemaProperty( record_columns=[kinesisanalyticsv2.CfnApplicationReferenceDataSource.RecordColumnProperty( name="name", sql_type="sqlType", # the properties below are optional mapping="mapping" )], record_format=kinesisanalyticsv2.CfnApplicationReferenceDataSource.RecordFormatProperty( record_format_type="recordFormatType", # the properties below are optional mapping_parameters=kinesisanalyticsv2.CfnApplicationReferenceDataSource.MappingParametersProperty( csv_mapping_parameters=kinesisanalyticsv2.CfnApplicationReferenceDataSource.CSVMappingParametersProperty( record_column_delimiter="recordColumnDelimiter", record_row_delimiter="recordRowDelimiter" ), json_mapping_parameters=kinesisanalyticsv2.CfnApplicationReferenceDataSource.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 CfnApplicationReferenceDataSource.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.
- 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_kinesisanalyticsv2 as kinesisanalyticsv2 s3_reference_data_source_property = kinesisanalyticsv2.CfnApplicationReferenceDataSource.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.