CfnDataset
- class aws_cdk.aws_iotanalytics.CfnDataset(scope, id, *, actions, content_delivery_rules=None, dataset_name=None, late_data_rules=None, retention_period=None, tags=None, triggers=None, versioning_configuration=None)
Bases:
CfnResource
A CloudFormation
AWS::IoTAnalytics::Dataset
.The AWS::IoTAnalytics::Dataset resource stores data retrieved from a data store by applying a
queryAction
(an SQL query) or acontainerAction
(executing a containerized application). The data set can be populated manually by callingCreateDatasetContent
or automatically according to atrigger
you specify. For more information, see How to Use AWS IoT Analytics in the AWS IoT Analytics User Guide .- CloudformationResource:
AWS::IoTAnalytics::Dataset
- Link:
http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-iotanalytics-dataset.html
- 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_iotanalytics as iotanalytics cfn_dataset = iotanalytics.CfnDataset(self, "MyCfnDataset", actions=[iotanalytics.CfnDataset.ActionProperty( action_name="actionName", # the properties below are optional container_action=iotanalytics.CfnDataset.ContainerActionProperty( execution_role_arn="executionRoleArn", image="image", resource_configuration=iotanalytics.CfnDataset.ResourceConfigurationProperty( compute_type="computeType", volume_size_in_gb=123 ), # the properties below are optional variables=[iotanalytics.CfnDataset.VariableProperty( variable_name="variableName", # the properties below are optional dataset_content_version_value=iotanalytics.CfnDataset.DatasetContentVersionValueProperty( dataset_name="datasetName" ), double_value=123, output_file_uri_value=iotanalytics.CfnDataset.OutputFileUriValueProperty( file_name="fileName" ), string_value="stringValue" )] ), query_action=iotanalytics.CfnDataset.QueryActionProperty( sql_query="sqlQuery", # the properties below are optional filters=[iotanalytics.CfnDataset.FilterProperty( delta_time=iotanalytics.CfnDataset.DeltaTimeProperty( offset_seconds=123, time_expression="timeExpression" ) )] ) )], # the properties below are optional content_delivery_rules=[iotanalytics.CfnDataset.DatasetContentDeliveryRuleProperty( destination=iotanalytics.CfnDataset.DatasetContentDeliveryRuleDestinationProperty( iot_events_destination_configuration=iotanalytics.CfnDataset.IotEventsDestinationConfigurationProperty( input_name="inputName", role_arn="roleArn" ), s3_destination_configuration=iotanalytics.CfnDataset.S3DestinationConfigurationProperty( bucket="bucket", key="key", role_arn="roleArn", # the properties below are optional glue_configuration=iotanalytics.CfnDataset.GlueConfigurationProperty( database_name="databaseName", table_name="tableName" ) ) ), # the properties below are optional entry_name="entryName" )], dataset_name="datasetName", late_data_rules=[iotanalytics.CfnDataset.LateDataRuleProperty( rule_configuration=iotanalytics.CfnDataset.LateDataRuleConfigurationProperty( delta_time_session_window_configuration=iotanalytics.CfnDataset.DeltaTimeSessionWindowConfigurationProperty( timeout_in_minutes=123 ) ), # the properties below are optional rule_name="ruleName" )], retention_period=iotanalytics.CfnDataset.RetentionPeriodProperty( number_of_days=123, unlimited=False ), tags=[CfnTag( key="key", value="value" )], triggers=[iotanalytics.CfnDataset.TriggerProperty( schedule=iotanalytics.CfnDataset.ScheduleProperty( schedule_expression="scheduleExpression" ), triggering_dataset=iotanalytics.CfnDataset.TriggeringDatasetProperty( dataset_name="datasetName" ) )], versioning_configuration=iotanalytics.CfnDataset.VersioningConfigurationProperty( max_versions=123, unlimited=False ) )
Create a new
AWS::IoTAnalytics::Dataset
.- Parameters:
scope (
Construct
) –scope in which this resource is defined.
id (
str
) –scoped id of the resource.
actions (
Union
[IResolvable
,Sequence
[Union
[IResolvable
,ActionProperty
,Dict
[str
,Any
]]]]) – TheDatasetAction
objects that automatically create the dataset contents.content_delivery_rules (
Union
[IResolvable
,Sequence
[Union
[IResolvable
,DatasetContentDeliveryRuleProperty
,Dict
[str
,Any
]]],None
]) – When dataset contents are created they are delivered to destinations specified here.dataset_name (
Optional
[str
]) – The name of the dataset.late_data_rules (
Union
[IResolvable
,Sequence
[Union
[IResolvable
,LateDataRuleProperty
,Dict
[str
,Any
]]],None
]) – A list of data rules that send notifications to CloudWatch, when data arrives late. To specifylateDataRules
, the dataset must use a DeltaTimer filter.retention_period (
Union
[IResolvable
,RetentionPeriodProperty
,Dict
[str
,Any
],None
]) – Optional. How long, in days, message data is kept for the dataset.tags (
Optional
[Sequence
[Union
[CfnTag
,Dict
[str
,Any
]]]]) – Metadata which can be used to manage the data set. For more information, see Tag .triggers (
Union
[IResolvable
,Sequence
[Union
[IResolvable
,TriggerProperty
,Dict
[str
,Any
]]],None
]) – TheDatasetTrigger
objects that specify when the dataset is automatically updated.versioning_configuration (
Union
[IResolvable
,VersioningConfigurationProperty
,Dict
[str
,Any
],None
]) – Optional. How many versions of dataset contents are kept. If not specified or set to null, only the latest version plus the latest succeeded version (if they are different) are kept for the time period specified by theretentionPeriod
parameter. For more information, see Keeping Multiple Versions of AWS IoT Analytics datasets in the AWS IoT Analytics User Guide .
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
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
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::IoTAnalytics::Dataset'
- actions
The
DatasetAction
objects that automatically create the dataset contents.
- attr_id
Id
- Type:
cloudformationAttribute
- cfn_options
Options for this resource, such as condition, update policy etc.
- cfn_resource_type
AWS resource type.
- content_delivery_rules
When dataset contents are created they are delivered to destinations specified here.
- 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.
- dataset_name
The name of the dataset.
- late_data_rules
A list of data rules that send notifications to CloudWatch, when data arrives late.
To specify
lateDataRules
, the dataset must use a DeltaTimer filter.
- 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 })
.
- retention_period
Optional.
How long, in days, message data is kept for the dataset.
- stack
The stack in which this element is defined.
CfnElements must be defined within a stack scope (directly or indirectly).
- triggers
The
DatasetTrigger
objects that specify when the dataset is automatically updated.
- versioning_configuration
Optional.
How many versions of dataset contents are kept. If not specified or set to null, only the latest version plus the latest succeeded version (if they are different) are kept for the time period specified by the
retentionPeriod
parameter. For more information, see Keeping Multiple Versions of AWS IoT Analytics datasets in the AWS IoT Analytics User Guide .
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
ActionProperty
- class CfnDataset.ActionProperty(*, action_name, container_action=None, query_action=None)
Bases:
object
Information needed to run the “containerAction” to produce data set contents.
- Parameters:
action_name (
str
) – The name of the data set action by which data set contents are automatically created.container_action (
Union
[IResolvable
,ContainerActionProperty
,Dict
[str
,Any
],None
]) – Information which allows the system to run a containerized application in order to create the data set contents. The application must be in a Docker container along with any needed support libraries.query_action (
Union
[IResolvable
,QueryActionProperty
,Dict
[str
,Any
],None
]) – An “SqlQueryDatasetAction” object that uses an SQL query to automatically create data set contents.
- 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_iotanalytics as iotanalytics action_property = iotanalytics.CfnDataset.ActionProperty( action_name="actionName", # the properties below are optional container_action=iotanalytics.CfnDataset.ContainerActionProperty( execution_role_arn="executionRoleArn", image="image", resource_configuration=iotanalytics.CfnDataset.ResourceConfigurationProperty( compute_type="computeType", volume_size_in_gb=123 ), # the properties below are optional variables=[iotanalytics.CfnDataset.VariableProperty( variable_name="variableName", # the properties below are optional dataset_content_version_value=iotanalytics.CfnDataset.DatasetContentVersionValueProperty( dataset_name="datasetName" ), double_value=123, output_file_uri_value=iotanalytics.CfnDataset.OutputFileUriValueProperty( file_name="fileName" ), string_value="stringValue" )] ), query_action=iotanalytics.CfnDataset.QueryActionProperty( sql_query="sqlQuery", # the properties below are optional filters=[iotanalytics.CfnDataset.FilterProperty( delta_time=iotanalytics.CfnDataset.DeltaTimeProperty( offset_seconds=123, time_expression="timeExpression" ) )] ) )
Attributes
- action_name
The name of the data set action by which data set contents are automatically created.
- container_action
Information which allows the system to run a containerized application in order to create the data set contents.
The application must be in a Docker container along with any needed support libraries.
- query_action
An “SqlQueryDatasetAction” object that uses an SQL query to automatically create data set contents.
ContainerActionProperty
- class CfnDataset.ContainerActionProperty(*, execution_role_arn, image, resource_configuration, variables=None)
Bases:
object
Information needed to run the “containerAction” to produce data set contents.
- Parameters:
execution_role_arn (
str
) – The ARN of the role which gives permission to the system to access needed resources in order to run the “containerAction”. This includes, at minimum, permission to retrieve the data set contents which are the input to the containerized application.image (
str
) – The ARN of the Docker container stored in your account. The Docker container contains an application and needed support libraries and is used to generate data set contents.resource_configuration (
Union
[IResolvable
,ResourceConfigurationProperty
,Dict
[str
,Any
]]) – Configuration of the resource which executes the “containerAction”.variables (
Union
[IResolvable
,Sequence
[Union
[IResolvable
,VariableProperty
,Dict
[str
,Any
]]],None
]) – The values of variables used within the context of the execution of the containerized application (basically, parameters passed to the application). Each variable must have a name and a value given by one of “stringValue”, “datasetContentVersionValue”, or “outputFileUriValue”.
- 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_iotanalytics as iotanalytics container_action_property = iotanalytics.CfnDataset.ContainerActionProperty( execution_role_arn="executionRoleArn", image="image", resource_configuration=iotanalytics.CfnDataset.ResourceConfigurationProperty( compute_type="computeType", volume_size_in_gb=123 ), # the properties below are optional variables=[iotanalytics.CfnDataset.VariableProperty( variable_name="variableName", # the properties below are optional dataset_content_version_value=iotanalytics.CfnDataset.DatasetContentVersionValueProperty( dataset_name="datasetName" ), double_value=123, output_file_uri_value=iotanalytics.CfnDataset.OutputFileUriValueProperty( file_name="fileName" ), string_value="stringValue" )] )
Attributes
- execution_role_arn
The ARN of the role which gives permission to the system to access needed resources in order to run the “containerAction”.
This includes, at minimum, permission to retrieve the data set contents which are the input to the containerized application.
- image
The ARN of the Docker container stored in your account.
The Docker container contains an application and needed support libraries and is used to generate data set contents.
- resource_configuration
Configuration of the resource which executes the “containerAction”.
- variables
The values of variables used within the context of the execution of the containerized application (basically, parameters passed to the application).
Each variable must have a name and a value given by one of “stringValue”, “datasetContentVersionValue”, or “outputFileUriValue”.
DatasetContentDeliveryRuleDestinationProperty
- class CfnDataset.DatasetContentDeliveryRuleDestinationProperty(*, iot_events_destination_configuration=None, s3_destination_configuration=None)
Bases:
object
The destination to which dataset contents are delivered.
- Parameters:
iot_events_destination_configuration (
Union
[IResolvable
,IotEventsDestinationConfigurationProperty
,Dict
[str
,Any
],None
]) – Configuration information for delivery of dataset contents to AWS IoT Events .s3_destination_configuration (
Union
[IResolvable
,S3DestinationConfigurationProperty
,Dict
[str
,Any
],None
]) – Configuration information for delivery of dataset contents to Amazon S3.
- 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_iotanalytics as iotanalytics dataset_content_delivery_rule_destination_property = iotanalytics.CfnDataset.DatasetContentDeliveryRuleDestinationProperty( iot_events_destination_configuration=iotanalytics.CfnDataset.IotEventsDestinationConfigurationProperty( input_name="inputName", role_arn="roleArn" ), s3_destination_configuration=iotanalytics.CfnDataset.S3DestinationConfigurationProperty( bucket="bucket", key="key", role_arn="roleArn", # the properties below are optional glue_configuration=iotanalytics.CfnDataset.GlueConfigurationProperty( database_name="databaseName", table_name="tableName" ) ) )
Attributes
- iot_events_destination_configuration
Configuration information for delivery of dataset contents to AWS IoT Events .
- s3_destination_configuration
Configuration information for delivery of dataset contents to Amazon S3.
DatasetContentDeliveryRuleProperty
- class CfnDataset.DatasetContentDeliveryRuleProperty(*, destination, entry_name=None)
Bases:
object
When dataset contents are created, they are delivered to destination specified here.
- Parameters:
destination (
Union
[IResolvable
,DatasetContentDeliveryRuleDestinationProperty
,Dict
[str
,Any
]]) – The destination to which dataset contents are delivered.entry_name (
Optional
[str
]) – The name of the dataset content delivery rules entry.
- 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_iotanalytics as iotanalytics dataset_content_delivery_rule_property = iotanalytics.CfnDataset.DatasetContentDeliveryRuleProperty( destination=iotanalytics.CfnDataset.DatasetContentDeliveryRuleDestinationProperty( iot_events_destination_configuration=iotanalytics.CfnDataset.IotEventsDestinationConfigurationProperty( input_name="inputName", role_arn="roleArn" ), s3_destination_configuration=iotanalytics.CfnDataset.S3DestinationConfigurationProperty( bucket="bucket", key="key", role_arn="roleArn", # the properties below are optional glue_configuration=iotanalytics.CfnDataset.GlueConfigurationProperty( database_name="databaseName", table_name="tableName" ) ) ), # the properties below are optional entry_name="entryName" )
Attributes
- destination
The destination to which dataset contents are delivered.
- entry_name
The name of the dataset content delivery rules entry.
DatasetContentVersionValueProperty
- class CfnDataset.DatasetContentVersionValueProperty(*, dataset_name)
Bases:
object
The dataset whose latest contents are used as input to the notebook or application.
- Parameters:
dataset_name (
str
) – The name of the dataset whose latest contents are used as input to the notebook or application.- 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_iotanalytics as iotanalytics dataset_content_version_value_property = iotanalytics.CfnDataset.DatasetContentVersionValueProperty( dataset_name="datasetName" )
Attributes
- dataset_name
The name of the dataset whose latest contents are used as input to the notebook or application.
DeltaTimeProperty
- class CfnDataset.DeltaTimeProperty(*, offset_seconds, time_expression)
Bases:
object
Used to limit data to that which has arrived since the last execution of the action.
- Parameters:
offset_seconds (
Union
[int
,float
]) – The number of seconds of estimated in-flight lag time of message data. When you create dataset contents using message data from a specified timeframe, some message data might still be in flight when processing begins, and so do not arrive in time to be processed. Use this field to make allowances for the in flight time of your message data, so that data not processed from a previous timeframe is included with the next timeframe. Otherwise, missed message data would be excluded from processing during the next timeframe too, because its timestamp places it within the previous timeframe.time_expression (
str
) – An expression by which the time of the message data might be determined. This can be the name of a timestamp field or a SQL expression that is used to derive the time the message data was generated.
- 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_iotanalytics as iotanalytics delta_time_property = iotanalytics.CfnDataset.DeltaTimeProperty( offset_seconds=123, time_expression="timeExpression" )
Attributes
- offset_seconds
The number of seconds of estimated in-flight lag time of message data.
When you create dataset contents using message data from a specified timeframe, some message data might still be in flight when processing begins, and so do not arrive in time to be processed. Use this field to make allowances for the in flight time of your message data, so that data not processed from a previous timeframe is included with the next timeframe. Otherwise, missed message data would be excluded from processing during the next timeframe too, because its timestamp places it within the previous timeframe.
- time_expression
An expression by which the time of the message data might be determined.
This can be the name of a timestamp field or a SQL expression that is used to derive the time the message data was generated.
DeltaTimeSessionWindowConfigurationProperty
- class CfnDataset.DeltaTimeSessionWindowConfigurationProperty(*, timeout_in_minutes)
Bases:
object
A structure that contains the configuration information of a delta time session window.
`DeltaTime
<https://docs.aws.amazon.com/iotanalytics/latest/APIReference/API_DeltaTime.html>`_ specifies a time interval. You can useDeltaTime
to create dataset contents with data that has arrived in the data store since the last execution. For an example ofDeltaTime
, see Creating a SQL dataset with a delta window (CLI) in the AWS IoT Analytics User Guide .- Parameters:
timeout_in_minutes (
Union
[int
,float
]) – A time interval. You can usetimeoutInMinutes
so that AWS IoT Analytics can batch up late data notifications that have been generated since the last execution. AWS IoT Analytics sends one batch of notifications to Amazon CloudWatch Events at one time. For more information about how to write a timestamp expression, see Date and Time Functions and Operators , in the Presto 0.172 Documentation .- 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_iotanalytics as iotanalytics delta_time_session_window_configuration_property = iotanalytics.CfnDataset.DeltaTimeSessionWindowConfigurationProperty( timeout_in_minutes=123 )
Attributes
- timeout_in_minutes
A time interval.
You can use
timeoutInMinutes
so that AWS IoT Analytics can batch up late data notifications that have been generated since the last execution. AWS IoT Analytics sends one batch of notifications to Amazon CloudWatch Events at one time.For more information about how to write a timestamp expression, see Date and Time Functions and Operators , in the Presto 0.172 Documentation .
FilterProperty
- class CfnDataset.FilterProperty(*, delta_time=None)
Bases:
object
Information which is used to filter message data, to segregate it according to the time frame in which it arrives.
- Parameters:
delta_time (
Union
[IResolvable
,DeltaTimeProperty
,Dict
[str
,Any
],None
]) – Used to limit data to that which has arrived since the last execution of the action.- 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_iotanalytics as iotanalytics filter_property = iotanalytics.CfnDataset.FilterProperty( delta_time=iotanalytics.CfnDataset.DeltaTimeProperty( offset_seconds=123, time_expression="timeExpression" ) )
Attributes
- delta_time
Used to limit data to that which has arrived since the last execution of the action.
GlueConfigurationProperty
- class CfnDataset.GlueConfigurationProperty(*, database_name, table_name)
Bases:
object
Configuration information for coordination with AWS Glue , a fully managed extract, transform and load (ETL) service.
- Parameters:
database_name (
str
) – The name of the database in your AWS Glue Data Catalog in which the table is located. An AWS Glue Data Catalog database contains metadata tables.table_name (
str
) – The name of the table in your AWS Glue Data Catalog that is used to perform the ETL operations. An AWS Glue Data Catalog table contains partitioned data and descriptions of data sources and targets.
- 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_iotanalytics as iotanalytics glue_configuration_property = iotanalytics.CfnDataset.GlueConfigurationProperty( database_name="databaseName", table_name="tableName" )
Attributes
- database_name
The name of the database in your AWS Glue Data Catalog in which the table is located.
An AWS Glue Data Catalog database contains metadata tables.
- table_name
The name of the table in your AWS Glue Data Catalog that is used to perform the ETL operations.
An AWS Glue Data Catalog table contains partitioned data and descriptions of data sources and targets.
IotEventsDestinationConfigurationProperty
- class CfnDataset.IotEventsDestinationConfigurationProperty(*, input_name, role_arn)
Bases:
object
Configuration information for delivery of dataset contents to AWS IoT Events .
- Parameters:
input_name (
str
) – The name of the AWS IoT Events input to which dataset contents are delivered.role_arn (
str
) – The ARN of the role that grants AWS IoT Analytics permission to deliver dataset contents to an AWS IoT Events input.
- 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_iotanalytics as iotanalytics iot_events_destination_configuration_property = iotanalytics.CfnDataset.IotEventsDestinationConfigurationProperty( input_name="inputName", role_arn="roleArn" )
Attributes
- input_name
The name of the AWS IoT Events input to which dataset contents are delivered.
- role_arn
The ARN of the role that grants AWS IoT Analytics permission to deliver dataset contents to an AWS IoT Events input.
LateDataRuleConfigurationProperty
- class CfnDataset.LateDataRuleConfigurationProperty(*, delta_time_session_window_configuration=None)
Bases:
object
The information needed to configure a delta time session window.
- Parameters:
delta_time_session_window_configuration (
Union
[IResolvable
,DeltaTimeSessionWindowConfigurationProperty
,Dict
[str
,Any
],None
]) – The information needed to configure a delta time session window.- 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_iotanalytics as iotanalytics late_data_rule_configuration_property = iotanalytics.CfnDataset.LateDataRuleConfigurationProperty( delta_time_session_window_configuration=iotanalytics.CfnDataset.DeltaTimeSessionWindowConfigurationProperty( timeout_in_minutes=123 ) )
Attributes
- delta_time_session_window_configuration
The information needed to configure a delta time session window.
LateDataRuleProperty
- class CfnDataset.LateDataRuleProperty(*, rule_configuration, rule_name=None)
Bases:
object
A structure that contains the name and configuration information of a late data rule.
- Parameters:
rule_configuration (
Union
[IResolvable
,LateDataRuleConfigurationProperty
,Dict
[str
,Any
]]) – The information needed to configure the late data rule.rule_name (
Optional
[str
]) – The name of the late data rule.
- 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_iotanalytics as iotanalytics late_data_rule_property = iotanalytics.CfnDataset.LateDataRuleProperty( rule_configuration=iotanalytics.CfnDataset.LateDataRuleConfigurationProperty( delta_time_session_window_configuration=iotanalytics.CfnDataset.DeltaTimeSessionWindowConfigurationProperty( timeout_in_minutes=123 ) ), # the properties below are optional rule_name="ruleName" )
Attributes
- rule_configuration
The information needed to configure the late data rule.
- rule_name
The name of the late data rule.
OutputFileUriValueProperty
- class CfnDataset.OutputFileUriValueProperty(*, file_name)
Bases:
object
The value of the variable as a structure that specifies an output file URI.
- Parameters:
file_name (
str
) – The URI of the location where dataset contents are stored, usually the URI of a file in an S3 bucket.- 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_iotanalytics as iotanalytics output_file_uri_value_property = iotanalytics.CfnDataset.OutputFileUriValueProperty( file_name="fileName" )
Attributes
- file_name
The URI of the location where dataset contents are stored, usually the URI of a file in an S3 bucket.
QueryActionProperty
- class CfnDataset.QueryActionProperty(*, sql_query, filters=None)
Bases:
object
An “SqlQueryDatasetAction” object that uses an SQL query to automatically create data set contents.
- Parameters:
sql_query (
str
) – An “SqlQueryDatasetAction” object that uses an SQL query to automatically create data set contents.filters (
Union
[IResolvable
,Sequence
[Union
[IResolvable
,FilterProperty
,Dict
[str
,Any
]]],None
]) – Pre-filters applied to message 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_iotanalytics as iotanalytics query_action_property = iotanalytics.CfnDataset.QueryActionProperty( sql_query="sqlQuery", # the properties below are optional filters=[iotanalytics.CfnDataset.FilterProperty( delta_time=iotanalytics.CfnDataset.DeltaTimeProperty( offset_seconds=123, time_expression="timeExpression" ) )] )
Attributes
- filters
Pre-filters applied to message data.
- sql_query
An “SqlQueryDatasetAction” object that uses an SQL query to automatically create data set contents.
ResourceConfigurationProperty
- class CfnDataset.ResourceConfigurationProperty(*, compute_type, volume_size_in_gb)
Bases:
object
The configuration of the resource used to execute the
containerAction
.- Parameters:
compute_type (
str
) – The type of the compute resource used to execute thecontainerAction
. Possible values are:ACU_1
(vCPU=4, memory=16 GiB) orACU_2
(vCPU=8, memory=32 GiB).volume_size_in_gb (
Union
[int
,float
]) – The size, in GB, of the persistent storage available to the resource instance used to execute thecontainerAction
(min: 1, max: 50).
- 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_iotanalytics as iotanalytics resource_configuration_property = iotanalytics.CfnDataset.ResourceConfigurationProperty( compute_type="computeType", volume_size_in_gb=123 )
Attributes
- compute_type
The type of the compute resource used to execute the
containerAction
.Possible values are:
ACU_1
(vCPU=4, memory=16 GiB) orACU_2
(vCPU=8, memory=32 GiB).
- volume_size_in_gb
50).
- Link:
- Type:
The size, in GB, of the persistent storage available to the resource instance used to execute the
containerAction
(min- Type:
1, max
RetentionPeriodProperty
- class CfnDataset.RetentionPeriodProperty(*, number_of_days=None, unlimited=None)
Bases:
object
How long, in days, message data is kept.
- Parameters:
number_of_days (
Union
[int
,float
,None
]) – The number of days that message data is kept. Theunlimited
parameter must be false.unlimited (
Union
[bool
,IResolvable
,None
]) – If true, message data is kept indefinitely.
- 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_iotanalytics as iotanalytics retention_period_property = iotanalytics.CfnDataset.RetentionPeriodProperty( number_of_days=123, unlimited=False )
Attributes
- number_of_days
The number of days that message data is kept.
The
unlimited
parameter must be false.
- unlimited
If true, message data is kept indefinitely.
S3DestinationConfigurationProperty
- class CfnDataset.S3DestinationConfigurationProperty(*, bucket, key, role_arn, glue_configuration=None)
Bases:
object
Configuration information for delivery of dataset contents to Amazon Simple Storage Service (Amazon S3).
- Parameters:
bucket (
str
) – The name of the S3 bucket to which dataset contents are delivered.key (
str
) – The key of the dataset contents object in an S3 bucket. Each object has a key that is a unique identifier. Each object has exactly one key. You can create a unique key with the following options: - Use!{iotanalytics:scheduleTime}
to insert the time of a scheduled SQL query run. - Use!{iotanalytics:versionId}
to insert a unique hash that identifies a dataset content. - Use!{iotanalytics:creationTime}
to insert the creation time of a dataset content. The following example creates a unique key for a CSV file:dataset/mydataset/!{iotanalytics:scheduleTime}/!{iotanalytics:versionId}.csv
.. epigraph:: If you don’t use!{iotanalytics:versionId}
to specify the key, you might get duplicate keys. For example, you might have two dataset contents with the samescheduleTime
but differentversionId
s. This means that one dataset content overwrites the other.role_arn (
str
) – The ARN of the role that grants AWS IoT Analytics permission to interact with your Amazon S3 and AWS Glue resources.glue_configuration (
Union
[IResolvable
,GlueConfigurationProperty
,Dict
[str
,Any
],None
]) – Configuration information for coordination with AWS Glue , a fully managed extract, transform and load (ETL) service.
- 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_iotanalytics as iotanalytics s3_destination_configuration_property = iotanalytics.CfnDataset.S3DestinationConfigurationProperty( bucket="bucket", key="key", role_arn="roleArn", # the properties below are optional glue_configuration=iotanalytics.CfnDataset.GlueConfigurationProperty( database_name="databaseName", table_name="tableName" ) )
Attributes
- bucket
The name of the S3 bucket to which dataset contents are delivered.
- glue_configuration
Configuration information for coordination with AWS Glue , a fully managed extract, transform and load (ETL) service.
- key
The key of the dataset contents object in an S3 bucket.
Each object has a key that is a unique identifier. Each object has exactly one key.
You can create a unique key with the following options:
Use
!{iotanalytics:scheduleTime}
to insert the time of a scheduled SQL query run.Use
!{iotanalytics:versionId}
to insert a unique hash that identifies a dataset content.Use
!{iotanalytics:creationTime}
to insert the creation time of a dataset content.
The following example creates a unique key for a CSV file:
dataset/mydataset/!{iotanalytics:scheduleTime}/!{iotanalytics:versionId}.csv
.. epigraph:If you don't use ``!{iotanalytics:versionId}`` to specify the key, you might get duplicate keys. For example, you might have two dataset contents with the same ``scheduleTime`` but different ``versionId`` s. This means that one dataset content overwrites the other.
- role_arn
The ARN of the role that grants AWS IoT Analytics permission to interact with your Amazon S3 and AWS Glue resources.
ScheduleProperty
- class CfnDataset.ScheduleProperty(*, schedule_expression)
Bases:
object
The schedule for when to trigger an update.
- Parameters:
schedule_expression (
str
) – The expression that defines when to trigger an update. For more information, see Schedule Expressions for Rules in the Amazon CloudWatch documentation.- 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_iotanalytics as iotanalytics schedule_property = iotanalytics.CfnDataset.ScheduleProperty( schedule_expression="scheduleExpression" )
Attributes
- schedule_expression
The expression that defines when to trigger an update.
For more information, see Schedule Expressions for Rules in the Amazon CloudWatch documentation.
TriggerProperty
- class CfnDataset.TriggerProperty(*, schedule=None, triggering_dataset=None)
Bases:
object
The “DatasetTrigger” that specifies when the data set is automatically updated.
- Parameters:
schedule (
Union
[IResolvable
,ScheduleProperty
,Dict
[str
,Any
],None
]) – The “Schedule” when the trigger is initiated.triggering_dataset (
Union
[IResolvable
,TriggeringDatasetProperty
,Dict
[str
,Any
],None
]) – Information about the data set whose content generation triggers the new data set content generation.
- 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_iotanalytics as iotanalytics trigger_property = iotanalytics.CfnDataset.TriggerProperty( schedule=iotanalytics.CfnDataset.ScheduleProperty( schedule_expression="scheduleExpression" ), triggering_dataset=iotanalytics.CfnDataset.TriggeringDatasetProperty( dataset_name="datasetName" ) )
Attributes
- schedule
The “Schedule” when the trigger is initiated.
- triggering_dataset
Information about the data set whose content generation triggers the new data set content generation.
TriggeringDatasetProperty
- class CfnDataset.TriggeringDatasetProperty(*, dataset_name)
Bases:
object
Information about the dataset whose content generation triggers the new dataset content generation.
- Parameters:
dataset_name (
str
) – The name of the data set whose content generation triggers the new data set content generation.- 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_iotanalytics as iotanalytics triggering_dataset_property = iotanalytics.CfnDataset.TriggeringDatasetProperty( dataset_name="datasetName" )
Attributes
- dataset_name
The name of the data set whose content generation triggers the new data set content generation.
VariableProperty
- class CfnDataset.VariableProperty(*, variable_name, dataset_content_version_value=None, double_value=None, output_file_uri_value=None, string_value=None)
Bases:
object
An instance of a variable to be passed to the
containerAction
execution.Each variable must have a name and a value given by one of
stringValue
,datasetContentVersionValue
, oroutputFileUriValue
.- Parameters:
variable_name (
str
) – The name of the variable.dataset_content_version_value (
Union
[IResolvable
,DatasetContentVersionValueProperty
,Dict
[str
,Any
],None
]) – The value of the variable as a structure that specifies a dataset content version.double_value (
Union
[int
,float
,None
]) – The value of the variable as a double (numeric).output_file_uri_value (
Union
[IResolvable
,OutputFileUriValueProperty
,Dict
[str
,Any
],None
]) – The value of the variable as a structure that specifies an output file URI.string_value (
Optional
[str
]) – The value of the variable as a string.
- 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_iotanalytics as iotanalytics variable_property = iotanalytics.CfnDataset.VariableProperty( variable_name="variableName", # the properties below are optional dataset_content_version_value=iotanalytics.CfnDataset.DatasetContentVersionValueProperty( dataset_name="datasetName" ), double_value=123, output_file_uri_value=iotanalytics.CfnDataset.OutputFileUriValueProperty( file_name="fileName" ), string_value="stringValue" )
Attributes
- dataset_content_version_value
The value of the variable as a structure that specifies a dataset content version.
- double_value
The value of the variable as a double (numeric).
- output_file_uri_value
The value of the variable as a structure that specifies an output file URI.
- string_value
The value of the variable as a string.
- variable_name
The name of the variable.
VersioningConfigurationProperty
- class CfnDataset.VersioningConfigurationProperty(*, max_versions=None, unlimited=None)
Bases:
object
Information about the versioning of dataset contents.
- Parameters:
max_versions (
Union
[int
,float
,None
]) – How many versions of dataset contents are kept. Theunlimited
parameter must befalse
.unlimited (
Union
[bool
,IResolvable
,None
]) – If true, unlimited versions of dataset contents are kept.
- 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_iotanalytics as iotanalytics versioning_configuration_property = iotanalytics.CfnDataset.VersioningConfigurationProperty( max_versions=123, unlimited=False )
Attributes
- max_versions
How many versions of dataset contents are kept.
The
unlimited
parameter must befalse
.
- unlimited
If true, unlimited versions of dataset contents are kept.