Service Control API V1 API - Class Google::Cloud::ServiceControl::V1::Distribution (v1.2.1)

Reference documentation and code samples for the Service Control API V1 API class Google::Cloud::ServiceControl::V1::Distribution.

Distribution represents a frequency distribution of double-valued sample points. It contains the size of the population of sample points plus additional optional information:

  • the arithmetic mean of the samples
  • the minimum and maximum of the samples
  • the sum-squared-deviation of the samples, used to compute variance
  • a histogram of the values of the sample points

Inherits

  • Object

Extended By

  • Google::Protobuf::MessageExts::ClassMethods

Includes

  • Google::Protobuf::MessageExts

Methods

#bucket_counts

def bucket_counts() -> ::Array<::Integer>
Returns
  • (::Array<::Integer>) — The number of samples in each histogram bucket. bucket_counts are optional. If present, they must sum to the count value.

    The buckets are defined below in bucket_option. There are N buckets. bucket_counts[0] is the number of samples in the underflow bucket. bucket_counts[1] to bucket_counts[N-1] are the numbers of samples in each of the finite buckets. And bucket_counts[N] is the number of samples in the overflow bucket. See the comments ofbucket_option` below for more details.

    Any suffix of trailing zeros may be omitted.

#bucket_counts=

def bucket_counts=(value) -> ::Array<::Integer>
Parameter
  • value (::Array<::Integer>) — The number of samples in each histogram bucket. bucket_counts are optional. If present, they must sum to the count value.

    The buckets are defined below in bucket_option. There are N buckets. bucket_counts[0] is the number of samples in the underflow bucket. bucket_counts[1] to bucket_counts[N-1] are the numbers of samples in each of the finite buckets. And bucket_counts[N] is the number of samples in the overflow bucket. See the comments ofbucket_option` below for more details.

    Any suffix of trailing zeros may be omitted.

Returns
  • (::Array<::Integer>) — The number of samples in each histogram bucket. bucket_counts are optional. If present, they must sum to the count value.

    The buckets are defined below in bucket_option. There are N buckets. bucket_counts[0] is the number of samples in the underflow bucket. bucket_counts[1] to bucket_counts[N-1] are the numbers of samples in each of the finite buckets. And bucket_counts[N] is the number of samples in the overflow bucket. See the comments ofbucket_option` below for more details.

    Any suffix of trailing zeros may be omitted.

#count

def count() -> ::Integer
Returns
  • (::Integer) — The total number of samples in the distribution. Must be >= 0.

#count=

def count=(value) -> ::Integer
Parameter
  • value (::Integer) — The total number of samples in the distribution. Must be >= 0.
Returns
  • (::Integer) — The total number of samples in the distribution. Must be >= 0.

#exemplars

def exemplars() -> ::Array<::Google::Api::Distribution::Exemplar>
Returns

#exemplars=

def exemplars=(value) -> ::Array<::Google::Api::Distribution::Exemplar>
Parameter
Returns

#explicit_buckets

def explicit_buckets() -> ::Google::Cloud::ServiceControl::V1::Distribution::ExplicitBuckets
Returns

#explicit_buckets=

def explicit_buckets=(value) -> ::Google::Cloud::ServiceControl::V1::Distribution::ExplicitBuckets
Parameter
Returns

#exponential_buckets

def exponential_buckets() -> ::Google::Cloud::ServiceControl::V1::Distribution::ExponentialBuckets
Returns

#exponential_buckets=

def exponential_buckets=(value) -> ::Google::Cloud::ServiceControl::V1::Distribution::ExponentialBuckets
Parameter
Returns

#linear_buckets

def linear_buckets() -> ::Google::Cloud::ServiceControl::V1::Distribution::LinearBuckets
Returns

#linear_buckets=

def linear_buckets=(value) -> ::Google::Cloud::ServiceControl::V1::Distribution::LinearBuckets
Parameter
Returns

#maximum

def maximum() -> ::Float
Returns
  • (::Float) — The maximum of the population of values. Ignored if count is zero.

#maximum=

def maximum=(value) -> ::Float
Parameter
  • value (::Float) — The maximum of the population of values. Ignored if count is zero.
Returns
  • (::Float) — The maximum of the population of values. Ignored if count is zero.

#mean

def mean() -> ::Float
Returns
  • (::Float) — The arithmetic mean of the samples in the distribution. If count is zero then this field must be zero.

#mean=

def mean=(value) -> ::Float
Parameter
  • value (::Float) — The arithmetic mean of the samples in the distribution. If count is zero then this field must be zero.
Returns
  • (::Float) — The arithmetic mean of the samples in the distribution. If count is zero then this field must be zero.

#minimum

def minimum() -> ::Float
Returns
  • (::Float) — The minimum of the population of values. Ignored if count is zero.

#minimum=

def minimum=(value) -> ::Float
Parameter
  • value (::Float) — The minimum of the population of values. Ignored if count is zero.
Returns
  • (::Float) — The minimum of the population of values. Ignored if count is zero.

#sum_of_squared_deviation

def sum_of_squared_deviation() -> ::Float
Returns
  • (::Float) — The sum of squared deviations from the mean: Sumi=1..count where each x_i is a sample values. If count is zero then this field must be zero, otherwise validation of the request fails.

#sum_of_squared_deviation=

def sum_of_squared_deviation=(value) -> ::Float
Parameter
  • value (::Float) — The sum of squared deviations from the mean: Sumi=1..count where each x_i is a sample values. If count is zero then this field must be zero, otherwise validation of the request fails.
Returns
  • (::Float) — The sum of squared deviations from the mean: Sumi=1..count where each x_i is a sample values. If count is zero then this field must be zero, otherwise validation of the request fails.