Struct google_monitoring3::Distribution

pub struct Distribution {
    pub count: Option<String>,
    pub bucket_counts: Option<Vec<String>>,
    pub sum_of_squared_deviation: Option<f64>,
    pub range: Option<Range>,
    pub bucket_options: Option<BucketOptions>,
    pub exemplars: Option<Vec<Exemplar>>,
    pub mean: Option<f64>,
}

Distribution contains summary statistics for a population of values. It optionally contains a histogram representing the distribution of those values across a set of buckets.The summary statistics are the count, mean, sum of the squared deviation from the mean, the minimum, and the maximum of the set of population of values. The histogram is based on a sequence of buckets and gives a count of values that fall into each bucket. The boundaries of the buckets are given either explicitly or by formulas for buckets of fixed or exponentially increasing widths.Although it is not forbidden, it is generally a bad idea to include non-finite values (infinities or NaNs) in the population of values, as this will render the mean and sum_of_squared_deviation fields meaningless.

This type is not used in any activity, and only used as part of another schema.

Fields

count: Option<String>

The number of values in the population. Must be non-negative. This value must equal the sum of the values in bucket_counts if a histogram is provided.

bucket_counts: Option<Vec<String>>

Required in the Cloud Monitoring API v3. The values for each bucket specified in bucket_options. The sum of the values in bucketCounts must equal the value in the count field of the Distribution object. The order of the bucket counts follows the numbering schemes described for the three bucket types. The underflow bucket has number 0; the finite buckets, if any, have numbers 1 through N-2; and the overflow bucket has number N-1. The size of bucket_counts must not be greater than N. If the size is less than N, then the remaining buckets are assigned values of zero.

sum_of_squared_deviation: Option<f64>

The sum of squared deviations from the mean of the values in the population. For values x_i this is: Sum[i=1..n]((x_i - mean)^2) Knuth, "The Art of Computer Programming", Vol. 2, page 323, 3rd edition describes Welford's method for accumulating this sum in one pass.If count is zero then this field must be zero.

range: Option<Range>

If specified, contains the range of the population values. The field must not be present if the count is zero. This field is presently ignored by the Cloud Monitoring API v3.

bucket_options: Option<BucketOptions>

Required in the Cloud Monitoring API v3. Defines the histogram bucket boundaries.

exemplars: Option<Vec<Exemplar>>

Must be in increasing order of value field.

mean: Option<f64>

The arithmetic mean of the values in the population. If count is zero then this field must be zero.

Trait Implementations

impl Clone for Distribution

fn clone(&self) -> Distribution

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for Distribution

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

Formats the value using the given formatter.

impl Default for Distribution

fn default() -> Distribution

Returns the "default value" for a type.

impl<'de> Deserialize<'de> for Distribution

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error> where
    __D: Deserializer<'de>, 

Deserialize this value from the given Serde deserializer.

impl Part for Distribution

impl Serialize for Distribution

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

Serialize this value into the given Serde serializer.