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 nonfinite values (infinities or NaNs) in the population of values, as this will render the mean
and sumOfSquaredDeviation
fields meaningless.
JSON representation 

{ "count": string, "mean": number, "sumOfSquaredDeviation": number, "range": { object ( 
Fields  

count 
The number of values in the population. Must be nonnegative. This value must equal the sum of the values in 
mean 
The arithmetic mean of the values in the population. If 
sumOfSquaredDeviation 
The sum of squared deviations from the mean of the values in the population. For values x_i this is:
Knuth, "The Art of Computer Programming", Vol. 2, page 232, 3rd edition describes Welford's method for accumulating this sum in one pass. If 
range 
If specified, contains the range of the population values. The field must not be present if the 
bucketOptions 
Defines the histogram bucket boundaries. If the distribution does not contain a histogram, then omit this field. 
bucketCounts[] 
The number of values in each bucket of the histogram, as described in If present, The order of the values in 
exemplars[] 
Must be in increasing order of 
Range
The range of the population values.
JSON representation 

{ "min": number, "max": number } 
Fields  

min 
The minimum of the population values. 
max 
The maximum of the population values. 
BucketOptions
BucketOptions
describes the bucket boundaries used to create a histogram for the distribution. The buckets can be in a linear sequence, an exponential sequence, or each bucket can be specified explicitly. BucketOptions
does not include the number of values in each bucket.
A bucket has an inclusive lower bound and exclusive upper bound for the values that are counted for that bucket. The upper bound of a bucket must be strictly greater than the lower bound. The sequence of N buckets for a distribution consists of an underflow bucket (number 0), zero or more finite buckets (number 1 through N  2) and an overflow bucket (number N  1). The buckets are contiguous: the lower bound of bucket i (i > 0) is the same as the upper bound of bucket i  1. The buckets span the whole range of finite values: lower bound of the underflow bucket is infinity and the upper bound of the overflow bucket is +infinity. The finite buckets are socalled because both bounds are finite.
JSON representation 

{ // Union field 
Fields  

Union field options . Exactly one of these three fields must be set. options can be only one of the following: 

linearBuckets 
The linear bucket. 
exponentialBuckets 
The exponential buckets. 
explicitBuckets 
The explicit buckets. 
Linear
Specifies a linear sequence of buckets that all have the same width (except overflow and underflow). Each bucket represents a constant absolute uncertainty on the specific value in the bucket.
There are numFiniteBuckets + 2
(= N) buckets. Bucket i
has the following boundaries:
Upper bound (0 <= i < N1): offset + (width * i).
Lower bound (1 <= i < N): offset + (width * (i  1)).
JSON representation 

{ "numFiniteBuckets": integer, "width": number, "offset": number } 
Fields  

numFiniteBuckets 
Must be greater than 0. 
width 
Must be greater than 0. 
offset 
Lower bound of the first bucket. 
Exponential
Specifies an exponential sequence of buckets that have a width that is proportional to the value of the lower bound. Each bucket represents a constant relative uncertainty on a specific value in the bucket.
There are numFiniteBuckets + 2
(= N) buckets. Bucket i
has the following boundaries:
Upper bound (0 <= i < N1): scale * (growthFactor ^ i).
Lower bound (1 <= i < N): scale * (growthFactor ^ (i  1)).
JSON representation 

{ "numFiniteBuckets": integer, "growthFactor": number, "scale": number } 
Fields  

numFiniteBuckets 
Must be greater than 0. 
growthFactor 
Must be greater than 1. 
scale 
Must be greater than 0. 
Explicit
Specifies a set of buckets with arbitrary widths.
There are size(bounds) + 1
(= N) buckets. Bucket i
has the following boundaries:
Upper bound (0 <= i < N1): bounds[i] Lower bound (1 <= i < N); bounds[i  1]
The bounds
field must contain at least one element. If bounds
has only one element, then there are no finite buckets, and that single element is the common boundary of the overflow and underflow buckets.
JSON representation 

{ "bounds": [ number ] } 
Fields  

bounds[] 
The values must be monotonically increasing. 
Exemplar
Exemplars are example points that may be used to annotate aggregated distribution values. They are metadata that gives information about a particular value added to a Distribution bucket, such as a trace ID that was active when a value was added. They may contain further information, such as a example values and timestamps, origin, etc.
JSON representation 

{ "value": number, "timestamp": string, "attachments": [ { "@type": string, field1: ..., ... } ] } 
Fields  

value 
Value of the exemplar point. This value determines to which bucket the exemplar belongs. 
timestamp 
The observation (sampling) time of the above value. 
attachments[] 
Contextual information about the example value. Examples are: Trace: type.googleapis.com/google.monitoring.v3.SpanContext Literal string: type.googleapis.com/google.protobuf.StringValue Labels dropped during aggregation: type.googleapis.com/google.monitoring.v3.DroppedLabels There may be only a single attachment of any given message type in a single exemplar, and this is enforced by the system. 