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Diffstat (limited to 'third_party/googleapis/google/monitoring/v3/common.proto')
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diff --git a/third_party/googleapis/google/monitoring/v3/common.proto b/third_party/googleapis/google/monitoring/v3/common.proto new file mode 100644 index 0000000000..c8f701eeaa --- /dev/null +++ b/third_party/googleapis/google/monitoring/v3/common.proto @@ -0,0 +1,323 @@ +// Copyright 2016 Google Inc. +// +// 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. + +syntax = "proto3"; + +package google.monitoring.v3; + +import "google/api/distribution.proto"; +import "google/protobuf/duration.proto"; +import "google/protobuf/timestamp.proto"; + +option csharp_namespace = "Google.Cloud.Monitoring.V3"; +option go_package = "google.golang.org/genproto/googleapis/monitoring/v3;monitoring"; +option java_multiple_files = true; +option java_outer_classname = "CommonProto"; +option java_package = "com.google.monitoring.v3"; + + +// A single strongly-typed value. +message TypedValue { + // The typed value field. + oneof value { + // A Boolean value: `true` or `false`. + bool bool_value = 1; + + // A 64-bit integer. Its range is approximately ±9.2x10<sup>18</sup>. + int64 int64_value = 2; + + // A 64-bit double-precision floating-point number. Its magnitude + // is approximately ±10<sup>±300</sup> and it has 16 + // significant digits of precision. + double double_value = 3; + + // A variable-length string value. + string string_value = 4; + + // A distribution value. + google.api.Distribution distribution_value = 5; + } +} + +// A time interval extending just after a start time through an end time. +// If the start time is the same as the end time, then the interval +// represents a single point in time. +message TimeInterval { + // Required. The end of the time interval. + google.protobuf.Timestamp end_time = 2; + + // Optional. The beginning of the time interval. The default value + // for the start time is the end time. The start time must not be + // later than the end time. + google.protobuf.Timestamp start_time = 1; +} + +// Describes how to combine multiple time series to provide different views of +// the data. Aggregation consists of an alignment step on individual time +// series (`per_series_aligner`) followed by an optional reduction of the data +// across different time series (`cross_series_reducer`). For more details, see +// [Aggregation](/monitoring/api/learn_more#aggregation). +message Aggregation { + // The Aligner describes how to bring the data points in a single + // time series into temporal alignment. + enum Aligner { + // No alignment. Raw data is returned. Not valid if cross-time + // series reduction is requested. The value type of the result is + // the same as the value type of the input. + ALIGN_NONE = 0; + + // Align and convert to delta metric type. This alignment is valid + // for cumulative metrics and delta metrics. Aligning an existing + // delta metric to a delta metric requires that the alignment + // period be increased. The value type of the result is the same + // as the value type of the input. + ALIGN_DELTA = 1; + + // Align and convert to a rate. This alignment is valid for + // cumulative metrics and delta metrics with numeric values. The output is a + // gauge metric with value type + // [DOUBLE][google.api.MetricDescriptor.ValueType.DOUBLE]. + ALIGN_RATE = 2; + + // Align by interpolating between adjacent points around the + // period boundary. This alignment is valid for gauge + // metrics with numeric values. The value type of the result is the same + // as the value type of the input. + ALIGN_INTERPOLATE = 3; + + // Align by shifting the oldest data point before the period + // boundary to the boundary. This alignment is valid for gauge + // metrics. The value type of the result is the same as the + // value type of the input. + ALIGN_NEXT_OLDER = 4; + + // Align time series via aggregation. The resulting data point in + // the alignment period is the minimum of all data points in the + // period. This alignment is valid for gauge and delta metrics with numeric + // values. The value type of the result is the same as the value + // type of the input. + ALIGN_MIN = 10; + + // Align time series via aggregation. The resulting data point in + // the alignment period is the maximum of all data points in the + // period. This alignment is valid for gauge and delta metrics with numeric + // values. The value type of the result is the same as the value + // type of the input. + ALIGN_MAX = 11; + + // Align time series via aggregation. The resulting data point in + // the alignment period is the average or arithmetic mean of all + // data points in the period. This alignment is valid for gauge and delta + // metrics with numeric values. The value type of the output is + // [DOUBLE][google.api.MetricDescriptor.ValueType.DOUBLE]. + ALIGN_MEAN = 12; + + // Align time series via aggregation. The resulting data point in + // the alignment period is the count of all data points in the + // period. This alignment is valid for gauge and delta metrics with numeric + // or Boolean values. The value type of the output is + // [INT64][google.api.MetricDescriptor.ValueType.INT64]. + ALIGN_COUNT = 13; + + // Align time series via aggregation. The resulting data point in + // the alignment period is the sum of all data points in the + // period. This alignment is valid for gauge and delta metrics with numeric + // and distribution values. The value type of the output is the + // same as the value type of the input. + ALIGN_SUM = 14; + + // Align time series via aggregation. The resulting data point in + // the alignment period is the standard deviation of all data + // points in the period. This alignment is valid for gauge and delta metrics + // with numeric values. The value type of the output is + // [DOUBLE][google.api.MetricDescriptor.ValueType.DOUBLE]. + ALIGN_STDDEV = 15; + + // Align time series via aggregation. The resulting data point in + // the alignment period is the count of True-valued data points in the + // period. This alignment is valid for gauge metrics with + // Boolean values. The value type of the output is + // [INT64][google.api.MetricDescriptor.ValueType.INT64]. + ALIGN_COUNT_TRUE = 16; + + // Align time series via aggregation. The resulting data point in + // the alignment period is the fraction of True-valued data points in the + // period. This alignment is valid for gauge metrics with Boolean values. + // The output value is in the range [0, 1] and has value type + // [DOUBLE][google.api.MetricDescriptor.ValueType.DOUBLE]. + ALIGN_FRACTION_TRUE = 17; + + // Align time series via aggregation. The resulting data point in + // the alignment period is the 99th percentile of all data + // points in the period. This alignment is valid for gauge and delta metrics + // with distribution values. The output is a gauge metric with value type + // [DOUBLE][google.api.MetricDescriptor.ValueType.DOUBLE]. + ALIGN_PERCENTILE_99 = 18; + + // Align time series via aggregation. The resulting data point in + // the alignment period is the 95th percentile of all data + // points in the period. This alignment is valid for gauge and delta metrics + // with distribution values. The output is a gauge metric with value type + // [DOUBLE][google.api.MetricDescriptor.ValueType.DOUBLE]. + ALIGN_PERCENTILE_95 = 19; + + // Align time series via aggregation. The resulting data point in + // the alignment period is the 50th percentile of all data + // points in the period. This alignment is valid for gauge and delta metrics + // with distribution values. The output is a gauge metric with value type + // [DOUBLE][google.api.MetricDescriptor.ValueType.DOUBLE]. + ALIGN_PERCENTILE_50 = 20; + + // Align time series via aggregation. The resulting data point in + // the alignment period is the 5th percentile of all data + // points in the period. This alignment is valid for gauge and delta metrics + // with distribution values. The output is a gauge metric with value type + // [DOUBLE][google.api.MetricDescriptor.ValueType.DOUBLE]. + ALIGN_PERCENTILE_05 = 21; + } + + // A Reducer describes how to aggregate data points from multiple + // time series into a single time series. + enum Reducer { + // No cross-time series reduction. The output of the aligner is + // returned. + REDUCE_NONE = 0; + + // Reduce by computing the mean across time series for each + // alignment period. This reducer is valid for delta and + // gauge metrics with numeric or distribution values. The value type of the + // output is [DOUBLE][google.api.MetricDescriptor.ValueType.DOUBLE]. + REDUCE_MEAN = 1; + + // Reduce by computing the minimum across time series for each + // alignment period. This reducer is valid for delta and + // gauge metrics with numeric values. The value type of the output + // is the same as the value type of the input. + REDUCE_MIN = 2; + + // Reduce by computing the maximum across time series for each + // alignment period. This reducer is valid for delta and + // gauge metrics with numeric values. The value type of the output + // is the same as the value type of the input. + REDUCE_MAX = 3; + + // Reduce by computing the sum across time series for each + // alignment period. This reducer is valid for delta and + // gauge metrics with numeric and distribution values. The value type of + // the output is the same as the value type of the input. + REDUCE_SUM = 4; + + // Reduce by computing the standard deviation across time series + // for each alignment period. This reducer is valid for delta + // and gauge metrics with numeric or distribution values. The value type of + // the output is [DOUBLE][google.api.MetricDescriptor.ValueType.DOUBLE]. + REDUCE_STDDEV = 5; + + // Reduce by computing the count of data points across time series + // for each alignment period. This reducer is valid for delta + // and gauge metrics of numeric, Boolean, distribution, and string value + // type. The value type of the output is + // [INT64][google.api.MetricDescriptor.ValueType.INT64]. + REDUCE_COUNT = 6; + + // Reduce by computing the count of True-valued data points across time + // series for each alignment period. This reducer is valid for delta + // and gauge metrics of Boolean value type. The value type of + // the output is [INT64][google.api.MetricDescriptor.ValueType.INT64]. + REDUCE_COUNT_TRUE = 7; + + // Reduce by computing the fraction of True-valued data points across time + // series for each alignment period. This reducer is valid for delta + // and gauge metrics of Boolean value type. The output value is in the + // range [0, 1] and has value type + // [DOUBLE][google.api.MetricDescriptor.ValueType.DOUBLE]. + REDUCE_FRACTION_TRUE = 8; + + // Reduce by computing 99th percentile of data points across time series + // for each alignment period. This reducer is valid for gauge and delta + // metrics of numeric and distribution type. The value of the output is + // [DOUBLE][google.api.MetricDescriptor.ValueType.DOUBLE] + REDUCE_PERCENTILE_99 = 9; + + // Reduce by computing 95th percentile of data points across time series + // for each alignment period. This reducer is valid for gauge and delta + // metrics of numeric and distribution type. The value of the output is + // [DOUBLE][google.api.MetricDescriptor.ValueType.DOUBLE] + REDUCE_PERCENTILE_95 = 10; + + // Reduce by computing 50th percentile of data points across time series + // for each alignment period. This reducer is valid for gauge and delta + // metrics of numeric and distribution type. The value of the output is + // [DOUBLE][google.api.MetricDescriptor.ValueType.DOUBLE] + REDUCE_PERCENTILE_50 = 11; + + // Reduce by computing 5th percentile of data points across time series + // for each alignment period. This reducer is valid for gauge and delta + // metrics of numeric and distribution type. The value of the output is + // [DOUBLE][google.api.MetricDescriptor.ValueType.DOUBLE] + REDUCE_PERCENTILE_05 = 12; + } + + // The alignment period for per-[time series][google.monitoring.v3.TimeSeries] + // alignment. If present, `alignmentPeriod` must be at least 60 + // seconds. After per-time series alignment, each time series will + // contain data points only on the period boundaries. If + // `perSeriesAligner` is not specified or equals `ALIGN_NONE`, then + // this field is ignored. If `perSeriesAligner` is specified and + // does not equal `ALIGN_NONE`, then this field must be defined; + // otherwise an error is returned. + google.protobuf.Duration alignment_period = 1; + + // The approach to be used to align individual time series. Not all + // alignment functions may be applied to all time series, depending + // on the metric type and value type of the original time + // series. Alignment may change the metric type or the value type of + // the time series. + // + // Time series data must be aligned in order to perform cross-time + // series reduction. If `crossSeriesReducer` is specified, then + // `perSeriesAligner` must be specified and not equal `ALIGN_NONE` + // and `alignmentPeriod` must be specified; otherwise, an error is + // returned. + Aligner per_series_aligner = 2; + + // The approach to be used to combine time series. Not all reducer + // functions may be applied to all time series, depending on the + // metric type and the value type of the original time + // series. Reduction may change the metric type of value type of the + // time series. + // + // Time series data must be aligned in order to perform cross-time + // series reduction. If `crossSeriesReducer` is specified, then + // `perSeriesAligner` must be specified and not equal `ALIGN_NONE` + // and `alignmentPeriod` must be specified; otherwise, an error is + // returned. + Reducer cross_series_reducer = 4; + + // The set of fields to preserve when `crossSeriesReducer` is + // specified. The `groupByFields` determine how the time series are + // partitioned into subsets prior to applying the aggregation + // function. Each subset contains time series that have the same + // value for each of the grouping fields. Each individual time + // series is a member of exactly one subset. The + // `crossSeriesReducer` is applied to each subset of time series. + // It is not possible to reduce across different resource types, so + // this field implicitly contains `resource.type`. Fields not + // specified in `groupByFields` are aggregated away. If + // `groupByFields` is not specified and all the time series have + // the same resource type, then the time series are aggregated into + // a single output time series. If `crossSeriesReducer` is not + // defined, this field is ignored. + repeated string group_by_fields = 5; +} |