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# frozen_string_literal: true
module Gitlab
module Database
module PostgresHll
# Bucket class represent data structure build with HyperLogLog algorithm
# that models data distribution in analysed set. This representation than can be used
# for following purposes
# 1. Estimating number of unique elements that this structure represents
# 2. Merging with other Buckets structure to later estimate number of unique elements in sum of two
# represented data sets
# 3. Serializing Buckets structure to json format, that can be stored in various persistence layers
#
# @example Usage
# ::Gitlab::Database::PostgresHll::Buckets.new(141 => 1, 56 => 1).estimated_distinct_count
# ::Gitlab::Database::PostgresHll::Buckets.new(141 => 1, 56 => 1).merge_hash!(141 => 1, 56 => 5).estimated_distinct_count
# ::Gitlab::Database::PostgresHll::Buckets.new(141 => 1, 56 => 1).to_json
# @note HyperLogLog is an PROBABILISTIC algorithm that ESTIMATES distinct count of given attribute value for supplied relation
# Like all probabilistic algorithm is has ERROR RATE margin, that can affect values,
# for given implementation no higher value was reported (https://gitlab.com/gitlab-org/gitlab/-/merge_requests/45673#accuracy-estimation) than 5.3%
# for the most of a cases this value is lower. However, if the exact value is necessary other tools has to be used.
class Buckets
TOTAL_BUCKETS = 512
def initialize(buckets = {})
@buckets = buckets
end
# Based on HyperLogLog structure estimates number of unique elements in analysed set.
#
# @return [Float] Estimate number of unique elements
def estimated_distinct_count
@estimated_distinct_count ||= estimate_cardinality
end
# Updates instance underlying HyperLogLog structure by merging it with other HyperLogLog structure
#
# @param other_buckets_hash hash with HyperLogLog structure representation
def merge_hash!(other_buckets_hash)
buckets.merge!(other_buckets_hash) { |_key, old, new| new > old ? new : old }
end
# Serialize instance underlying HyperLogLog structure to JSON format, that can be stored in various persistence layers
#
# @return [String] HyperLogLog data structure serialized to JSON
def to_json(_ = nil)
buckets.to_json
end
private
attr_accessor :buckets
# arbitrary values that are present in #estimate_cardinality
# are sourced from https://www.sisense.com/blog/hyperloglog-in-pure-sql/
# article, they are not representing any entity and serves as tune value
# for the whole equation
def estimate_cardinality
num_zero_buckets = TOTAL_BUCKETS - buckets.size
num_uniques = (
((TOTAL_BUCKETS**2) * (0.7213 / (1 + 1.079 / TOTAL_BUCKETS))) /
(num_zero_buckets + buckets.values.sum { |bucket_hash| 2**(-1 * bucket_hash) })
).to_i
if num_zero_buckets > 0 && num_uniques < 2.5 * TOTAL_BUCKETS
TOTAL_BUCKETS * Math.log(TOTAL_BUCKETS.to_f / num_zero_buckets)
else
num_uniques
end
end
end
end
end
end
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