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services: delete unused proto (#4604)

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Eric Gribkoff 2018-06-29 15:03:08 -07:00 committed by GitHub
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services/src/generated/main/java/com/google/instrumentation/stats/proto/CensusProto.java
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services/src/main/proto/google/instrumentation/census.proto
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// Copyright 2017 The gRPC Authors
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// This is copied from https://github.com/google/instrumentation-proto/.
// TODO(ericgribkoff) Sync this proto with grpc/grpc-proto.
syntax = "proto3";
package google.instrumentation;
option java_package = "com.google.instrumentation.stats.proto";
option java_outer_classname = "CensusProto";
// All the census protos.
//
// Nomenclature notes:
// * Capitalized names below (like View) are protos.
// * Protos which describe types are named with a Descriptor suffix (e.g.
// MesurementDescriptor).
//
// Census lets you define the type and description of the data being measured
// (e.g. the latency of an RPC or the number of CPU cycles spent on an
// operation using MeasurementDescriptor. As individual measurements (a double
// value) for are recorded, they are aggregated together into an
// Aggregation. There are two Aggregation types available: Distribution
// (describes the distribution of all measurements, possibly with a histogram)
// and IntervalStats (the count and mean of measurements across specified time
// periods). An Aggregation is described by an AggregationDescriptor.
//
// You can define how your measurements (described by a MeasurementDescriptor)
// are broken down by Tag values and which Aggregations to use through a
// ViewDescriptor. The output (all measurements broken down by tag values into
// specific Aggregations) is called a View.
// The following two types are copied from
// google/protobuf/{duration,timestamp}.proto. Ideally, we would be able to
// import them, but this causes compilation issues on C-based systems
// (e.g. https://koti.kapsi.fi/jpa/nanopb/), which cannot process the C++
// headers generated from the standard protobuf distribution. See the relevant
// proto files for full documentation of these types.
message Duration {
// Signed seconds of the span of time. Must be from -315,576,000,000
// to +315,576,000,000 inclusive.
int64 seconds = 1;
// Signed fractions of a second at nanosecond resolution of the span
// of time. Durations less than one second are represented with a 0
// `seconds` field and a positive or negative `nanos` field. For durations
// of one second or more, a non-zero value for the `nanos` field must be
// of the same sign as the `seconds` field. Must be from -999,999,999
// to +999,999,999 inclusive.
int32 nanos = 2;
}
message Timestamp {
// Represents seconds of UTC time since Unix epoch
// 1970-01-01T00:00:00Z. Must be from from 0001-01-01T00:00:00Z to
// 9999-12-31T23:59:59Z inclusive.
int64 seconds = 1;
// Non-negative fractions of a second at nanosecond resolution. Negative
// second values with fractions must still have non-negative nanos values
// that count forward in time. Must be from 0 to 999,999,999
// inclusive.
int32 nanos = 2;
}
// MeasurementDescriptor describes a data point (measurement) type.
message MeasurementDescriptor {
// A descriptive name, e.g. rpc_latency, cpu. Must be unique.
string name = 1;
// More detailed description of the resource, used in documentation.
string description = 2;
// Fundamental units of measurement supported by Census
// TODO(aveitch): expand this to include other S.I. units?
enum BasicUnit {
UNKNOWN = 0; // Implementations should not use this
SCALAR = 1; // Dimensionless
BITS = 2; // A single bit
BYTES = 3; // An 8-bit byte
SECONDS = 4; // S.I. unit
CORES = 5; // CPU core usage
MAX_UNITS = 6; // Last defined value; implementations should only use
// this for validation.
}
// MeasurementUnit lets you build compound units of the form
// 10^n * (A * B * ...) / (X * Y * ...),
// where the elements in the numerator and denominator are all BasicUnits. A
// MeasurementUnit must have at least one BasicUnit in its numerator.
//
// To specify multiplication in the numerator or denominator, simply specify
// multiple numerator or denominator fields. For example:
//
// - byte-seconds (i.e. bytes * seconds):
// numerator: BYTES
// numerator: SECS
//
// - events/sec^2 (i.e. rate of change of events/sec):
// numerator: SCALAR
// denominator: SECS
// denominator: SECS
//
// To specify multiples (in power of 10) of units, specify a non-zero
// 'power10' value, for example:
//
// - MB/s (i.e. megabytes / s):
// power10: 6
// numerator: BYTES
// denominator: SECS
//
// - nanoseconds
// power10: -9
// numerator: SECS
message MeasurementUnit {
int32 power10 = 1;
repeated BasicUnit numerators = 2;
repeated BasicUnit denominators = 3;
}
// The units used by this type of measurement.
MeasurementUnit unit = 3;
}
// An aggregation summarizes a series of individual measurements. There are
// two types of aggregation (IntervalAggregation and DistributionAggregation),
// unique types of each can be set using descriptors for each.
// DistributionAggregation contains summary statistics for a population of
// values and, optionally, a histogram representing the distribution of those
// values across a specified set of histogram buckets, as defined in
// DistributionAggregationDescriptor.bucket_bounds.
//
// The summary statistics are the count, mean, minimum, and the maximum of the
// set of population of values.
//
// 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` field meaningless.
message DistributionAggregation {
// The number of values in the population. Must be non-negative.
int64 count = 1;
// The arithmetic mean of the values in the population. If `count` is zero
// then this field must be zero.
double mean = 2;
// The sum of the values in the population. If `count` is zero then this
// field must be zero.
double sum = 3;
// Describes a range of population values.
message Range {
// The minimum of the population values.
double min = 1;
// The maximum of the population values.
double max = 2;
}
// The range of the population values. If `count` is zero, this field will not
// be defined.
Range range = 4;
// A Distribution may optionally contain a histogram of the values in the
// population. The histogram is given in `bucket_count` as counts of values
// that fall into one of a sequence of non-overlapping buckets, as described
// by `DistributionAggregationDescriptor.bucket_boundaries`. The sum of the
// values in `bucket_counts` must equal the value in `count`.
//
// Bucket counts are given in order under the numbering scheme described
// above (the underflow bucket has number 0; the finite buckets, if any,
// have numbers 1 through N-2; the overflow bucket has number N-1).
//
// The size of `bucket_count` must be no greater than N as defined in
// `bucket_boundaries`.
//
// Any suffix of trailing zero bucket_count fields may be omitted.
repeated int64 bucket_counts = 5;
// Tags associated with this DistributionAggregation. These will be filled
// in based on the View specification.
repeated Tag tags = 6;
}
message DistributionAggregationDescriptor {
// A Distribution may optionally contain a histogram of the values in the
// population. The bucket boundaries for that histogram are described by
// `bucket_bounds`. This defines `size(bucket_bounds) + 1` (= N)
// buckets. The boundaries for bucket index i are:
//
// [-infinity, bucket_bounds[i]) for i == 0
// [bucket_bounds[i-1], bucket_bounds[i]) for 0 < i < N-2
// [bucket_bounds[i-1], +infinity) for i == N-1
//
// i.e. an underflow bucket (number 0), zero or more finite buckets (1
// through N - 2, and an overflow bucket (N - 1), with inclusive lower
// bounds and exclusive upper bounds.
//
// If `bucket_bounds` has no elements (zero size), then there is no
// histogram associated with the Distribution. If `bucket_bounds` has only
// one element, there are no finite buckets, and that single element is the
// common boundary of the overflow and underflow buckets. The values must
// be monotonically increasing.
repeated double bucket_bounds = 1;
}
// An IntervalAggreation records summary stats over various time
// windows. These stats are approximate, with the degree of accuracy
// controlled by setting the n_sub_intervals parameter in the
// IntervalAggregationDescriptor.
message IntervalAggregation {
// Summary statistic over a single time interval.
message Interval {
// The interval duration. Must be positive.
Duration interval_size = 1;
// Approximate number of measurements recorded in this interval.
double count = 2;
// The cumulative sum of measurements in this interval.
double sum = 3;
}
// Full set of intervals for this aggregation.
repeated Interval intervals = 1;
// Tags associated with this IntervalAggregation. These will be filled in
// based on the View specification.
repeated Tag tags = 2;
}
// An IntervalAggreationDescriptor specifies time intervals for an
// IntervalAggregation.
message IntervalAggregationDescriptor {
// Number of internal sub-intervals to use when collecting stats for each
// interval. The max error in interval measurements will be approximately
// 1/n_sub_intervals (although in practice, this will only be approached in
// the presence of very large and bursty workload changes), and underlying
// memory usage will be roughly proportional to the value of this
// field. Must be in the range [2, 20]. A value of 5 will be used if this is
// unspecified.
int32 n_sub_intervals = 1;
// The size of each interval, as a time duration. Must have at least one
// element.
repeated Duration interval_sizes = 2;
}
// A Tag: key-value pair.
message Tag {
string key = 1;
string value = 2;
}
// A ViewDescriptor specifies an AggregationDescriptor and a set of tag
// keys. Views instantiated from this descriptor will contain Aggregations
// broken down by the unique set of matching tag values for each measurement.
message ViewDescriptor {
// Name of view. Must be unique.
string name = 1;
// More detailed description, for documentation purposes.
string description = 2;
// Name of a MeasurementDescriptor to be used for this view.
string measurement_descriptor_name = 3;
// Aggregation type to associate with View.
oneof aggregation {
IntervalAggregationDescriptor interval_aggregation = 4;
DistributionAggregationDescriptor distribution_aggregation = 5;
}
// Tag keys to match with a given measurement. If no keys are specified,
// then all stats are recorded. Keys must be unique.
repeated string tag_keys = 6;
}
// DistributionView contains all aggregations for a view specified using a
// DistributionAggregationDescriptor.
message DistributionView {
// Aggregations - each will have a unique set of tag values for the tag_keys
// associated with the corresponding View.
repeated DistributionAggregation aggregations = 1;
// Start and end timestamps over which aggregations was accumulated.
Timestamp start = 2;
Timestamp end = 3;
}
// IntervalView contains all aggregations for a view specified using a
// IntervalAggregationDescriptor.
message IntervalView {
// Aggregations - each will have a unique set of tag values for the tag_keys
// associated with the corresponding View.
repeated IntervalAggregation aggregations = 1;
}
// A View contains the aggregations based on a ViewDescriptor.
message View {
// ViewDescriptor name associated with this set of View.
string view_name = 1;
oneof view {
DistributionView distribution_view = 2;
IntervalView interval_view = 3;
}
}