android-15.0.0_r3/s

// Copyright 2023 Google LLC
//
// 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 cobalt;

import "window_size.proto";

option java_multiple_files = true;
option java_package = "com.google.cobalt";

////////////////////////////////////////////////////////////////////////////////
// NOTE: This file is used by the Cobalt client and the Cobalt servers.
// The source-of-truth of this file is located in Cobalt's open source code
// repository, and the file is copied to Android where it is used by the Cobalt
// client. Do not edit the copy of this file in this Android repo as those edits
// will be overwritten when the file is next copied.
////////////////////////////////////////////////////////////////////////////////

// A Report analyzes Events that were logged to Cobalt and emits an aggregated
// output that may then be queried or visualized by an analyst user of Cobalt.
//
// A Report is associated with a Metric and this means that the Report analyzes
// the Events that were logged to that Metric. The first step occurs on a
// device where Cobalt analyzes the logged Events in order to form Observations.
//
// An Observation is built for a particular Report. The type of observation,
// including which of several privacy-oriented Encodings is used or not, depends
// on the Report type.
//
// The Observations are sent to the Cobalt Shuffler which shuffles them in order
// to break linkability between Observations and linkability with the
// originating device. Next the shuffled Observations are sent to the Analyzer
// which aggregates Observations from all devices in order to generate a report.
//
// There are multiple types of Metrics and multiple types of Reports. Each
// Report type is compatible with only some of the Metric types.
//
// A ReportDefinition defines a Cobalt Report to be generated.
// An instance of ReportDefinition is always associated with an instance of
// MetricDefinition called the owning MetricDefinition.
// Next ID: 33
message ReportDefinition {
  reserved 4, 5, 6, 7, 8, 9, 11, 14, 15, 16, 12, 101, 102, 31, 21;
  reserved "aggregation_type", "aggregation_window", "candidate_lis", "dp_release_config",
      "expected_population_size", "expected_string_set_size", "export_location_override",
      "local_privacy_noise_level", "output_location", "percentiles", "threshold", "window_size",
      "use_poisson_mechanism_for_privacy", "prob_bit_flip", "candidate_file";

  // Unique name for this Report within its owning MetricDefinition.
  // The name must obey the syntax of a C variable name and must have length
  // at most 64. The integer |id| field is the stable identifier for a report
  // so this name may be changed. However doing this may affect the
  // names and locations of some artifacts produced by Cobalt's report
  // generation pipeline.
  string report_name = 1;

  // The unique integer ID for this report within its owning metric.
  // The user must manually set this |id| field. This is the stable identifier
  // for a report and should not be changed once data collection begins.
  uint32 id = 2;

  // A Report has one of the following types.
  // Next standard report type ID: 22
  enum ReportType {
    reserved 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 19, 9999;
    reserved "CUSTOM_RAW_DUMP", "EVENT_COMPONENT_OCCURRENCE_COUNT", "HIGH_FREQUENCY_STRING_COUNTS",
        "INT_RANGE_HISTOGRAM", "NUMERIC_AGGREGATION", "NUMERIC_PERF_RAW_DUMP",
        "PER_DEVICE_HISTOGRAM", "PER_DEVICE_NUMERIC_STATS", "SIMPLE_OCCURRENCE_COUNT",
        "STRING_COUNTS_WITH_THRESHOLD", "STRING_HISTOGRAMS", "UNIQUE_N_DAY_ACTIVES";

    REPORT_TYPE_UNSET = 0;

    // For each system_profile SP and each event_vector EV, produces the total
    // count of all occurrences on all devices in the fleet with system profile
    // SP of the event associated with EV over the course of the report day.
    // For example, a report of this type might give the total number of times
    // a medium, red widget was used across the fleet yesterday.
    //
    // Input metric types: OCCURRENCE
    //
    // Local aggregation: COUNT
    // Local aggregation period: 1 hour
    // Global aggregation: OCCURRENCE_COUNTS
    // System Profile Selection Policy: REPORT_ALL
    //
    // Output report row type: OccurrenceCountReportRow
    // (See report_row.proto)
    //
    // ReportDefinition fields particular to this type:
    //    none
    FLEETWIDE_OCCURRENCE_COUNTS = 11;

    // For each system_profile SP and each event_vector EV, produces the count
    // of the number of unique devices with system profile SP for which EV
    // “is accepted” during the aggregation period, which must be DAYS_1,
    // DAYS_7, DAYS_28 or DAYS_30.
    //
    // There are different versions of what “is accepted” means depending on
    // which local aggregation procedure is specified:
    //
    // AT_LEAST_ONCE. In this case EV is accepted if EV was logged at least once
    // during the aggregation period. For example, a report of this type might
    // give the total number of devices with system profile SP on which a
    // medium, red widget was used at least once in the seven-day period
    // ending yesterday.
    //
    // SELECT_FIRST, SELECT_MOST_COMMON. In this case EV is accepted if the
    // category selection procedure selected EV. For example, a report of this
    // type using SELECT_MOST_COMMON might give the total number of devices
    // with system profile SP on which most of the widgets used during the
    // seven-day period ending yesterday were medium-red.
    //
    // NOTE: Using a local aggregation procedure of AT_LEAST_ONCE or
    // SELECT_FIRST, in combination with setting expedited_sending, results in
    // the count being sent by the device when the event occurs (instead of at
    // the end of the day). This can be desirable for having data for the
    // current day appear faster in the reports output by Cobalt.
    //
    // Input metric types: OCCURRENCE
    //
    // Local aggregation: AT_LEAST_ONCE, SELECT_FIRST, or SELECT_MOST_COMMON
    // Local aggregation period: DAYS_1, DAYS_7, DAYS_28 or DAYS_30.
    // Global aggregation: OCCURRENCE_COUNTS
    //
    // Output report row type: OccurrenceCountReportRow
    // (See report_row.proto)
    //
    // ReportDefinition fields particular to this type:
    //   - local_aggregation_procedure
    //   - local_aggregation_period
    //   - expedited_sending
    //   - system_profile_selection (SELECT_FIRST and SELECT LAST will maintain
    //     uniqueness, REPORT_ALL may be useful in some cases)
    UNIQUE_DEVICE_COUNTS = 12;

    // For each system_profile SP and each event_vector EV, produces an
    // int-range histogram such that in each int range bucket it gives the
    // number of unique devices with system_profile SP for which an integer
    // value, aggregated locally on device over the aggregation period,
    // associated with EV, falls into the bucket.
    //
    // There are two versions of this depending on the metric type:
    //
    // With metrics of type OCCURRENCE the integer values are occurrence counts.
    // For example, for the integer bucket 10-100, a report of this type might
    // give the number of devices with system profile SP on which a medium,
    // red widget was used between 10 and 100 times in the seven-day period
    // ending yesterday.
    //
    // With metrics of type INTEGER the integer values are computed statistics.
    // For example, for the integer bucket 10-100, a report of this type that
    // specifies the MINIMUM local aggregation procedure might give the number
    // of devices with system profile SP on which the minimum temperature of a
    // medium red widget over the seven-day period ending yesterday was between
    // 10 and 100 degrees.
    //
    // Input metric types: OCCURRENCE or INTEGER
    //
    // Local aggregation: COUNT_AS_INTEGER (used with OCCURRENCE metrics) or
    //                    NUMERIC_STAT (used with INTEGER metrics)
    // Local aggregation period: DAYS_1, DAYS_7, DAYS_28 or DAYS_30.
    // Global aggregation: INTEGER_HISTOGRAMS
    //
    // Output report row type: IntegerHistogramReportRow
    // (See report_row.proto)
    //
    // ReportDefinition fields particular to this type:
    //   - local_aggregation_procedure (only when the metric type is INTEGER)
    //   - local_aggregation_period
    //   - int_buckets (this is used only on the server for reports without
    //     added privacy, but is used on the client for reports with added
    //     privacy)
    //   - system_profile_selection (SELECT_FIRST and SELECT LAST will maintain
    //     uniqueness, REPORT_ALL may be useful in some cases)
    UNIQUE_DEVICE_HISTOGRAMS = 13;

    // For each system_profile SP and each event_vector EV, produces an
    // int-range histogram such that in each int range bucket it gives the
    // number of values, associated with EV, from devices
    // with system_profile SP, that fall into the bucket, where each device
    // computes one such value per hour.
    //
    // Computationally this report type is identical to
    // UNQIQUE_DEVICE_HISTOGRAMS except that the local aggregation period
    // used is one hour and so the counts in each buckets are not interpreted
    // as a number of unique devices.
    //
    // There are two versions of this depending on the metric type:
    //
    // With metrics of type OCCURRENCE the integer values are occurrence counts.
    // For example, for the integer bucket 10-100, a report of this type might
    // give the number of times that the hourly count of medium red widgets
    // used was between 10 and 100 over devices with system profile SP,
    // yesterday.
    //
    // With metrics of type INTEGER the integer values are computed statistics.
    // For example, for the integer bucket 10-100, a report of this that
    // specifies the MINIMUM local aggregation procedure might give the number
    // of times that the minimum temperature over an hour of all medium red
    // widgets used was between 10 and 100 degrees over all devices with
    // system profile SP, yesterday.
    //
    // Input metric types: OCCURRENCE or INTEGER
    //
    // Local aggregation: COUNT_AS_INTEGER (used with OCCURRENCE metrics) or
    //                    NUMERIC_STAT (used with INTEGER metrics)
    // Local aggregation period: one hour
    // Global aggregation: INTEGER_HISTOGRAMS
    //
    // Output report row type: IntegerHistogramReportRow
    // (See report_row.proto)
    //
    // ReportDefinition fields particular to this type:
    //   - local_aggregation_procedure (only when the metric type is INTEGER)
    //   - int_buckets (this is used only on the server for reports without
    //     added privacy, but is used on the client for reports with added
    //     privacy)
    //   - system_profile_selection (SELECT_FIRST and SELECT LAST will maintain
    //     uniqueness, REPORT_ALL may be useful in some cases)
    HOURLY_VALUE_HISTOGRAMS = 14;

    // For each system_profile SP and each event_vector EV, produces an
    // int-range histogram such that in each int range bucket it gives the
    // number of integer measurements, associated with EV, logged on devices
    // with system_profile SP, that fall into the bucket. Here we are counting
    // each value logged by the instrumented code individually and so the rate
    // at which values are being recorded is arbitrary and varies from device
    // to device. For example, for the integer bucket 10-100, a report of this
    // type might give the number of times that a medium red widget's
    // temperature was measured as being between 10 and 100 degrees over all
    // devices with system profile SP, yesterday. The rate at which these
    // widget temperature measurements are taken is arbitrary and may vary
    // from device to device.
    //
    // Input metric types: INTEGER or INTEGER_HISTOGRAM
    //
    // Local aggregation: INTEGER_HISTOGRAM
    // Local aggregation period: one hour
    // Global aggregation: INTEGER_HISTOGRAMS
    // System Profile Selection Policy: REPORT_ALL
    //
    // Output report row type: IntegerHistogramReportRow
    // (See report_row.proto)
    //
    // ReportDefinition fields particular to this type:
    //   - int_buckets (Only with metric_type = INTEGER)
    FLEETWIDE_HISTOGRAMS = 15;

    // For each system_profile SP and each event_vector EV, produces the sum
    // and count of many integer measurements associated with EV, logged on
    // devices with system_profile SP. Here we are counting each value logged
    // by the instrumented code individually and so the rate at which values are
    // being recorded is arbitrary and varies from device to device. This allows
    // us to  produce a fleetwide mean. For example, a report of this type might
    // give the mean of all temperature measurements of medium-red widgets
    // yesterday, across all devices with system profile SP, regardless of how
    // many temperature measurements were taken on each device individually.
    //
    // Input metric types: INTEGER
    //
    // Local aggregation: SUM_AND_COUNT
    // Local aggregation period: one hour
    // Global aggregation: SUM_AND_COUNTS
    // System Profile Selection Policy: REPORT_ALL
    //
    // Output report row type: SumAndCountReportRow
    // (See report_row.proto)
    //
    // ReportDefinition fields particular to this type:
    //   none
    FLEETWIDE_MEANS = 16;

    // For each system_profile SP and each event_vector EV, produces several
    // numeric statistics (e.g. 95%-ile) over a set of integers associated
    // with EV, collected from all devices with system_profile SP. Each unique
    // device contributes a single value and so the distribution of the values
    // may be thought of as a distribution of unique devices.
    //
    // There are different versions of this depending on the metric type:
    //
    // With metrics of type OCCURRENCE the integer values are occurrence counts
    // over the course of the aggregation period. For example a report of this
    // type might give the 95%-ile of the counts of medium-red widgets used by
    // each device over the 7-day period ending yesterday.
    //
    // With metrics of type INTEGER the integer values are computed statistics.
    // For example, a report of this type that specifies the MINIMUM local
    // aggregation procedure might give the 95%-ile of the minimum temperature
    // over the 7-day period ending yesterday of all medium-red widgets over
    // all devices with system profile SP.
    //
    // Input metric types: OCCURRENCE or INTEGER
    //
    // Local aggregation: COUNT_AS_INTEGER (used with OCCURRENCE metrics) or
    //                    NUMERIC_STAT (used with INTEGER metrics)
    // Local aggregation period: DAYS_1, DAYS_7, DAYS_28 or DAYS_30.
    // Global aggregation: NUMERIC_STATS
    // System Profile Selection Policy: REPORT_ALL
    //
    // Output report row type: NumericStatsReportRow
    // (See report_row.proto)
    //
    // ReportDefinition fields particular to this type:
    //   - local_aggregation_procedure (only when the metric type is INTEGER)
    //   - local_aggregation_period
    UNIQUE_DEVICE_NUMERIC_STATS = 17;

    // For each system_profile SP and each event_vector EV, produces several
    // numeric statistics (e.g. 95%-ile) over a set of integers associated
    // with EV, collected from all devices with system_profile SP. Each unique
    // device contributes a value every hour and so the distribution of the
    // values may NOT be thought of as a distribution of unique devices.
    //
    // Computationally this report type is identical to
    // UNIQUE_DEVICE_NUMERIC_STATS except that the local aggregation period
    // used is one hour.
    //
    // There are different versions of this depending on the metric type:
    //
    // With metrics of type OCCURRENCE the integer values are occurrence counts
    // over the course of the hour. For example a report of this
    // type might give the 95%-ile of the counts of medium-red widgets used in
    // any one hour period on any device with System profile SP, yesterday.
    //
    // With metrics of type INTEGER the integer values are computed statistics.
    // For example, a report of this type that specifies the MINIMUM local
    // aggregation procedure might give the 95%-ile of the minimum temperature
    // over any one-hour period of medium-red widgets use on any device
    // with system profile SP, yesterday.
    //
    // Input metric types: OCCURRENCE or INTEGER
    //
    // Local aggregation: COUNT_AS_INTEGER (used with OCCURRENCE metrics) or
    //                    NUMERIC_STAT (used with INTEGER metrics)
    // Local aggregation period: 1 hour
    // Global aggregation: NUMERIC_STATS
    // System Profile Selection Policy: REPORT_ALL
    //
    // Output report row type: NumericStatsReportRow
    // (See report_row.proto)
    //
    // ReportDefinition fields particular to this type:
    //   - local_aggregation_procedure (only when the metric type is INTEGER)
    HOURLY_VALUE_NUMERIC_STATS = 18;

    // For each system_profile SP and each event_vector EV, produces the total
    // count of all occurrences of a string value on all devices in the fleet
    // with system profile SP of the event associated with EV over the course
    // of the report day.
    //
    // Input metric types: STRING
    //
    // Local aggregation: STRING_HISTOGRAM
    // Local aggregation period: 1 hour
    // Global aggregation: STRING_HISTOGRAMS
    // System Profile Selection Policy: REPORT_ALL
    //
    // Output report row type: StringCountReportRow
    // (See report_row.proto)
    //
    // ReportDefinition fields particular to this type:
    //   - string_buffer_max
    STRING_COUNTS = 20;

    // For each system_profile SP, each event_vector EV, and each string value
    // produces the count of the number of unique devices with system profile
    // SP on which the string value was logged in connection with the EV during
    // the aggregation period, which must be DAYS_1, DAYS_7, DAYS_28 or DAYS_30.
    //
    // This is similar to the AT_LEAST_ONCE local aggregation procedure for
    // UNIQUE_DEVICE_COUNTS. For example, a report of this type might
    // give the total number of devices with system profile SP on which a
    // medium, red widget was used in conjunction with the component name
    // "widget-consumer" at least once in the seven-day period ending
    // yesterday.
    //
    // Input metric types: STRING
    //
    // Local aggregation period: DAYS_1, DAYS_7, DAYS_28 or DAYS_30.
    // Global aggregation: STRING_HISTOGRAMS
    //
    // Output report row type: StringCountReportRow
    // (See report_row.proto)
    //
    // ReportDefinition fields particular to this type:
    //   - local_aggregation_period
    //   - string_buffer_max
    //   - system_profile_selection (SELECT_FIRST and SELECT LAST will maintain
    //     uniqueness, REPORT_ALL may be useful in some cases)
    UNIQUE_DEVICE_STRING_COUNTS = 21;
  }
  ReportType report_type = 3;

  ////////////////  Fields for reports with privacy enabled  /////////////////

  // The level of differential privacy applied to the report. Each level
  // corresponds to an epsilon value in the shuffled model. The mapping
  // from enum values to epsilon values is hard-coded in makePrivacyConstants()
  // in the file //src/bin/config_parser/src/privacy/privacy_encoding_params.go
  enum PrivacyLevel {
    PRIVACY_LEVEL_UNKNOWN = 0;

    // epsilon = infinity
    NO_ADDED_PRIVACY = 1;

    LOW_PRIVACY = 2;

    MEDIUM_PRIVACY = 3;

    HIGH_PRIVACY = 4;
  }

  // This field is used to specify the privacy level for a Cobalt report.
  // All Cobalt report types support differential privacy and are required
  // to set this field (use NO_ADDED_PRIVACY to disable differential privacy).
  PrivacyLevel privacy_level = 20;

  // The mean number of observations added per index point when performing the
  // Poisson mechanism encoding for Cobalt reports. Should be set if and only if
  // `privacy_level` is not NO_ADDED_PRIVACY.
  //
  // In the future, the value of this field will be computed by the registry
  // parser as a function of other privacy-related fields and an estimate of the
  // user population size. For now, it should be set manually in the Cobalt
  // registry in consultation with the Cobalt team.
  //
  // TODO(b/295053509): update this comment once the field is populated by
  // the registry parser.
  double poisson_mean = 30;

  // When reporting numerical values with privacy, the values are mapped to
  // indices from 0 to num_index_points-1 with a randomized rounding method.
  //
  // In the future, the value of this field will be computed by the registry
  // parser as a function of other privacy-related fields and an estimate of the
  // user population size. For now, it should be set manually in the Cobalt
  // registry in consultation with the Cobalt team.
  //
  // TODO(b/278932979): update this comment once the field is populated by
  // the registry parser.
  uint32 num_index_points = 22;

  // When reporting strings with privacy, the strings are counted using a linear
  // sketch.
  //
  // In the future, the value of this field will be computed by the registry
  // parser as a function of other privacy-related fields and an estimate of the
  // user population size. For now, it should be set manually in the Cobalt
  // registry in consultation with the Cobalt team.
  //
  // TODO(b/278932979): update this comment once the field is populated by
  // the registry parser.
  StringSketchParameters string_sketch_params = 27;

  // These fields specify the range of values that can be reported by a device
  // in the specified local_aggregation_period. If the true value to be reported
  // falls outside specified range, the value is clipped.
  //
  // For FLEETWIDE_OCCURRENCE_COUNTS, UNIQUE_DEVICE_NUMERIC_STATS and
  // HOURLY_VALUE_NUMERIC_STATS, the range applies to the total numerical value
  // computed for the device over the aggregation period specified in the
  // report.
  //
  // For FLEETWIDE_MEANS, the range applies to the per-device sum of the value
  // to be averaged over one hour. (For FLEETWIDE_MEANS, the `max_count` field
  // is also required in order to bound the `count` value.)
  //
  // If a privacy_level other than NO_ADDED_PRIVACY is specified, this field is
  // required for reports of type:
  // * FLEETWIDE_OCCURRENCE_COUNTS
  // * UNIQUE_DEVICE_NUMERIC_STATS
  // * HOURLY_VALUE_NUMERIC_STATS
  // * FLEETWIDE_MEANS
  int64 min_value = 23;
  int64 max_value = 24;

  // This field specifies the maximum count to be reported by a device in the
  // specified local_aggregation_period. If the true count is greater than
  // max_count, then the count will be reported as max_count.
  //
  // For FLEETWIDE_HISTOGRAMS, the bound applies to the count for each
  // individual histogram bucket over the aggregation period of one hour. For
  // STRING_COUNTS, it applies to the count for each string over one hour.
  //
  // For FLEETWIDE_MEANS, the bound applies to the per-device count of the
  // values to be averaged over one hour.
  //
  // If a privacy_level other than NO_ADDED_PRIVACY is specified, this field is
  // required for reports of type:
  // * FLEETWIDE_HISTOGRAMS
  // * FLEETWIDE_MEANS
  // * STRING_COUNTS
  uint64 max_count = 25;

  ////////////////  Fields specific to some report types /////////////////

  // A specification of integer-range buckets for a histogram.
  //
  // This field is for reports of type UNIQUE_DEVICE_HISTOGRAMS,
  // HOURLY_VALUE_HISTOGRAMS, and FLEETWIDE_HISTOGRAMS -- but for
  // FLEETWIDE_HISTOGRAMS only with metrics of type INTEGER, not with metrics of
  // type INTEGER_HISTOGRAM, because in that case the MetricDefinition already
  // contains an instance of IntegerBuckets.
  IntegerBuckets int_buckets = 10;

  // The interval with which clients will generate and upload observations.
  enum ReportingInterval {
    REPORTING_INTERVAL_UNSET = 0;
    HOURS_1 = 1;
    DAYS_1 = 2;
  }

  // This field is optional for FLEETWIDE_OCCURRENCE_COUNTS reports, and is only
  // supported by some client platforms. If not set, the reporting interval
  // defaults to 1 hour for FLEETWIDE_OCCURRENCE_COUNTS reports.
  ReportingInterval reporting_interval = 32;

  // This field can be used with all Report types. When set, the generated
  // report will exclude an Observation if there are not at least
  // |reporting_threshold| number of distinct devices reporting Observations
  // with the same ObservationMetadata.
  uint32 reporting_threshold = 13;

  // The on-device function computed on the metric during the aggregation
  // window.
  enum LocalAggregationProcedure {
    LOCAL_AGGREGATION_PROCEDURE_UNSET = 0;

    // Numerical statistic aggregation procedures to be used with reports
    // of type UNIQUE_DEVICE_HISTOGRAMS, HOURLY_VALUE_HISTOGRAMS,
    // UNIQUE_DEVICE_NUMERIC_STATS and HOURLY_VALUE_NUMERIC_STATS.
    // TODO(fxbug.dev/87151): Rename these to remove the '_PROCEDURE' suffix.
    SUM_PROCEDURE = 1;
    MIN_PROCEDURE = 2;
    MAX_PROCEDURE = 3;
    MEAN = 4;
    MEDIAN = 5;
    // The value of N is set in the field
    // |local_aggregation_procedure_percentile_n|.
    PERCENTILE_N = 6;

    // Logical aggregation procedures to be used with reports of type
    // UNIQUE_DEVICE_COUNTS
    AT_LEAST_ONCE = 7;
    SELECT_FIRST = 8;
    SELECT_MOST_COMMON = 9;
  }

  // This field is required for reports of type
  // UNIQUE_DEVICE_HISTOGRAMS, HOURLY_VALUE_HISTOGRAMS,
  // UNIQUE_DEVICE_NUMERIC_STATS, HOURLY_VALUE_NUMERIC_STATS
  // and UNIQUE_DEVICE_COUNTS. Different report types support
  // different values of this field. See the comments on the
  // enum values in LocalAggregationProcedure.
  LocalAggregationProcedure local_aggregation_procedure = 17;

  // This field is required when
  // local_aggregation_procedure = LOCAL_AGGREGATION_PROCEDURE_PERCENTILE_N.
  // In this case it gives the value of N to use. Otherwise this field is
  // ignored.
  uint32 local_aggregation_procedure_percentile_n = 18;

  // Time window over which the metric is aggregated. The local aggregation
  // period is specified for UNIQUE_DEVICE_* report types.
  WindowSize local_aggregation_period = 19;

  // The maximum number of distinct event vectors for which an instance of the Cobalt
  // client should produce an observation, for a given local aggregation period. Event
  // vectors are prioritized in order of first arrival during the aggregation period.
  //
  // For example, if a report has an event_vector_buffer_max of 10, and 12 distinct event
  // vectors are logged for this metric over an aggregation period, then Cobalt will send
  // observations of the first 10 event vectors for that aggregation period and drop the
  // last 2.
  //
  // If this field is unset, the registry parser assigns to it the total number of event
  // vectors for the report's parent metric (i.e., the product over all metric dimensions
  // of the number of event codes per dimension).
  //
  // The report's project will be charged against a resource budget for this value
  // so project owners are encouraged to set this as small as possible.  For example,
  // the report's parent metric may include a dimension with thousands of event codes,
  // but it is expected that any one device will log only a few distinct event vectors
  // per day. In that case we may set event_vector_buffer_max to a relatively small number,
  // say 20. For reports which use differential privacy, setting event_vector_buffer_max
  // to a smaller number will improve the signal for event vectors which are included in
  // observations.
  uint64 event_vector_buffer_max = 26;

  // The maximum number of distinct strings that Cobalt must keep in its in-memory buffer
  // on any single device. During local aggregation for reports of type STRING_COUNTS and
  // UNIQUE_DEVICE_STRING_COUNTS, Cobalt will keep track of this many distinct strings per
  // aggregation period. The report's project will be charged against a resource budget for this
  // value so project owners are encouraged to set this as small as possible. A STRING metric
  // includes a file of candidate strings that may contain many thousands of strings. But it is
  // expected that any one device will log only a few of these strings per day. We may set
  // string_buffer_max to a relatively small number, say 20.
  //
  // This is a required field for reports of type STRING_COUNTS and UNIQUE_DEVICE_STRING_COUNTS.
  uint32 string_buffer_max = 28;

  // For reports of type UNIQUE_DEVICE_COUNTS, send observations as soon as the
  // event occurs, instead of waiting for the end of the day.
  //
  // This can only be enabled when using a local aggregation procedure of
  // AT_LEAST_ONCE or SELECT_FIRST, and when the privacy level is
  // NO_ADDED_PRIVACY. When used with a system_profile_selection of REPORT_ALL
  // or SELECT_FIRST, enabling this is recommended as Cobalt will send the count
  // for the current day when the event occurs instead of at the end of the day.
  // For a system_profile_selection of SELECT_LAST, this may also be desirable,
  // though it may result in a slight change in the current day's system profile
  // that is used, as Cobalt won't wait until the end of the day to determine
  // the final system profile, but will instead send the count immediately with
  // the system profile that is currently active on the device.
  bool expedited_sending = 29;

  ///////////////////  Fields used by all report types ///////////////////
  // Next id: 109

  // The list of SystemProfileFields to include in each row of the report.
  // Optional.
  repeated SystemProfileField system_profile_field = 100;

  // The list of Experiments to include in each row of the report.
  //
  // Each report row lists the intersection of the experiment ids active on the device and
  // experiment ids specified in this field.
  //
  // The specified experiment ids must be found in one of the project's experiments_namespaces.
  repeated int64 experiment_id = 104;

  // This field is required for reports of type UNIQUE_DEVICE_COUNTS,
  // UNIQUE_DEVICE_HISTOGRAMS, UNIQUE_DEVICE_STRING_COUNTS, and
  // HOURLY_VALUE_HISTOGRAMS. The value for these reports must be SELECT_LAST,
  // SELECT_FIRST, or occasionally REPORT_ALL.
  //
  // If the system profile value changed during the aggregation window specified
  // for this report, system_profile_selection specifies which system profile to
  // report for each device.
  SystemProfileSelectionPolicy system_profile_selection = 103;

  // Maximum ReleaseStage for which this Report is allowed to be collected.
  ReleaseStage max_release_stage = 105;

  // Report can be collected even if the user/device has not consented.
  // This field can only be set to true on reports that use privacy mechanisms
  // that include differential privacy (i.e. not DE_IDENTIFICATION). The use of
  // this field is for collecting anonymized data that is allowed even when
  // the consent is not given. These use cases need to be specially approved
  // by privacy reviewers.
  bool exempt_from_consent = 108;

  // New Privacy API

  // This enum identifies what privacy protection is applied to the report.
  enum PrivacyMechanism {
    PRIVACY_MECHANISM_UNSPECIFIED = 0;
    // If you specify this value the data will be de-identified without
    // additional privacy protections.
    DE_IDENTIFICATION = 1;
    // If you specify this value the data will be protected with Shuffled
    // Differential Privacy guarantees (e.g., the noise wll be added on the
    // devices)
    SHUFFLED_DIFFERENTIAL_PRIVACY = 2;
  }

  // This field identifies what privacy protection is applied to the report.
  // It will eventually be required once migration from privacy_level
  // is complete.
  PrivacyMechanism privacy_mechanism = 106;

  // The object for grouping all parameters needed for SHUFFLED DP mode.
  message ShuffledDifferentialPrivacyConfig {
    // This field represents an upper bound on the amount of information which
    // can be learned about a device from a report including that device.
    // Lower values correspond to higher privacy.
    // Epsilon must be > 0.
    double epsilon = 1;
    // This field represents the risk of the epsilon guarantee not holding. This
    // is usually set as 1 over the expected number of participating devices.
    // Delta must be > 0 and < 1.
    double delta = 2;
    // The generated report will exclude an Observation if there are not at
    // least |reporting_threshold| number of distinct devices reporting
    // Observations with the same ObservationMetadata.
    uint32 reporting_threshold = 3;

    // The mean number of observations added per index point when performing the
    // Poisson mechanism encoding for Cobalt reports. Required.
    //
    // In the future, the value of this field will be computed by the registry
    // parser as a function of other fields in this
    // ShuffledDifferentialPrivacyConfig. For now, it should be set manually in
    // the Cobalt registry in consultation with the Cobalt team.
    //
    // TODO(b/295053509): update this comment once the field is auto populated by
    // the registry parser.
    double poisson_mean = 4;
  }

  // If privacy_mechanism is SHUFFLED_DIFFERENTIAL_PRIVACY then privacy_config
  // must contain valid ShuffledDifferentialPrivacyConfig otherwise empty.
  oneof privacy_config {
    ShuffledDifferentialPrivacyConfig shuffled_dp = 107;
  }
}

// A specification for SystemProfile selection policy.
enum SystemProfileSelectionPolicy {
  // Use the default value. For reports of type FLEETWIDE_OCCURRENCE_COUNTS,
  // FLEETWIDE_HISTOGRAMS, FLEETWIDE_MEANS, UNIQUE_DEVICE_NUMERIC_STATS,
  // HOURLY_VALUE_NUMERIC_STATS, and STRING_COUNTS this will resolve to
  // 'REPORT_ALL' and should not be changed. For all other report types,
  // SELECT_DEFAULT must not be used.
  SELECT_DEFAULT = 0;

  // Always report the last SystemProfile seen in the aggregation window. This
  // will be the last SystemProfile seen *at the time of an event* in the
  // aggregation window.
  SELECT_LAST = 1;

  // Always report the first SystemProfile seen in the aggregation window. This
  // will be the first SystemProfile seen *at the time of an event* in the
  // aggregation window.
  SELECT_FIRST = 2;

  // Report all system profiles in the aggregation window. For most report
  // types, this is the most sensible value to use. For reports that depend on
  // some concept of uniqueness (such as UNIQUE_DEVICE_COUNTS,
  // UNIQUE_DEVICE_HISTOGRAMS, UNIQUE_DEVICE_STRING_COUNTS, and
  // HOURLY_VALUE_HISTOGRAMS) this may not be the best choice, since it will no
  // longer be the case that a single device will only upload one observation
  // per time period (It will upload one observation per time period *per unique
  // system_profile*).
  REPORT_ALL = 3;
}

// A specification of a field from SystemProfile. These are used in a
// ReportDefinition to specify which fields should be included in the generated
// Observations and reports.
//
// For a description of the meaning of each field, see the fields in the
// SystemProfile in: cobalt/proto/common.proto
enum SystemProfileField {
  OS = 0;
  ARCH = 1;
  BOARD_NAME = 2;
  PRODUCT_NAME = 3;
  SYSTEM_VERSION = 4;
  APP_VERSION = 10;
  CHANNEL = 5;
  BUILD_TYPE = 7;
  EXPERIMENT_IDS = 9;
  reserved 6, 8;
  reserved "REALM", "EXPERIMENT_TOKENS";
}

// Stages in the release cycle of a component. Each Cobalt customer determines
// its current ReleaseStage when initializing the CobaltService. Each Metric
// and Report can declare the maximum ReleaseStage for which it is allowed to
// be collected. For example a DEBUG Metric will not be collected from a device
// running a FISHFOOD release.
enum ReleaseStage {
  RELEASE_STAGE_NOT_SET = 0;

  // A test build. Also called "eng". Only use this value when the device is
  // running test builds as all metrics/reports will be collected.
  DEBUG = 10;
  // Small, internal prototype. Used for testing a new feature internally,
  // usually within the team or a small group.
  FISHFOOD = 20;
  // An internal release for testing with internal users.
  DOGFOOD = 40;
  // An open beta, for testing with internal and external users.
  OPEN_BETA = 60;

  // Generally-available. The final stage of a release. Also called
  // "production". If unsure of which release stage the device is running, it
  // is safest to fallback to this value (which is the default if no value is
  // set), to avoid inadvertently collecting metric/report data.
  GA = 99;
}

// ExponentialIntegerBuckets is used to define a partition of the integers into
// a finite number of exponentially increasing buckets.
//
// Let n = num_buckets. Then there are n+2 buckets indexed 0,...,n+1.
//
// The bucket boundaries are:
// a[0] = floor
// a[1] = floor + initial_step
// a[2] = floor + initial_step * step_multiplier
// a[3] = floor + initial_step * step_multiplier ^ 2
// a[4] = floor + initial_step * step_multiplier ^ 3
// and in general, for i = 1, 2, 3 ... n
// a[i] = floor + initial_step * step_multiplier ^ (i-1)
//
// Then, the buckets are defined as follows:
// Bucket 0 is the underflow bucket: (-infinity, floor)
// Bucket i for 0 < i < n+1: [a[i-1], a[i])
// Bucket n+1 is the overflow bucket: [a[n], +infinity)
//
// Examples:
// floor = 0
// num_buckets = 3
// initial_step = 10
// step_multiplier = 10
// Then, the buckets are:
// (-infinity, 0), [0, 10), [10, 100), [100, 1000), [1000, +infinity)
//
// floor = 0
// num_buckets = 3
// initial_step = 2
// step_multiplier = 2
// Then, the buckets are:
// (-infinity, 0), [0, 2), [2, 4), [4, 8), [8, +infinity)
//
// floor = 10
// num_buckets = 3
// initial_step = 2
// step_multiplier = 2
// Then, the buckets are:
// (-infinity, 10), [10, 12), [12, 14), [14, 18), [18, +infinity)
//
// floor = 0
// num_buckets = 3
// initial_step = 100
// step_multiplier = 10
// Then, the buckets are:
// (-infinity, 0), [0, 100), [100, 1000), [1000, 10000), [10000, +infinity)
//
message ExponentialIntegerBuckets {
  int64 floor = 1;

  // num_buckets must be at least 1.
  uint32 num_buckets = 2;

  // Must be at least one.
  uint32 initial_step = 3;

  // Must be at least one.
  uint32 step_multiplier = 4;
}

// LinearIntegerBuckets is used to define a partition of the integers into a
// finite number of buckets of equal size.
//
// Let n = num_buckets. Then there are n+2 buckets indexed 0,...,n+1.
// Bucket 0 is the underflow bucket: (-infinity, floor)
// Bucket n+1 is the overflow bucket: [lower + step_size * n, +infinity)
//
// For i = 1 to n, the bucket i is defined as
// [floor + step_size * (i-1), floor + step_size * i)
//
// Example: floor = 0, num_buckets = 3, step_size = 10.
// (-infinity, 0), [0, 10), [10, 20), [20, 30), [30, +inifinity)
message LinearIntegerBuckets {
  int64 floor = 1;

  // Must be at least one.
  uint32 num_buckets = 2;

  // Must be at least one.
  uint32 step_size = 3;
}

message IntegerBuckets {
  oneof buckets {
    ExponentialIntegerBuckets exponential = 1;
    LinearIntegerBuckets linear = 2;
  }

  // If set to true, empty buckets will not be added to the report data such
  // that all histograms contain a row for every bucket. Buckets with a zero
  // count may still occur if data is logged that contains a zero count. This
  // field can not be set on reports with added privacy.
  bool sparse_output = 3;
}

message StringSketchParameters {
  // Number of hashes in Count-Min Sketch.
  int32 num_hashes = 1;

  // Number of cells per hash in Count-Min Sketch.
  int32 num_cells_per_hash = 2;
}