Struct LogsQueryCompute

#[non_exhaustive]
pub struct LogsQueryCompute {
    pub aggregation: String,
    pub facet: Option<String>,
    pub interval: Option<i64>,
    pub additional_properties: BTreeMap<String, Value>,
    /* private fields */
}

Define computation for a log query.

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.

aggregation: String

The aggregation method.

facet: Option<String>

Facet name.

interval: Option<i64>

Define a time interval in seconds.

additional_properties: BTreeMap<String, Value>

Implementations

impl LogsQueryCompute

pub fn new(aggregation: String) -> LogsQueryCompute

Examples found in repository

examples/v1_dashboards_CreateDashboard.rs (line 28)

async fn main() {
    let body = Dashboard::new(
        DashboardLayoutType::ORDERED,
        "Example-Dashboard with Profile Metrics Query".to_string(),
        vec![Widget::new(WidgetDefinition::TimeseriesWidgetDefinition(
            Box::new(TimeseriesWidgetDefinition::new(
                vec![TimeseriesWidgetRequest::new().profile_metrics_query(
                    LogQueryDefinition::new()
                        .compute(
                            LogsQueryCompute::new("sum".to_string())
                                .facet("@prof_core_cpu_cores".to_string()),
                        )
                        .group_by(vec![LogQueryDefinitionGroupBy::new("service".to_string())
                            .limit(10)
                            .sort(
                                LogQueryDefinitionGroupBySort::new(
                                    "sum".to_string(),
                                    WidgetSort::DESCENDING,
                                )
                                .facet("@prof_core_cpu_cores".to_string()),
                            )])
                        .search(LogQueryDefinitionSearch::new("runtime:jvm".to_string())),
                )],
                TimeseriesWidgetDefinitionType::TIMESERIES,
            )),
        ))],
    );
    let configuration = datadog::Configuration::new();
    let api = DashboardsAPI::with_config(configuration);
    let resp = api.create_dashboard(body).await;
    if let Ok(value) = resp {
        println!("{:#?}", value);
    } else {
        println!("{:#?}", resp.unwrap_err());
    }
}

pub fn facet(self, value: String) -> Self

Examples found in repository

examples/v1_dashboards_CreateDashboard.rs (line 29)

async fn main() {
    let body = Dashboard::new(
        DashboardLayoutType::ORDERED,
        "Example-Dashboard with Profile Metrics Query".to_string(),
        vec![Widget::new(WidgetDefinition::TimeseriesWidgetDefinition(
            Box::new(TimeseriesWidgetDefinition::new(
                vec![TimeseriesWidgetRequest::new().profile_metrics_query(
                    LogQueryDefinition::new()
                        .compute(
                            LogsQueryCompute::new("sum".to_string())
                                .facet("@prof_core_cpu_cores".to_string()),
                        )
                        .group_by(vec![LogQueryDefinitionGroupBy::new("service".to_string())
                            .limit(10)
                            .sort(
                                LogQueryDefinitionGroupBySort::new(
                                    "sum".to_string(),
                                    WidgetSort::DESCENDING,
                                )
                                .facet("@prof_core_cpu_cores".to_string()),
                            )])
                        .search(LogQueryDefinitionSearch::new("runtime:jvm".to_string())),
                )],
                TimeseriesWidgetDefinitionType::TIMESERIES,
            )),
        ))],
    );
    let configuration = datadog::Configuration::new();
    let api = DashboardsAPI::with_config(configuration);
    let resp = api.create_dashboard(body).await;
    if let Ok(value) = resp {
        println!("{:#?}", value);
    } else {
        println!("{:#?}", resp.unwrap_err());
    }
}

pub fn interval(self, value: i64) -> Self

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

Trait Implementations

impl Clone for LogsQueryCompute

fn clone(&self) -> LogsQueryCompute

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for LogsQueryCompute

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

Formats the value using the given formatter.

impl<'de> Deserialize<'de> for LogsQueryCompute

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

where D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl PartialEq for LogsQueryCompute

fn eq(&self, other: &LogsQueryCompute) -> 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 LogsQueryCompute

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 LogsQueryCompute