Struct QueryFormula

#[non_exhaustive]
pub struct QueryFormula {
    pub formula: String,
    pub limit: Option<FormulaLimit>,
    pub additional_properties: BTreeMap<String, Value>,
    /* private fields */
}

A formula for calculation based on one or more queries.

Fields (Non-exhaustive)

Non-exhaustive structs could have additional fields added in future. Therefore, non-exhaustive structs cannot be constructed in external crates using the traditional Struct { .. } syntax; cannot be matched against without a wildcard ..; and struct update syntax will not work.

formula: String

Formula string, referencing one or more queries with their name property.

limit: Option<FormulaLimit>

Message for specifying limits to the number of values returned by a query. This limit is only for scalar queries and has no effect on timeseries queries.

additional_properties: BTreeMap<String, Value>

Implementations

impl QueryFormula

pub fn new(formula: String) -> QueryFormula

Examples found in repository

examples/v2_metrics_QueryScalarData.rs (line 30)

async fn main() {
    let body = ScalarFormulaQueryRequest::new(ScalarFormulaRequest::new(
        ScalarFormulaRequestAttributes::new(
            1568899800000,
            vec![ScalarQuery::MetricsScalarQuery(Box::new(
                MetricsScalarQuery::new(
                    MetricsAggregator::AVG,
                    MetricsDataSource::METRICS,
                    "avg:system.cpu.user{*} by {env}".to_string(),
                ),
            ))],
            1568923200000,
        )
        .formulas(vec![QueryFormula::new("a+b".to_string())
            .limit(FormulaLimit::new().count(10).order(QuerySortOrder::DESC))]),
        ScalarFormulaRequestType::SCALAR_REQUEST,
    ));
    let configuration = datadog::Configuration::new();
    let api = MetricsAPI::with_config(configuration);
    let resp = api.query_scalar_data(body).await;
    if let Ok(value) = resp {
        println!("{:#?}", value);
    } else {
        println!("{:#?}", resp.unwrap_err());
    }
}

examples/v2_metrics_QueryTimeseriesData.rs (line 28)

async fn main() {
    let body = TimeseriesFormulaQueryRequest::new(TimeseriesFormulaRequest::new(
        TimeseriesFormulaRequestAttributes::new(
            1568899800000,
            vec![TimeseriesQuery::MetricsTimeseriesQuery(Box::new(
                MetricsTimeseriesQuery::new(
                    MetricsDataSource::METRICS,
                    "avg:system.cpu.user{*} by {env}".to_string(),
                ),
            ))],
            1568923200000,
        )
        .formulas(vec![QueryFormula::new("a+b".to_string())
            .limit(FormulaLimit::new().count(10).order(QuerySortOrder::DESC))])
        .interval(5000),
        TimeseriesFormulaRequestType::TIMESERIES_REQUEST,
    ));
    let configuration = datadog::Configuration::new();
    let api = MetricsAPI::with_config(configuration);
    let resp = api.query_timeseries_data(body).await;
    if let Ok(value) = resp {
        println!("{:#?}", value);
    } else {
        println!("{:#?}", resp.unwrap_err());
    }
}

examples/v2_metrics_QueryScalarData_3112571352.rs (line 31)

async fn main() {
    let body = ScalarFormulaQueryRequest::new(ScalarFormulaRequest::new(
        ScalarFormulaRequestAttributes::new(
            1636625471000,
            vec![ScalarQuery::MetricsScalarQuery(Box::new(
                MetricsScalarQuery::new(
                    MetricsAggregator::AVG,
                    MetricsDataSource::METRICS,
                    "avg:system.cpu.user{*}".to_string(),
                )
                .name("a".to_string()),
            ))],
            1636629071000,
        )
        .formulas(vec![QueryFormula::new("a".to_string())
            .limit(FormulaLimit::new().count(10).order(QuerySortOrder::DESC))]),
        ScalarFormulaRequestType::SCALAR_REQUEST,
    ));
    let configuration = datadog::Configuration::new();
    let api = MetricsAPI::with_config(configuration);
    let resp = api.query_scalar_data(body).await;
    if let Ok(value) = resp {
        println!("{:#?}", value);
    } else {
        println!("{:#?}", resp.unwrap_err());
    }
}

examples/v2_metrics_QueryTimeseriesData_301142940.rs (line 29)

async fn main() {
    let body = TimeseriesFormulaQueryRequest::new(TimeseriesFormulaRequest::new(
        TimeseriesFormulaRequestAttributes::new(
            1636625471000,
            vec![TimeseriesQuery::MetricsTimeseriesQuery(Box::new(
                MetricsTimeseriesQuery::new(
                    MetricsDataSource::METRICS,
                    "avg:datadog.estimated_usage.metrics.custom{*}".to_string(),
                )
                .name("a".to_string()),
            ))],
            1636629071000,
        )
        .formulas(vec![QueryFormula::new("a".to_string())
            .limit(FormulaLimit::new().count(10).order(QuerySortOrder::DESC))])
        .interval(5000),
        TimeseriesFormulaRequestType::TIMESERIES_REQUEST,
    ));
    let configuration = datadog::Configuration::new();
    let api = MetricsAPI::with_config(configuration);
    let resp = api.query_timeseries_data(body).await;
    if let Ok(value) = resp {
        println!("{:#?}", value);
    } else {
        println!("{:#?}", resp.unwrap_err());
    }
}

pub fn limit(self, value: FormulaLimit) -> Self

Examples found in repository

examples/v2_metrics_QueryScalarData.rs (line 31)

async fn main() {
    let body = ScalarFormulaQueryRequest::new(ScalarFormulaRequest::new(
        ScalarFormulaRequestAttributes::new(
            1568899800000,
            vec![ScalarQuery::MetricsScalarQuery(Box::new(
                MetricsScalarQuery::new(
                    MetricsAggregator::AVG,
                    MetricsDataSource::METRICS,
                    "avg:system.cpu.user{*} by {env}".to_string(),
                ),
            ))],
            1568923200000,
        )
        .formulas(vec![QueryFormula::new("a+b".to_string())
            .limit(FormulaLimit::new().count(10).order(QuerySortOrder::DESC))]),
        ScalarFormulaRequestType::SCALAR_REQUEST,
    ));
    let configuration = datadog::Configuration::new();
    let api = MetricsAPI::with_config(configuration);
    let resp = api.query_scalar_data(body).await;
    if let Ok(value) = resp {
        println!("{:#?}", value);
    } else {
        println!("{:#?}", resp.unwrap_err());
    }
}

examples/v2_metrics_QueryTimeseriesData.rs (line 29)

async fn main() {
    let body = TimeseriesFormulaQueryRequest::new(TimeseriesFormulaRequest::new(
        TimeseriesFormulaRequestAttributes::new(
            1568899800000,
            vec![TimeseriesQuery::MetricsTimeseriesQuery(Box::new(
                MetricsTimeseriesQuery::new(
                    MetricsDataSource::METRICS,
                    "avg:system.cpu.user{*} by {env}".to_string(),
                ),
            ))],
            1568923200000,
        )
        .formulas(vec![QueryFormula::new("a+b".to_string())
            .limit(FormulaLimit::new().count(10).order(QuerySortOrder::DESC))])
        .interval(5000),
        TimeseriesFormulaRequestType::TIMESERIES_REQUEST,
    ));
    let configuration = datadog::Configuration::new();
    let api = MetricsAPI::with_config(configuration);
    let resp = api.query_timeseries_data(body).await;
    if let Ok(value) = resp {
        println!("{:#?}", value);
    } else {
        println!("{:#?}", resp.unwrap_err());
    }
}

examples/v2_metrics_QueryScalarData_3112571352.rs (line 32)

async fn main() {
    let body = ScalarFormulaQueryRequest::new(ScalarFormulaRequest::new(
        ScalarFormulaRequestAttributes::new(
            1636625471000,
            vec![ScalarQuery::MetricsScalarQuery(Box::new(
                MetricsScalarQuery::new(
                    MetricsAggregator::AVG,
                    MetricsDataSource::METRICS,
                    "avg:system.cpu.user{*}".to_string(),
                )
                .name("a".to_string()),
            ))],
            1636629071000,
        )
        .formulas(vec![QueryFormula::new("a".to_string())
            .limit(FormulaLimit::new().count(10).order(QuerySortOrder::DESC))]),
        ScalarFormulaRequestType::SCALAR_REQUEST,
    ));
    let configuration = datadog::Configuration::new();
    let api = MetricsAPI::with_config(configuration);
    let resp = api.query_scalar_data(body).await;
    if let Ok(value) = resp {
        println!("{:#?}", value);
    } else {
        println!("{:#?}", resp.unwrap_err());
    }
}

examples/v2_metrics_QueryTimeseriesData_301142940.rs (line 30)

async fn main() {
    let body = TimeseriesFormulaQueryRequest::new(TimeseriesFormulaRequest::new(
        TimeseriesFormulaRequestAttributes::new(
            1636625471000,
            vec![TimeseriesQuery::MetricsTimeseriesQuery(Box::new(
                MetricsTimeseriesQuery::new(
                    MetricsDataSource::METRICS,
                    "avg:datadog.estimated_usage.metrics.custom{*}".to_string(),
                )
                .name("a".to_string()),
            ))],
            1636629071000,
        )
        .formulas(vec![QueryFormula::new("a".to_string())
            .limit(FormulaLimit::new().count(10).order(QuerySortOrder::DESC))])
        .interval(5000),
        TimeseriesFormulaRequestType::TIMESERIES_REQUEST,
    ));
    let configuration = datadog::Configuration::new();
    let api = MetricsAPI::with_config(configuration);
    let resp = api.query_timeseries_data(body).await;
    if let Ok(value) = resp {
        println!("{:#?}", value);
    } else {
        println!("{:#?}", resp.unwrap_err());
    }
}

pub fn additional_properties(self, value: BTreeMap<String, Value>) -> Self

Trait Implementations

impl Clone for QueryFormula

fn clone(&self) -> QueryFormula

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for QueryFormula

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

Formats the value using the given formatter.

impl<'de> Deserialize<'de> for QueryFormula

fn deserialize<D>(deserializer: D) -> Result<Self, D::Error>

where D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl PartialEq for QueryFormula

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

Tests for self and other values to be equal, and is used by ==.

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

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

impl Serialize for QueryFormula

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.

impl StructuralPartialEq for QueryFormula