mirror of https://github.com/grpc/grpc.git
The C based gRPC (C++, Python, Ruby, Objective-C, PHP, C#)
https://grpc.io/
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319 lines
12 KiB
319 lines
12 KiB
8 years ago
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// Copyright 2017, Google Inc.
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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// http://www.apache.org/licenses/LICENSE-2.0
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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//TODO(ericgribkoff) Depend on this directly from the instrumentation-proto
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//repository.
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syntax = "proto3";
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package google.instrumentation;
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option java_package = "com.google.instrumentation.stats.proto";
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option java_outer_classname = "CensusProto";
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// All the census protos.
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//
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// Nomenclature notes:
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// * Capitalized names below (like View) are protos.
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// * Protos which describe types are named with a Descriptor suffix (e.g.
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// MesurementDescriptor).
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//
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// Census lets you define the type and description of the data being measured
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// (e.g. the latency of an RPC or the number of CPU cycles spent on an
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// operation using MeasurementDescriptor. As individual measurements (a double
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// value) for are recorded, they are aggregated together into an
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// Aggregation. There are two Aggregation types available: Distribution
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// (describes the distribution of all measurements, possibly with a histogram)
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// and IntervalStats (the count and mean of measurements across specified time
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// periods). An Aggregation is described by an AggregationDescriptor.
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//
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// You can define how your measurements (described by a MeasurementDescriptor)
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// are broken down by Tag values and which Aggregations to use through a
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// ViewDescriptor. The output (all measurements broken down by tag values into
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// specific Aggregations) is called a View.
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// The following two types are copied from
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// google/protobuf/{duration,timestamp}.proto. Ideally, we would be able to
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// import them, but this causes compilation issues on C-based systems
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// (e.g. https://koti.kapsi.fi/jpa/nanopb/), which cannot process the C++
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// headers generated from the standard protobuf distribution. See the relevant
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// proto files for full documentation of these types.
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message Duration {
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// Signed seconds of the span of time. Must be from -315,576,000,000
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// to +315,576,000,000 inclusive.
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int64 seconds = 1;
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// Signed fractions of a second at nanosecond resolution of the span
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// of time. Durations less than one second are represented with a 0
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// `seconds` field and a positive or negative `nanos` field. For durations
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// of one second or more, a non-zero value for the `nanos` field must be
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// of the same sign as the `seconds` field. Must be from -999,999,999
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// to +999,999,999 inclusive.
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int32 nanos = 2;
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}
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message Timestamp {
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// Represents seconds of UTC time since Unix epoch
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// 1970-01-01T00:00:00Z. Must be from from 0001-01-01T00:00:00Z to
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// 9999-12-31T23:59:59Z inclusive.
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int64 seconds = 1;
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// Non-negative fractions of a second at nanosecond resolution. Negative
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// second values with fractions must still have non-negative nanos values
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// that count forward in time. Must be from 0 to 999,999,999
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// inclusive.
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int32 nanos = 2;
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}
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// MeasurementDescriptor describes a data point (measurement) type.
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message MeasurementDescriptor {
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// A descriptive name, e.g. rpc_latency, cpu. Must be unique.
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string name = 1;
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// More detailed description of the resource, used in documentation.
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string description = 2;
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// Fundamental units of measurement supported by Census
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// TODO(aveitch): expand this to include other S.I. units?
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enum BasicUnit {
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UNKNOWN = 0; // Implementations should not use this
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SCALAR = 1; // Dimensionless
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BITS = 2; // A single bit
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BYTES = 3; // An 8-bit byte
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SECONDS = 4; // S.I. unit
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CORES = 5; // CPU core usage
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MAX_UNITS = 6; // Last defined value; implementations should only use
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// this for validation.
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}
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// MeasurementUnit lets you build compound units of the form
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// 10^n * (A * B * ...) / (X * Y * ...),
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// where the elements in the numerator and denominator are all BasicUnits. A
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// MeasurementUnit must have at least one BasicUnit in its numerator.
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//
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// To specify multiplication in the numerator or denominator, simply specify
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// multiple numerator or denominator fields. For example:
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//
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// - byte-seconds (i.e. bytes * seconds):
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// numerator: BYTES
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// numerator: SECS
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//
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// - events/sec^2 (i.e. rate of change of events/sec):
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// numerator: SCALAR
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// denominator: SECS
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// denominator: SECS
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//
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// To specify multiples (in power of 10) of units, specify a non-zero
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// 'power10' value, for example:
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//
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// - MB/s (i.e. megabytes / s):
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// power10: 6
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// numerator: BYTES
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// denominator: SECS
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//
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// - nanoseconds
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// power10: -9
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// numerator: SECS
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message MeasurementUnit {
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int32 power10 = 1;
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repeated BasicUnit numerators = 2;
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repeated BasicUnit denominators = 3;
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}
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// The units used by this type of measurement.
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MeasurementUnit unit = 3;
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}
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// An aggregation summarizes a series of individual measurements. There are
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// two types of aggregation (IntervalAggregation and DistributionAggregation),
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// unique types of each can be set using descriptors for each.
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// DistributionAggregation contains summary statistics for a population of
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// values and, optionally, a histogram representing the distribution of those
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// values across a specified set of histogram buckets, as defined in
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// DistributionAggregationDescriptor.bucket_bounds.
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//
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// The summary statistics are the count, mean, minimum, and the maximum of the
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// set of population of values.
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//
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// Although it is not forbidden, it is generally a bad idea to include
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// non-finite values (infinities or NaNs) in the population of values, as this
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// will render the `mean` field meaningless.
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message DistributionAggregation {
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// The number of values in the population. Must be non-negative.
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int64 count = 1;
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// The arithmetic mean of the values in the population. If `count` is zero
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// then this field must be zero.
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double mean = 2;
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// The sum of the values in the population. If `count` is zero then this
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// field must be zero.
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double sum = 3;
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// Describes a range of population values.
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message Range {
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// The minimum of the population values.
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double min = 1;
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// The maximum of the population values.
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double max = 2;
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}
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// The range of the population values. If `count` is zero, this field will not
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// be defined.
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Range range = 4;
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// A Distribution may optionally contain a histogram of the values in the
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// population. The histogram is given in `bucket_count` as counts of values
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// that fall into one of a sequence of non-overlapping buckets, as described
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// by `DistributionAggregationDescriptor.bucket_boundaries`. The sum of the
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// values in `bucket_counts` must equal the value in `count`.
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//
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// Bucket counts are given in order under the numbering scheme described
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// above (the underflow bucket has number 0; the finite buckets, if any,
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// have numbers 1 through N-2; the overflow bucket has number N-1).
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//
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// The size of `bucket_count` must be no greater than N as defined in
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// `bucket_boundaries`.
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//
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// Any suffix of trailing zero bucket_count fields may be omitted.
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repeated int64 bucket_counts = 5;
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// Tags associated with this DistributionAggregation. These will be filled
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// in based on the View specification.
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repeated Tag tags = 6;
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}
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message DistributionAggregationDescriptor {
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// A Distribution may optionally contain a histogram of the values in the
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// population. The bucket boundaries for that histogram are described by
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// `bucket_bounds`. This defines `size(bucket_bounds) + 1` (= N)
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// buckets. The boundaries for bucket index i are:
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//
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// [-infinity, bucket_bounds[i]) for i == 0
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// [bucket_bounds[i-1], bucket_bounds[i]) for 0 < i < N-2
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// [bucket_bounds[i-1], +infinity) for i == N-1
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//
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// i.e. an underflow bucket (number 0), zero or more finite buckets (1
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// through N - 2, and an overflow bucket (N - 1), with inclusive lower
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// bounds and exclusive upper bounds.
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//
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// If `bucket_bounds` has no elements (zero size), then there is no
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// histogram associated with the Distribution. If `bucket_bounds` has only
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// one element, there are no finite buckets, and that single element is the
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// common boundary of the overflow and underflow buckets. The values must
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// be monotonically increasing.
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repeated double bucket_bounds = 1;
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}
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// An IntervalAggreation records summary stats over various time
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// windows. These stats are approximate, with the degree of accuracy
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// controlled by setting the n_sub_intervals parameter in the
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// IntervalAggregationDescriptor.
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message IntervalAggregation {
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// Summary statistic over a single time interval.
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message Interval {
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// The interval duration. Must be positive.
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Duration interval_size = 1;
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// Approximate number of measurements recorded in this interval.
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double count = 2;
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// The cumulative sum of measurements in this interval.
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double sum = 3;
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}
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// Full set of intervals for this aggregation.
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repeated Interval intervals = 1;
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// Tags associated with this IntervalAggregation. These will be filled in
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// based on the View specification.
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repeated Tag tags = 2;
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}
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// An IntervalAggreationDescriptor specifies time intervals for an
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// IntervalAggregation.
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message IntervalAggregationDescriptor {
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// Number of internal sub-intervals to use when collecting stats for each
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// interval. The max error in interval measurements will be approximately
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// 1/n_sub_intervals (although in practice, this will only be approached in
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// the presence of very large and bursty workload changes), and underlying
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// memory usage will be roughly proportional to the value of this
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// field. Must be in the range [2, 20]. A value of 5 will be used if this is
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// unspecified.
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int32 n_sub_intervals = 1;
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// The size of each interval, as a time duration. Must have at least one
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// element.
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repeated Duration interval_sizes = 2;
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}
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// A Tag: key-value pair.
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message Tag {
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string key = 1;
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string value = 2;
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}
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// A ViewDescriptor specifies an AggregationDescriptor and a set of tag
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// keys. Views instantiated from this descriptor will contain Aggregations
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// broken down by the unique set of matching tag values for each measurement.
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message ViewDescriptor {
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// Name of view. Must be unique.
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string name = 1;
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// More detailed description, for documentation purposes.
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string description = 2;
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// Name of a MeasurementDescriptor to be used for this view.
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string measurement_descriptor_name = 3;
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// Aggregation type to associate with View.
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oneof aggregation {
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IntervalAggregationDescriptor interval_aggregation = 4;
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DistributionAggregationDescriptor distribution_aggregation = 5;
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}
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// Tag keys to match with a given measurement. If no keys are specified,
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// then all stats are recorded. Keys must be unique.
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repeated string tag_keys = 6;
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}
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// DistributionView contains all aggregations for a view specified using a
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// DistributionAggregationDescriptor.
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message DistributionView {
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// Aggregations - each will have a unique set of tag values for the tag_keys
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// associated with the corresponding View.
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repeated DistributionAggregation aggregations = 1;
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// Start and end timestamps over which aggregations was accumulated.
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Timestamp start = 2;
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Timestamp end = 3;
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}
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// IntervalView contains all aggregations for a view specified using a
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// IntervalAggregationDescriptor.
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message IntervalView {
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// Aggregations - each will have a unique set of tag values for the tag_keys
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// associated with the corresponding View.
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repeated IntervalAggregation aggregations = 1;
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}
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// A View contains the aggregations based on a ViewDescriptor.
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message View {
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// ViewDescriptor name associated with this set of View.
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string view_name = 1;
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oneof view {
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DistributionView distribution_view = 2;
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IntervalView interval_view = 3;
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}
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}
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