Struct aws_sdk_kinesisanalyticsv2::types::builders::ParallelismConfigurationBuilder

#[non_exhaustive]
pub struct ParallelismConfigurationBuilder { /* private fields */ }

A builder for ParallelismConfiguration.

Implementations

impl ParallelismConfigurationBuilder

pub fn configuration_type(self, input: ConfigurationType) -> Self

Describes whether the application uses the default parallelism for the Kinesis Data Analytics service. You must set this property to CUSTOM in order to change your application's AutoScalingEnabled, Parallelism, or ParallelismPerKPU properties.

This field is required.

pub fn set_configuration_type(self, input: Option<ConfigurationType>) -> Self

Describes whether the application uses the default parallelism for the Kinesis Data Analytics service. You must set this property to CUSTOM in order to change your application's AutoScalingEnabled, Parallelism, or ParallelismPerKPU properties.

pub fn get_configuration_type(&self) -> &Option<ConfigurationType>

Describes whether the application uses the default parallelism for the Kinesis Data Analytics service. You must set this property to CUSTOM in order to change your application's AutoScalingEnabled, Parallelism, or ParallelismPerKPU properties.

pub fn parallelism(self, input: i32) -> Self

Describes the initial number of parallel tasks that a Flink-based Kinesis Data Analytics application can perform. If AutoScalingEnabled is set to True, Kinesis Data Analytics increases the CurrentParallelism value in response to application load. The service can increase the CurrentParallelism value up to the maximum parallelism, which is ParalellismPerKPU times the maximum KPUs for the application. The maximum KPUs for an application is 32 by default, and can be increased by requesting a limit increase. If application load is reduced, the service can reduce the CurrentParallelism value down to the Parallelism setting.

pub fn set_parallelism(self, input: Option<i32>) -> Self

Describes the initial number of parallel tasks that a Flink-based Kinesis Data Analytics application can perform. If AutoScalingEnabled is set to True, Kinesis Data Analytics increases the CurrentParallelism value in response to application load. The service can increase the CurrentParallelism value up to the maximum parallelism, which is ParalellismPerKPU times the maximum KPUs for the application. The maximum KPUs for an application is 32 by default, and can be increased by requesting a limit increase. If application load is reduced, the service can reduce the CurrentParallelism value down to the Parallelism setting.

pub fn get_parallelism(&self) -> &Option<i32>

Describes the initial number of parallel tasks that a Flink-based Kinesis Data Analytics application can perform. If AutoScalingEnabled is set to True, Kinesis Data Analytics increases the CurrentParallelism value in response to application load. The service can increase the CurrentParallelism value up to the maximum parallelism, which is ParalellismPerKPU times the maximum KPUs for the application. The maximum KPUs for an application is 32 by default, and can be increased by requesting a limit increase. If application load is reduced, the service can reduce the CurrentParallelism value down to the Parallelism setting.

pub fn parallelism_per_kpu(self, input: i32) -> Self

Describes the number of parallel tasks that a Flink-based Kinesis Data Analytics application can perform per Kinesis Processing Unit (KPU) used by the application. For more information about KPUs, see Amazon Kinesis Data Analytics Pricing.

pub fn set_parallelism_per_kpu(self, input: Option<i32>) -> Self

Describes the number of parallel tasks that a Flink-based Kinesis Data Analytics application can perform per Kinesis Processing Unit (KPU) used by the application. For more information about KPUs, see Amazon Kinesis Data Analytics Pricing.

pub fn get_parallelism_per_kpu(&self) -> &Option<i32>

Describes the number of parallel tasks that a Flink-based Kinesis Data Analytics application can perform per Kinesis Processing Unit (KPU) used by the application. For more information about KPUs, see Amazon Kinesis Data Analytics Pricing.

pub fn auto_scaling_enabled(self, input: bool) -> Self

Describes whether the Kinesis Data Analytics service can increase the parallelism of the application in response to increased throughput.

pub fn set_auto_scaling_enabled(self, input: Option<bool>) -> Self

Describes whether the Kinesis Data Analytics service can increase the parallelism of the application in response to increased throughput.

pub fn get_auto_scaling_enabled(&self) -> &Option<bool>

Describes whether the Kinesis Data Analytics service can increase the parallelism of the application in response to increased throughput.

pub fn build(self) -> Result<ParallelismConfiguration, BuildError>

Consumes the builder and constructs a ParallelismConfiguration. This method will fail if any of the following fields are not set:

• configuration_type

Trait Implementations

impl Clone for ParallelismConfigurationBuilder

fn clone(&self) -> ParallelismConfigurationBuilder

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for ParallelismConfigurationBuilder

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for ParallelismConfigurationBuilder

fn default() -> ParallelismConfigurationBuilder

Returns the “default value” for a type.

impl PartialEq for ParallelismConfigurationBuilder

fn eq(&self, other: &ParallelismConfigurationBuilder) -> bool

This method tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

This method tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl StructuralPartialEq for ParallelismConfigurationBuilder