CfnRefreshSchedule
- class aws_cdk.aws_quicksight.CfnRefreshSchedule(scope, id, *, aws_account_id=None, data_set_id=None, schedule=None)
Bases:
CfnResource
A CloudFormation
AWS::QuickSight::RefreshSchedule
.Creates a refresh schedule for a dataset in Amazon QuickSight .
- CloudformationResource:
AWS::QuickSight::RefreshSchedule
- 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_quicksight as quicksight cfn_refresh_schedule = quicksight.CfnRefreshSchedule(self, "MyCfnRefreshSchedule", aws_account_id="awsAccountId", data_set_id="dataSetId", schedule=quicksight.CfnRefreshSchedule.RefreshScheduleMapProperty( refresh_type="refreshType", schedule_frequency=quicksight.CfnRefreshSchedule.ScheduleFrequencyProperty( interval="interval", refresh_on_day=quicksight.CfnRefreshSchedule.RefreshOnDayProperty( day_of_month="dayOfMonth", day_of_week="dayOfWeek" ), time_of_the_day="timeOfTheDay", time_zone="timeZone" ), schedule_id="scheduleId", start_after_date_time="startAfterDateTime" ) )
Create a new
AWS::QuickSight::RefreshSchedule
.- Parameters:
scope (
Construct
) –scope in which this resource is defined.
id (
str
) –scoped id of the resource.
aws_account_id (
Optional
[str
]) – The AWS account ID of the account that you are creating a schedule in.data_set_id (
Optional
[str
]) – The ID of the dataset that you are creating a refresh schedule for.schedule (
Union
[IResolvable
,RefreshScheduleMapProperty
,Dict
[str
,Any
],None
]) – The refresh schedule of a dataset.
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::QuickSight::RefreshSchedule'
- attr_arn
The Amazon Resource Name (ARN) for the refresh schedule.
- CloudformationAttribute:
Arn
- aws_account_id
The AWS account ID of the account that you are creating a schedule in.
- 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.
- data_set_id
The ID of the dataset that you are creating a refresh schedule for.
- 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 })
.
- schedule
The refresh schedule of a dataset.
- 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
RefreshOnDayProperty
- class CfnRefreshSchedule.RefreshOnDayProperty(*, day_of_month=None, day_of_week=None)
Bases:
object
The day that you want yout dataset to refresh.
- Parameters:
day_of_month (
Optional
[str
]) – The day of the month that you want your dataset to refresh. This value is required for monthly refresh intervals.day_of_week (
Optional
[str
]) – The day of the week that you want to schedule the refresh on. This value is required for weekly and monthly refresh intervals.
- 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_quicksight as quicksight refresh_on_day_property = quicksight.CfnRefreshSchedule.RefreshOnDayProperty( day_of_month="dayOfMonth", day_of_week="dayOfWeek" )
Attributes
- day_of_month
The day of the month that you want your dataset to refresh.
This value is required for monthly refresh intervals.
- day_of_week
The day of the week that you want to schedule the refresh on.
This value is required for weekly and monthly refresh intervals.
RefreshScheduleMapProperty
- class CfnRefreshSchedule.RefreshScheduleMapProperty(*, refresh_type=None, schedule_frequency=None, schedule_id=None, start_after_date_time=None)
Bases:
object
A summary of a configured refresh schedule for a dataset.
- Parameters:
refresh_type (
Optional
[str
]) – The type of refresh that a dataset undergoes. Valid values are as follows:. -FULL_REFRESH
: A complete refresh of a dataset. -INCREMENTAL_REFRESH
: A partial refresh of some rows of a dataset, based on the time window specified. For more information on full and incremental refreshes, see Refreshing SPICE data in the Amazon QuickSight User Guide .schedule_frequency (
Union
[IResolvable
,ScheduleFrequencyProperty
,Dict
[str
,Any
],None
]) – The frequency for the refresh schedule.schedule_id (
Optional
[str
]) – An identifier for the refresh schedule.start_after_date_time (
Optional
[str
]) – Time after which the refresh schedule can be started, expressed inYYYY-MM-DDTHH:MM:SS
format.
- 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_quicksight as quicksight refresh_schedule_map_property = quicksight.CfnRefreshSchedule.RefreshScheduleMapProperty( refresh_type="refreshType", schedule_frequency=quicksight.CfnRefreshSchedule.ScheduleFrequencyProperty( interval="interval", refresh_on_day=quicksight.CfnRefreshSchedule.RefreshOnDayProperty( day_of_month="dayOfMonth", day_of_week="dayOfWeek" ), time_of_the_day="timeOfTheDay", time_zone="timeZone" ), schedule_id="scheduleId", start_after_date_time="startAfterDateTime" )
Attributes
- refresh_type
.
FULL_REFRESH
: A complete refresh of a dataset.INCREMENTAL_REFRESH
: A partial refresh of some rows of a dataset, based on the time window specified.
For more information on full and incremental refreshes, see Refreshing SPICE data in the Amazon QuickSight User Guide .
- Link:
- Type:
The type of refresh that a dataset undergoes. Valid values are as follows
- schedule_frequency
The frequency for the refresh schedule.
- schedule_id
An identifier for the refresh schedule.
- start_after_date_time
Time after which the refresh schedule can be started, expressed in
YYYY-MM-DDTHH:MM:SS
format.
ScheduleFrequencyProperty
- class CfnRefreshSchedule.ScheduleFrequencyProperty(*, interval=None, refresh_on_day=None, time_of_the_day=None, time_zone=None)
Bases:
object
The frequency for the refresh schedule.
- Parameters:
interval (
Optional
[str
]) – The interval between scheduled refreshes. Valid values are as follows:. -MINUTE15
: The dataset refreshes every 15 minutes. This value is only supported for incremental refreshes. This interval can only be used for one schedule per dataset. -MINUTE30
: The dataset refreshes every 30 minutes. This value is only supported for incremental refreshes. This interval can only be used for one schedule per dataset. -HOURLY
: The dataset refreshes every hour. This interval can only be used for one schedule per dataset. -DAILY
: The dataset refreshes every day. -WEEKLY
: The dataset refreshes every week. -MONTHLY
: The dataset refreshes every month.refresh_on_day (
Union
[IResolvable
,RefreshOnDayProperty
,Dict
[str
,Any
],None
]) – The day of the week that you want to schedule the refresh on. This value is required for weekly and monthly refresh intervals.time_of_the_day (
Optional
[str
]) – The time of day that you want the dataset to refresh. This value is expressed in HH:MM format. This field is not required for schedules that refresh hourly.time_zone (
Optional
[str
]) – The timezone that you want the refresh schedule to use. The timezone ID must match a corresponding ID found onjava.util.time.getAvailableIDs()
.
- 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_quicksight as quicksight schedule_frequency_property = quicksight.CfnRefreshSchedule.ScheduleFrequencyProperty( interval="interval", refresh_on_day=quicksight.CfnRefreshSchedule.RefreshOnDayProperty( day_of_month="dayOfMonth", day_of_week="dayOfWeek" ), time_of_the_day="timeOfTheDay", time_zone="timeZone" )
Attributes
- interval
.
MINUTE15
: The dataset refreshes every 15 minutes. This value is only supported for incremental refreshes. This interval can only be used for one schedule per dataset.MINUTE30
: The dataset refreshes every 30 minutes. This value is only supported for incremental refreshes. This interval can only be used for one schedule per dataset.HOURLY
: The dataset refreshes every hour. This interval can only be used for one schedule per dataset.DAILY
: The dataset refreshes every day.WEEKLY
: The dataset refreshes every week.MONTHLY
: The dataset refreshes every month.
- Link:
- Type:
The interval between scheduled refreshes. Valid values are as follows
- refresh_on_day
The day of the week that you want to schedule the refresh on.
This value is required for weekly and monthly refresh intervals.
- time_of_the_day
The time of day that you want the dataset to refresh.
This value is expressed in HH:MM format. This field is not required for schedules that refresh hourly.
- time_zone
The timezone that you want the refresh schedule to use.
The timezone ID must match a corresponding ID found on
java.util.time.getAvailableIDs()
.