aws_sdk_lightsail::operation::get_relational_database_metric_data::builders

Struct GetRelationalDatabaseMetricDataInputBuilder

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#[non_exhaustive]
pub struct GetRelationalDatabaseMetricDataInputBuilder { /* private fields */ }
Expand description

A builder for GetRelationalDatabaseMetricDataInput.

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impl GetRelationalDatabaseMetricDataInputBuilder

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pub fn relational_database_name(self, input: impl Into<String>) -> Self

The name of your database from which to get metric data.

This field is required.
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pub fn set_relational_database_name(self, input: Option<String>) -> Self

The name of your database from which to get metric data.

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pub fn get_relational_database_name(&self) -> &Option<String>

The name of your database from which to get metric data.

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pub fn metric_name(self, input: RelationalDatabaseMetricName) -> Self

The metric for which you want to return information.

Valid relational database metric names are listed below, along with the most useful statistics to include in your request, and the published unit value. All relational database metric data is available in 1-minute (60 seconds) granularity.

  • CPUUtilization - The percentage of CPU utilization currently in use on the database.

    Statistics: The most useful statistics are Maximum and Average.

    Unit: The published unit is Percent.

  • DatabaseConnections - The number of database connections in use.

    Statistics: The most useful statistics are Maximum and Sum.

    Unit: The published unit is Count.

  • DiskQueueDepth - The number of outstanding IOs (read/write requests) that are waiting to access the disk.

    Statistics: The most useful statistic is Sum.

    Unit: The published unit is Count.

  • FreeStorageSpace - The amount of available storage space.

    Statistics: The most useful statistic is Sum.

    Unit: The published unit is Bytes.

  • NetworkReceiveThroughput - The incoming (Receive) network traffic on the database, including both customer database traffic and AWS traffic used for monitoring and replication.

    Statistics: The most useful statistic is Average.

    Unit: The published unit is Bytes/Second.

  • NetworkTransmitThroughput - The outgoing (Transmit) network traffic on the database, including both customer database traffic and AWS traffic used for monitoring and replication.

    Statistics: The most useful statistic is Average.

    Unit: The published unit is Bytes/Second.

This field is required.
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pub fn set_metric_name( self, input: Option<RelationalDatabaseMetricName>, ) -> Self

The metric for which you want to return information.

Valid relational database metric names are listed below, along with the most useful statistics to include in your request, and the published unit value. All relational database metric data is available in 1-minute (60 seconds) granularity.

  • CPUUtilization - The percentage of CPU utilization currently in use on the database.

    Statistics: The most useful statistics are Maximum and Average.

    Unit: The published unit is Percent.

  • DatabaseConnections - The number of database connections in use.

    Statistics: The most useful statistics are Maximum and Sum.

    Unit: The published unit is Count.

  • DiskQueueDepth - The number of outstanding IOs (read/write requests) that are waiting to access the disk.

    Statistics: The most useful statistic is Sum.

    Unit: The published unit is Count.

  • FreeStorageSpace - The amount of available storage space.

    Statistics: The most useful statistic is Sum.

    Unit: The published unit is Bytes.

  • NetworkReceiveThroughput - The incoming (Receive) network traffic on the database, including both customer database traffic and AWS traffic used for monitoring and replication.

    Statistics: The most useful statistic is Average.

    Unit: The published unit is Bytes/Second.

  • NetworkTransmitThroughput - The outgoing (Transmit) network traffic on the database, including both customer database traffic and AWS traffic used for monitoring and replication.

    Statistics: The most useful statistic is Average.

    Unit: The published unit is Bytes/Second.

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pub fn get_metric_name(&self) -> &Option<RelationalDatabaseMetricName>

The metric for which you want to return information.

Valid relational database metric names are listed below, along with the most useful statistics to include in your request, and the published unit value. All relational database metric data is available in 1-minute (60 seconds) granularity.

  • CPUUtilization - The percentage of CPU utilization currently in use on the database.

    Statistics: The most useful statistics are Maximum and Average.

    Unit: The published unit is Percent.

  • DatabaseConnections - The number of database connections in use.

    Statistics: The most useful statistics are Maximum and Sum.

    Unit: The published unit is Count.

  • DiskQueueDepth - The number of outstanding IOs (read/write requests) that are waiting to access the disk.

    Statistics: The most useful statistic is Sum.

    Unit: The published unit is Count.

  • FreeStorageSpace - The amount of available storage space.

    Statistics: The most useful statistic is Sum.

    Unit: The published unit is Bytes.

  • NetworkReceiveThroughput - The incoming (Receive) network traffic on the database, including both customer database traffic and AWS traffic used for monitoring and replication.

    Statistics: The most useful statistic is Average.

    Unit: The published unit is Bytes/Second.

  • NetworkTransmitThroughput - The outgoing (Transmit) network traffic on the database, including both customer database traffic and AWS traffic used for monitoring and replication.

    Statistics: The most useful statistic is Average.

    Unit: The published unit is Bytes/Second.

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

The granularity, in seconds, of the returned data points.

All relational database metric data is available in 1-minute (60 seconds) granularity.

This field is required.
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pub fn set_period(self, input: Option<i32>) -> Self

The granularity, in seconds, of the returned data points.

All relational database metric data is available in 1-minute (60 seconds) granularity.

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

The granularity, in seconds, of the returned data points.

All relational database metric data is available in 1-minute (60 seconds) granularity.

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pub fn start_time(self, input: DateTime) -> Self

The start of the time interval from which to get metric data.

Constraints:

  • Specified in Coordinated Universal Time (UTC).

  • Specified in the Unix time format.

    For example, if you wish to use a start time of October 1, 2018, at 8 PM UTC, then you input 1538424000 as the start time.

This field is required.
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pub fn set_start_time(self, input: Option<DateTime>) -> Self

The start of the time interval from which to get metric data.

Constraints:

  • Specified in Coordinated Universal Time (UTC).

  • Specified in the Unix time format.

    For example, if you wish to use a start time of October 1, 2018, at 8 PM UTC, then you input 1538424000 as the start time.

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pub fn get_start_time(&self) -> &Option<DateTime>

The start of the time interval from which to get metric data.

Constraints:

  • Specified in Coordinated Universal Time (UTC).

  • Specified in the Unix time format.

    For example, if you wish to use a start time of October 1, 2018, at 8 PM UTC, then you input 1538424000 as the start time.

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pub fn end_time(self, input: DateTime) -> Self

The end of the time interval from which to get metric data.

Constraints:

  • Specified in Coordinated Universal Time (UTC).

  • Specified in the Unix time format.

    For example, if you wish to use an end time of October 1, 2018, at 8 PM UTC, then you input 1538424000 as the end time.

This field is required.
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pub fn set_end_time(self, input: Option<DateTime>) -> Self

The end of the time interval from which to get metric data.

Constraints:

  • Specified in Coordinated Universal Time (UTC).

  • Specified in the Unix time format.

    For example, if you wish to use an end time of October 1, 2018, at 8 PM UTC, then you input 1538424000 as the end time.

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pub fn get_end_time(&self) -> &Option<DateTime>

The end of the time interval from which to get metric data.

Constraints:

  • Specified in Coordinated Universal Time (UTC).

  • Specified in the Unix time format.

    For example, if you wish to use an end time of October 1, 2018, at 8 PM UTC, then you input 1538424000 as the end time.

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pub fn unit(self, input: MetricUnit) -> Self

The unit for the metric data request. Valid units depend on the metric data being requested. For the valid units with each available metric, see the metricName parameter.

This field is required.
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pub fn set_unit(self, input: Option<MetricUnit>) -> Self

The unit for the metric data request. Valid units depend on the metric data being requested. For the valid units with each available metric, see the metricName parameter.

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pub fn get_unit(&self) -> &Option<MetricUnit>

The unit for the metric data request. Valid units depend on the metric data being requested. For the valid units with each available metric, see the metricName parameter.

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pub fn statistics(self, input: MetricStatistic) -> Self

Appends an item to statistics.

To override the contents of this collection use set_statistics.

The statistic for the metric.

The following statistics are available:

  • Minimum - The lowest value observed during the specified period. Use this value to determine low volumes of activity for your application.

  • Maximum - The highest value observed during the specified period. Use this value to determine high volumes of activity for your application.

  • Sum - All values submitted for the matching metric added together. You can use this statistic to determine the total volume of a metric.

  • Average - The value of Sum / SampleCount during the specified period. By comparing this statistic with the Minimum and Maximum values, you can determine the full scope of a metric and how close the average use is to the Minimum and Maximum values. This comparison helps you to know when to increase or decrease your resources.

  • SampleCount - The count, or number, of data points used for the statistical calculation.

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pub fn set_statistics(self, input: Option<Vec<MetricStatistic>>) -> Self

The statistic for the metric.

The following statistics are available:

  • Minimum - The lowest value observed during the specified period. Use this value to determine low volumes of activity for your application.

  • Maximum - The highest value observed during the specified period. Use this value to determine high volumes of activity for your application.

  • Sum - All values submitted for the matching metric added together. You can use this statistic to determine the total volume of a metric.

  • Average - The value of Sum / SampleCount during the specified period. By comparing this statistic with the Minimum and Maximum values, you can determine the full scope of a metric and how close the average use is to the Minimum and Maximum values. This comparison helps you to know when to increase or decrease your resources.

  • SampleCount - The count, or number, of data points used for the statistical calculation.

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pub fn get_statistics(&self) -> &Option<Vec<MetricStatistic>>

The statistic for the metric.

The following statistics are available:

  • Minimum - The lowest value observed during the specified period. Use this value to determine low volumes of activity for your application.

  • Maximum - The highest value observed during the specified period. Use this value to determine high volumes of activity for your application.

  • Sum - All values submitted for the matching metric added together. You can use this statistic to determine the total volume of a metric.

  • Average - The value of Sum / SampleCount during the specified period. By comparing this statistic with the Minimum and Maximum values, you can determine the full scope of a metric and how close the average use is to the Minimum and Maximum values. This comparison helps you to know when to increase or decrease your resources.

  • SampleCount - The count, or number, of data points used for the statistical calculation.

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

Consumes the builder and constructs a GetRelationalDatabaseMetricDataInput.

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impl GetRelationalDatabaseMetricDataInputBuilder

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pub async fn send_with( self, client: &Client, ) -> Result<GetRelationalDatabaseMetricDataOutput, SdkError<GetRelationalDatabaseMetricDataError, HttpResponse>>

Sends a request with this input using the given client.

Trait Implementations§

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impl Clone for GetRelationalDatabaseMetricDataInputBuilder

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fn clone(&self) -> GetRelationalDatabaseMetricDataInputBuilder

Returns a duplicate of the value. Read more
1.0.0 · Source§

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

Performs copy-assignment from source. Read more
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impl Debug for GetRelationalDatabaseMetricDataInputBuilder

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

Formats the value using the given formatter. Read more
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impl Default for GetRelationalDatabaseMetricDataInputBuilder

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fn default() -> GetRelationalDatabaseMetricDataInputBuilder

Returns the “default value” for a type. Read more
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impl PartialEq for GetRelationalDatabaseMetricDataInputBuilder

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

Tests for self and other values to be equal, and is used by ==.
1.0.0 · Source§

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

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.
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impl StructuralPartialEq for GetRelationalDatabaseMetricDataInputBuilder

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impl<T> WithSubscriber for T

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fn with_subscriber<S>(self, subscriber: S) -> WithDispatch<Self>
where S: Into<Dispatch>,

Attaches the provided Subscriber to this type, returning a WithDispatch wrapper. Read more
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fn with_current_subscriber(self) -> WithDispatch<Self>

Attaches the current default Subscriber to this type, returning a WithDispatch wrapper. Read more
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impl<T> ErasedDestructor for T
where T: 'static,