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|
# frozen_string_literal: true
require 'spec_helper'
RSpec.describe Gitlab::Usage::Metrics::Aggregates::Aggregate, :clean_gitlab_redis_shared_state do
let(:entity1) { 'dfb9d2d2-f56c-4c77-8aeb-6cddc4a1f857' }
let(:entity2) { '1dd9afb2-a3ee-4de1-8ae3-a405579c8584' }
let(:entity3) { '34rfjuuy-ce56-sa35-ds34-dfer567dfrf2' }
let(:entity4) { '8b9a2671-2abf-4bec-a682-22f6a8f7bf31' }
let(:end_date) { Date.current }
let(:sources) { Gitlab::Usage::Metrics::Aggregates::Sources }
let(:namespace) { described_class.to_s.deconstantize.constantize }
let_it_be(:recorded_at) { Time.current.to_i }
def aggregated_metric(name:, time_frame:, source: "redis", events: %w[event1 event2 event3], operator: "OR", feature_flag: nil)
{
name: name,
source: source,
events: events,
operator: operator,
time_frame: time_frame,
feature_flag: feature_flag
}.compact.with_indifferent_access
end
context 'aggregated_metrics_data' do
shared_examples 'db sourced aggregated metrics without database_sourced_aggregated_metrics feature' do
before do
allow_next_instance_of(described_class) do |instance|
allow(instance).to receive(:aggregated_metrics).and_return(aggregated_metrics)
end
end
context 'with disabled database_sourced_aggregated_metrics feature flag' do
before do
stub_feature_flags(database_sourced_aggregated_metrics: false)
end
let(:aggregated_metrics) do
[
aggregated_metric(name: "gmau_2", source: "database", time_frame: time_frame)
]
end
it 'skips database sourced metrics', :aggregate_failures do
results = {}
params = { start_date: start_date, end_date: end_date, recorded_at: recorded_at }
expect(sources::PostgresHll).not_to receive(:calculate_metrics_union).with(params.merge(metric_names: %w[event1 event2 event3]))
expect(aggregated_metrics_data).to eq(results)
end
end
end
shared_examples 'aggregated_metrics_data' do
context 'no aggregated metric is defined' do
it 'returns empty hash' do
allow_next_instance_of(described_class) do |instance|
allow(instance).to receive(:aggregated_metrics).and_return([])
end
expect(aggregated_metrics_data).to eq({})
end
end
context 'there are aggregated metrics defined' do
before do
allow_next_instance_of(described_class) do |instance|
allow(instance).to receive(:aggregated_metrics).and_return(aggregated_metrics)
end
end
context 'with AND operator' do
let(:aggregated_metrics) do
params = { source: datasource, operator: "AND", time_frame: time_frame }
[
aggregated_metric(**params.merge(name: "gmau_1", events: %w[event3 event5])),
aggregated_metric(**params.merge(name: "gmau_2"))
]
end
it 'returns the number of unique events recorded for every metric in aggregate', :aggregate_failures do
results = {
'gmau_1' => 2,
'gmau_2' => 1
}
params = { start_date: start_date, end_date: end_date, recorded_at: recorded_at }
# gmau_1 data is as follow
# |A| => 4
expect(namespace::SOURCES[datasource]).to receive(:calculate_metrics_union).with(params.merge(metric_names: 'event3')).and_return(4)
# |B| => 6
expect(namespace::SOURCES[datasource]).to receive(:calculate_metrics_union).with(params.merge(metric_names: 'event5')).and_return(6)
# |A + B| => 8
expect(namespace::SOURCES[datasource]).to receive(:calculate_metrics_union).with(params.merge(metric_names: %w[event3 event5])).and_return(8)
# Exclusion inclusion principle formula to calculate intersection of 2 sets
# |A & B| = (|A| + |B|) - |A + B| => (4 + 6) - 8 => 2
# gmau_2 data is as follow:
# |A| => 2
expect(namespace::SOURCES[datasource]).to receive(:calculate_metrics_union).with(params.merge(metric_names: 'event1')).and_return(2)
# |B| => 3
expect(namespace::SOURCES[datasource]).to receive(:calculate_metrics_union).with(params.merge(metric_names: 'event2')).and_return(3)
# |C| => 5
expect(namespace::SOURCES[datasource]).to receive(:calculate_metrics_union).with(params.merge(metric_names: 'event3')).and_return(5)
# |A + B| => 4 therefore |A & B| = (|A| + |B|) - |A + B| => 2 + 3 - 4 => 1
expect(namespace::SOURCES[datasource]).to receive(:calculate_metrics_union).with(params.merge(metric_names: %w[event1 event2])).and_return(4)
# |A + C| => 6 therefore |A & C| = (|A| + |C|) - |A + C| => 2 + 5 - 6 => 1
expect(namespace::SOURCES[datasource]).to receive(:calculate_metrics_union).with(params.merge(metric_names: %w[event1 event3])).and_return(6)
# |B + C| => 7 therefore |B & C| = (|B| + |C|) - |B + C| => 3 + 5 - 7 => 1
expect(namespace::SOURCES[datasource]).to receive(:calculate_metrics_union).with(params.merge(metric_names: %w[event2 event3])).and_return(7)
# |A + B + C| => 8
expect(namespace::SOURCES[datasource]).to receive(:calculate_metrics_union).with(params.merge(metric_names: %w[event1 event2 event3])).and_return(8)
# Exclusion inclusion principle formula to calculate intersection of 3 sets
# |A & B & C| = (|A & B| + |A & C| + |B & C|) - (|A| + |B| + |C|) + |A + B + C|
# (1 + 1 + 1) - (2 + 3 + 5) + 8 => 1
expect(aggregated_metrics_data).to eq(results)
end
end
context 'with OR operator' do
let(:aggregated_metrics) do
[
aggregated_metric(name: "gmau_1", source: datasource, time_frame: time_frame, operator: "OR")
]
end
it 'returns the number of unique events occurred for any metric in aggregate', :aggregate_failures do
results = {
'gmau_1' => 5
}
params = { start_date: start_date, end_date: end_date, recorded_at: recorded_at }
expect(namespace::SOURCES[datasource]).to receive(:calculate_metrics_union).with(params.merge(metric_names: %w[event1 event2 event3])).and_return(5)
expect(aggregated_metrics_data).to eq(results)
end
end
context 'hidden behind feature flag' do
let(:enabled_feature_flag) { 'test_ff_enabled' }
let(:disabled_feature_flag) { 'test_ff_disabled' }
let(:aggregated_metrics) do
params = { source: datasource, time_frame: time_frame }
[
# represents stable aggregated metrics that has been fully released
aggregated_metric(**params.merge(name: "gmau_without_ff")),
# represents new aggregated metric that is under performance testing on gitlab.com
aggregated_metric(**params.merge(name: "gmau_enabled", feature_flag: enabled_feature_flag)),
# represents aggregated metric that is under development and shouldn't be yet collected even on gitlab.com
aggregated_metric(**params.merge(name: "gmau_disabled", feature_flag: disabled_feature_flag))
]
end
it 'does not calculate data for aggregates with ff turned off' do
skip_feature_flags_yaml_validation
skip_default_enabled_yaml_check
stub_feature_flags(enabled_feature_flag => true, disabled_feature_flag => false)
allow(namespace::SOURCES[datasource]).to receive(:calculate_metrics_union).and_return(6)
expect(aggregated_metrics_data).to eq('gmau_without_ff' => 6, 'gmau_enabled' => 6)
end
end
end
context 'error handling' do
context 'development and test environment' do
it 'raises error when unknown aggregation operator is used' do
allow_next_instance_of(described_class) do |instance|
allow(instance).to receive(:aggregated_metrics)
.and_return([aggregated_metric(name: 'gmau_1', source: datasource, operator: "SUM", time_frame: time_frame)])
end
expect { aggregated_metrics_data }.to raise_error namespace::UnknownAggregationOperator
end
it 'raises error when unknown aggregation source is used' do
allow_next_instance_of(described_class) do |instance|
allow(instance).to receive(:aggregated_metrics)
.and_return([aggregated_metric(name: 'gmau_1', source: 'whoami', time_frame: time_frame)])
end
expect { aggregated_metrics_data }.to raise_error namespace::UnknownAggregationSource
end
it 'raises error when union is missing' do
allow_next_instance_of(described_class) do |instance|
allow(instance).to receive(:aggregated_metrics)
.and_return([aggregated_metric(name: 'gmau_1', source: datasource, time_frame: time_frame)])
end
allow(namespace::SOURCES[datasource]).to receive(:calculate_metrics_union).and_raise(sources::UnionNotAvailable)
expect { aggregated_metrics_data }.to raise_error sources::UnionNotAvailable
end
end
context 'production' do
before do
stub_rails_env('production')
end
it 'rescues unknown aggregation operator error' do
allow_next_instance_of(described_class) do |instance|
allow(instance).to receive(:aggregated_metrics)
.and_return([aggregated_metric(name: 'gmau_1', source: datasource, operator: "SUM", time_frame: time_frame)])
end
expect(aggregated_metrics_data).to eq('gmau_1' => -1)
end
it 'rescues unknown aggregation source error' do
allow_next_instance_of(described_class) do |instance|
allow(instance).to receive(:aggregated_metrics)
.and_return([aggregated_metric(name: 'gmau_1', source: 'whoami', time_frame: time_frame)])
end
expect(aggregated_metrics_data).to eq('gmau_1' => -1)
end
it 'rescues error when union is missing' do
allow_next_instance_of(described_class) do |instance|
allow(instance).to receive(:aggregated_metrics)
.and_return([aggregated_metric(name: 'gmau_1', source: datasource, time_frame: time_frame)])
end
allow(namespace::SOURCES[datasource]).to receive(:calculate_metrics_union).and_raise(sources::UnionNotAvailable)
expect(aggregated_metrics_data).to eq('gmau_1' => -1)
end
end
end
end
shared_examples 'database_sourced_aggregated_metrics' do
let(:datasource) { namespace::DATABASE_SOURCE }
it_behaves_like 'aggregated_metrics_data'
end
shared_examples 'redis_sourced_aggregated_metrics' do
let(:datasource) { namespace::REDIS_SOURCE }
it_behaves_like 'aggregated_metrics_data' do
context 'error handling' do
let(:aggregated_metrics) { [aggregated_metric(name: 'gmau_1', source: datasource, time_frame: time_frame)] }
let(:error) { Gitlab::UsageDataCounters::HLLRedisCounter::EventError }
before do
allow_next_instance_of(described_class) do |instance|
allow(instance).to receive(:aggregated_metrics).and_return(aggregated_metrics)
end
allow(Gitlab::UsageDataCounters::HLLRedisCounter).to receive(:calculate_events_union).and_raise(error)
end
context 'development and test environment' do
it 're raises Gitlab::UsageDataCounters::HLLRedisCounter::EventError' do
expect { aggregated_metrics_data }.to raise_error error
end
end
context 'production' do
it 'rescues Gitlab::UsageDataCounters::HLLRedisCounter::EventError' do
stub_rails_env('production')
expect(aggregated_metrics_data).to eq('gmau_1' => -1)
end
end
end
end
end
describe '.aggregated_metrics_all_time_data' do
subject(:aggregated_metrics_data) { described_class.new(recorded_at).all_time_data }
let(:start_date) { nil }
let(:end_date) { nil }
let(:time_frame) { ['all'] }
it_behaves_like 'database_sourced_aggregated_metrics'
it_behaves_like 'db sourced aggregated metrics without database_sourced_aggregated_metrics feature'
context 'redis sourced aggregated metrics' do
let(:aggregated_metrics) { [aggregated_metric(name: 'gmau_1', time_frame: time_frame)] }
before do
allow_next_instance_of(described_class) do |instance|
allow(instance).to receive(:aggregated_metrics).and_return(aggregated_metrics)
end
end
context 'development and test environment' do
it 'raises Gitlab::Usage::Metrics::Aggregates::DisallowedAggregationTimeFrame' do
expect { aggregated_metrics_data }.to raise_error namespace::DisallowedAggregationTimeFrame
end
end
context 'production env' do
it 'returns fallback value for unsupported time frame' do
stub_rails_env('production')
expect(aggregated_metrics_data).to eq('gmau_1' => -1)
end
end
end
end
it 'allows for YAML aliases in aggregated metrics configs' do
expect(YAML).to receive(:safe_load).with(kind_of(String), aliases: true).at_least(:once)
described_class.new(recorded_at)
end
describe '.aggregated_metrics_weekly_data' do
subject(:aggregated_metrics_data) { described_class.new(recorded_at).weekly_data }
let(:start_date) { 7.days.ago.to_date }
let(:time_frame) { ['7d'] }
it_behaves_like 'database_sourced_aggregated_metrics'
it_behaves_like 'redis_sourced_aggregated_metrics'
it_behaves_like 'db sourced aggregated metrics without database_sourced_aggregated_metrics feature'
end
describe '.aggregated_metrics_monthly_data' do
subject(:aggregated_metrics_data) { described_class.new(recorded_at).monthly_data }
let(:start_date) { 4.weeks.ago.to_date }
let(:time_frame) { ['28d'] }
it_behaves_like 'database_sourced_aggregated_metrics'
it_behaves_like 'redis_sourced_aggregated_metrics'
it_behaves_like 'db sourced aggregated metrics without database_sourced_aggregated_metrics feature'
context 'metrics union calls' do
it 'caches intermediate operations', :aggregate_failures do
events = %w[event1 event2 event3 event5]
allow_next_instance_of(described_class) do |instance|
allow(instance).to receive(:aggregated_metrics)
.and_return([aggregated_metric(name: 'gmau_1', events: events, operator: "AND", time_frame: time_frame)])
end
params = { start_date: start_date, end_date: end_date, recorded_at: recorded_at }
events.each do |event|
expect(sources::RedisHll).to receive(:calculate_metrics_union)
.with(params.merge(metric_names: event))
.once
.and_return(0)
end
2.upto(4) do |subset_size|
events.combination(subset_size).each do |events|
expect(sources::RedisHll).to receive(:calculate_metrics_union)
.with(params.merge(metric_names: events))
.once
.and_return(0)
end
end
aggregated_metrics_data
end
end
end
end
end
|