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

Attributes

• bucketCounts (type: list(String.t), default: nil) - 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 (type: String.t, default: nil) - The total number of samples in the distribution. Must be >= 0.

• exemplars (type: list(GoogleApi.ServiceControl.V1.Model.Exemplar.t), default: nil) - Example points. Must be in increasing order of value field.

• explicitBuckets (type: GoogleApi.ServiceControl.V1.Model.ExplicitBuckets.t, default: nil) - Buckets with arbitrary user-provided width.

• exponentialBuckets (type: GoogleApi.ServiceControl.V1.Model.ExponentialBuckets.t, default: nil) - Buckets with exponentially growing width.

• linearBuckets (type: GoogleApi.ServiceControl.V1.Model.LinearBuckets.t, default: nil) - Buckets with constant width.

• maximum (type: float(), default: nil) - The maximum of the population of values. Ignored if count is zero.

• mean (type: float(), default: nil) - The arithmetic mean of the samples in the distribution. If count is zero then this field must be zero.

• minimum (type: float(), default: nil) - The minimum of the population of values. Ignored if count is zero.

• sumOfSquaredDeviation (type: float(), default: nil) - 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.