Cloud Monitoring V3 API - Class Google::Api::Distribution (v1.0.0)

Reference documentation and code samples for the Cloud Monitoring V3 API class Google::Api::Distribution.

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.

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 values in each bucket of the histogram, as described in bucket_options. If the distribution does not have a histogram, then omit this field. If there is a histogram, then the sum of the values in bucket_counts must equal the value in the count field of the distribution.

    If present, bucket_counts should contain N values, where N is the number of buckets specified in bucket_options. If you supply fewer than N values, the remaining values are assumed to be 0.

    The order of the values in bucket_counts follows the bucket numbering schemes described for the three bucket types. The first value must be the count for the underflow bucket (number 0). The next N-2 values are the counts for the finite buckets (number 1 through N-2). The N'th value in bucket_counts is the count for the overflow bucket (number N-1).

#bucket_counts=

def bucket_counts=(value) -> ::Array<::Integer>
Parameter
  • value (::Array<::Integer>) — The number of values in each bucket of the histogram, as described in bucket_options. If the distribution does not have a histogram, then omit this field. If there is a histogram, then the sum of the values in bucket_counts must equal the value in the count field of the distribution.

    If present, bucket_counts should contain N values, where N is the number of buckets specified in bucket_options. If you supply fewer than N values, the remaining values are assumed to be 0.

    The order of the values in bucket_counts follows the bucket numbering schemes described for the three bucket types. The first value must be the count for the underflow bucket (number 0). The next N-2 values are the counts for the finite buckets (number 1 through N-2). The N'th value in bucket_counts is the count for the overflow bucket (number N-1).

Returns
  • (::Array<::Integer>) — The number of values in each bucket of the histogram, as described in bucket_options. If the distribution does not have a histogram, then omit this field. If there is a histogram, then the sum of the values in bucket_counts must equal the value in the count field of the distribution.

    If present, bucket_counts should contain N values, where N is the number of buckets specified in bucket_options. If you supply fewer than N values, the remaining values are assumed to be 0.

    The order of the values in bucket_counts follows the bucket numbering schemes described for the three bucket types. The first value must be the count for the underflow bucket (number 0). The next N-2 values are the counts for the finite buckets (number 1 through N-2). The N'th value in bucket_counts is the count for the overflow bucket (number N-1).

#bucket_options

def bucket_options() -> ::Google::Api::Distribution::BucketOptions
Returns

#bucket_options=

def bucket_options=(value) -> ::Google::Api::Distribution::BucketOptions
Parameter
Returns

#count

def count() -> ::Integer
Returns
  • (::Integer) — 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.

#count=

def count=(value) -> ::Integer
Parameter
  • value (::Integer) — 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.
Returns
  • (::Integer) — 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.

#exemplars

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

#exemplars=

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

#mean

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

#mean=

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

#range

def range() -> ::Google::Api::Distribution::Range
Returns

#range=

def range=(value) -> ::Google::Api::Distribution::Range
Parameter
Returns

#sum_of_squared_deviation

def sum_of_squared_deviation() -> ::Float
Returns
  • (::Float) — 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 232, 3rd edition describes Welford's method for accumulating this sum in one pass.

    If count is zero then this field must be zero.

#sum_of_squared_deviation=

def sum_of_squared_deviation=(value) -> ::Float
Parameter
  • value (::Float) — 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 232, 3rd edition describes Welford's method for accumulating this sum in one pass.

    If count is zero then this field must be zero.

Returns
  • (::Float) — 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 232, 3rd edition describes Welford's method for accumulating this sum in one pass.

    If count is zero then this field must be zero.