Reference documentation and code samples for the Cloud Logging V2 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
defbucket_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=
defbucket_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).
(::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=
defcount=(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.
value (::Google::Api::Distribution::Range) — If specified, contains the range of the population values. The field
must not be present if the count is zero.
Returns
(::Google::Api::Distribution::Range) — If specified, contains the range of the population values. The field
must not be present if the count is zero.
#sum_of_squared_deviation
defsum_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=
defsum_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.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-08-28 UTC."],[],[],null,["# Cloud Logging V2 API - Class Google::Api::Distribution (v1.3.0)\n\nVersion latestkeyboard_arrow_down\n\n- [1.3.0 (latest)](/ruby/docs/reference/google-cloud-logging-v2/latest/Google-Api-Distribution)\n- [1.2.1](/ruby/docs/reference/google-cloud-logging-v2/1.2.1/Google-Api-Distribution)\n- [1.1.0](/ruby/docs/reference/google-cloud-logging-v2/1.1.0/Google-Api-Distribution)\n- [1.0.1](/ruby/docs/reference/google-cloud-logging-v2/1.0.1/Google-Api-Distribution)\n- [0.13.0](/ruby/docs/reference/google-cloud-logging-v2/0.13.0/Google-Api-Distribution)\n- [0.12.2](/ruby/docs/reference/google-cloud-logging-v2/0.12.2/Google-Api-Distribution)\n- [0.11.0](/ruby/docs/reference/google-cloud-logging-v2/0.11.0/Google-Api-Distribution)\n- [0.10.1](/ruby/docs/reference/google-cloud-logging-v2/0.10.1/Google-Api-Distribution)\n- [0.9.0](/ruby/docs/reference/google-cloud-logging-v2/0.9.0/Google-Api-Distribution)\n- [0.8.1](/ruby/docs/reference/google-cloud-logging-v2/0.8.1/Google-Api-Distribution)\n- [0.7.0](/ruby/docs/reference/google-cloud-logging-v2/0.7.0/Google-Api-Distribution)\n- [0.6.0](/ruby/docs/reference/google-cloud-logging-v2/0.6.0/Google-Api-Distribution)\n- [0.5.6](/ruby/docs/reference/google-cloud-logging-v2/0.5.6/Google-Api-Distribution) \nReference documentation and code samples for the Cloud Logging V2 API class Google::Api::Distribution.\n\n`Distribution` contains summary statistics for a population of values. It\noptionally contains a histogram representing the distribution of those values\nacross a set of buckets.\n\n\nThe summary statistics are the count, mean, sum of the squared deviation from\nthe mean, the minimum, and the maximum of the set of population of values.\nThe histogram is based on a sequence of buckets and gives a count of values\nthat fall into each bucket. The boundaries of the buckets are given either\nexplicitly or by formulas for buckets of fixed or exponentially increasing\nwidths.\n\n\u003cbr /\u003e\n\nAlthough it is not forbidden, it is generally a bad idea to include\nnon-finite values (infinities or NaNs) in the population of values, as this\nwill render the `mean` and `sum_of_squared_deviation` fields meaningless. \n\nInherits\n--------\n\n- Object \n\nExtended By\n-----------\n\n- Google::Protobuf::MessageExts::ClassMethods \n\nIncludes\n--------\n\n- Google::Protobuf::MessageExts\n\nMethods\n-------\n\n### #bucket_counts\n\n def bucket_counts() -\u003e ::Array\u003c::Integer\u003e\n\n**Returns**\n\n- (::Array\\\u003c::Integer\\\u003e) --- 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.\n\n\n If present, `bucket_counts` should contain N values, where N is the number\n of buckets specified in `bucket_options`. If you supply fewer than N\n values, the remaining values are assumed to be 0.\n\n The order of the values in `bucket_counts` follows the bucket numbering\n schemes described for the three bucket types. The first value must be the\n count for the underflow bucket (number 0). The next N-2 values are the\n counts for the finite buckets (number 1 through N-2). The N'th value in\n `bucket_counts` is the count for the overflow bucket (number N-1).\n\n### #bucket_counts=\n\n def bucket_counts=(value) -\u003e ::Array\u003c::Integer\u003e\n\n**Parameter**\n\n- **value** (::Array\\\u003c::Integer\\\u003e) --- 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.\n\n\n If present, `bucket_counts` should contain N values, where N is the number\n of buckets specified in `bucket_options`. If you supply fewer than N\n values, the remaining values are assumed to be 0.\n\n The order of the values in `bucket_counts` follows the bucket numbering\n schemes described for the three bucket types. The first value must be the\n count for the underflow bucket (number 0). The next N-2 values are the\n counts for the finite buckets (number 1 through N-2). The N'th value in\n`bucket_counts` is the count for the overflow bucket (number N-1). \n**Returns**\n\n- (::Array\\\u003c::Integer\\\u003e) --- 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.\n\n\n If present, `bucket_counts` should contain N values, where N is the number\n of buckets specified in `bucket_options`. If you supply fewer than N\n values, the remaining values are assumed to be 0.\n\n The order of the values in `bucket_counts` follows the bucket numbering\n schemes described for the three bucket types. The first value must be the\n count for the underflow bucket (number 0). The next N-2 values are the\n counts for the finite buckets (number 1 through N-2). The N'th value in\n `bucket_counts` is the count for the overflow bucket (number N-1).\n\n### #bucket_options\n\n def bucket_options() -\u003e ::Google::Api::Distribution::BucketOptions\n\n**Returns**\n\n- ([::Google::Api::Distribution::BucketOptions](./Google-Api-Distribution-BucketOptions)) --- Defines the histogram bucket boundaries. If the distribution does not contain a histogram, then omit this field.\n\n### #bucket_options=\n\n def bucket_options=(value) -\u003e ::Google::Api::Distribution::BucketOptions\n\n**Parameter**\n\n- **value** ([::Google::Api::Distribution::BucketOptions](./Google-Api-Distribution-BucketOptions)) --- Defines the histogram bucket boundaries. If the distribution does not contain a histogram, then omit this field. \n**Returns**\n\n- ([::Google::Api::Distribution::BucketOptions](./Google-Api-Distribution-BucketOptions)) --- Defines the histogram bucket boundaries. If the distribution does not contain a histogram, then omit this field.\n\n### #count\n\n def count() -\u003e ::Integer\n\n**Returns**\n\n- (::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.\n\n### #count=\n\n def count=(value) -\u003e ::Integer\n\n**Parameter**\n\n- **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. \n**Returns**\n\n- (::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.\n\n### #exemplars\n\n def exemplars() -\u003e ::Array\u003c::Google::Api::Distribution::Exemplar\u003e\n\n**Returns**\n\n- (::Array\\\u003c[::Google::Api::Distribution::Exemplar](./Google-Api-Distribution-Exemplar)\\\u003e) --- Must be in increasing order of `value` field.\n\n### #exemplars=\n\n def exemplars=(value) -\u003e ::Array\u003c::Google::Api::Distribution::Exemplar\u003e\n\n**Parameter**\n\n- **value** (::Array\\\u003c[::Google::Api::Distribution::Exemplar](./Google-Api-Distribution-Exemplar)\\\u003e) --- Must be in increasing order of `value` field. \n**Returns**\n\n- (::Array\\\u003c[::Google::Api::Distribution::Exemplar](./Google-Api-Distribution-Exemplar)\\\u003e) --- Must be in increasing order of `value` field.\n\n### #mean\n\n def mean() -\u003e ::Float\n\n**Returns**\n\n- (::Float) --- The arithmetic mean of the values in the population. If `count` is zero then this field must be zero.\n\n### #mean=\n\n def mean=(value) -\u003e ::Float\n\n**Parameter**\n\n- **value** (::Float) --- The arithmetic mean of the values in the population. If `count` is zero then this field must be zero. \n**Returns**\n\n- (::Float) --- The arithmetic mean of the values in the population. If `count` is zero then this field must be zero.\n\n### #range\n\n def range() -\u003e ::Google::Api::Distribution::Range\n\n**Returns**\n\n- ([::Google::Api::Distribution::Range](./Google-Api-Distribution-Range)) --- If specified, contains the range of the population values. The field must not be present if the `count` is zero.\n\n### #range=\n\n def range=(value) -\u003e ::Google::Api::Distribution::Range\n\n**Parameter**\n\n- **value** ([::Google::Api::Distribution::Range](./Google-Api-Distribution-Range)) --- If specified, contains the range of the population values. The field must not be present if the `count` is zero. \n**Returns**\n\n- ([::Google::Api::Distribution::Range](./Google-Api-Distribution-Range)) --- If specified, contains the range of the population values. The field must not be present if the `count` is zero.\n\n### #sum_of_squared_deviation\n\n def sum_of_squared_deviation() -\u003e ::Float\n\n**Returns**\n\n- (::Float) --- The sum of squared deviations from the mean of the values in the population. For values x_i this is:\n\n Sum[i=1..n]((x_i - mean)^2)\n\n Knuth, \"The Art of Computer Programming\", Vol. 2, page 232, 3rd edition\n describes Welford's method for accumulating this sum in one pass.\n\n If `count` is zero then this field must be zero.\n\n### #sum_of_squared_deviation=\n\n def sum_of_squared_deviation=(value) -\u003e ::Float\n\n**Parameter**\n\n- **value** (::Float) --- The sum of squared deviations from the mean of the values in the population. For values x_i this is:\n\n\n Sum[i=1..n]((x_i - mean)^2)\n\n Knuth, \"The Art of Computer Programming\", Vol. 2, page 232, 3rd edition\n describes Welford's method for accumulating this sum in one pass.\n\nIf `count` is zero then this field must be zero. \n**Returns**\n\n- (::Float) --- The sum of squared deviations from the mean of the values in the population. For values x_i this is:\n\n Sum[i=1..n]((x_i - mean)^2)\n\n Knuth, \"The Art of Computer Programming\", Vol. 2, page 232, 3rd edition\n describes Welford's method for accumulating this sum in one pass.\n\n If `count` is zero then this field must be zero."]]
