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 (List[String]): 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 of `bucket_option` below for more details. Any suffix of trailing zeros may be omitted. Defaults to: null.
• count (String): The total number of samples in the distribution. Must be >= 0. Defaults to: null.
• explicitBuckets (ExplicitBuckets): Buckets with arbitrary user-provided width. Defaults to: null.
• exponentialBuckets (ExponentialBuckets): Buckets with exponentially growing width. Defaults to: null.
• linearBuckets (LinearBuckets): Buckets with constant width. Defaults to: null.
• maximum (Float): The maximum of the population of values. Ignored if `count` is zero. Defaults to: null.
• mean (Float): The arithmetic mean of the samples in the distribution. If `count` is zero then this field must be zero. Defaults to: null.
• minimum (Float): The minimum of the population of values. Ignored if `count` is zero. Defaults to: null.
• sumOfSquaredDeviation (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. Defaults to: null.