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# frozen_string_literal: true
# For large tables, PostgreSQL can take a long time to count rows due to MVCC.
# We can optimize this by using various strategies for approximate counting.
#
# For example, we can use the reltuples count as described in https://wiki.postgresql.org/wiki/Slow_Counting.
#
# However, since statistics are not always up to date, we also implement a table sampling strategy
# that performs an exact count but only on a sample of the table. See TablesampleCountStrategy.
module Gitlab
module Database
module Count
CONNECTION_ERRORS =
if defined?(PG)
[
ActionView::Template::Error,
ActiveRecord::StatementInvalid,
PG::Error
].freeze
else
[
ActionView::Template::Error,
ActiveRecord::StatementInvalid
].freeze
end
# Takes in an array of models and returns a Hash for the approximate
# counts for them.
#
# Various count strategies can be specified that are executed in
# sequence until all tables have an approximate count attached
# or we run out of strategies.
#
# Note that not all strategies are available on all supported RDBMS.
#
# @param [Array]
# @return [Hash] of Model -> count mapping
def self.approximate_counts(models, strategies: [TablesampleCountStrategy, ReltuplesCountStrategy, ExactCountStrategy])
strategies.each_with_object({}) do |strategy, counts_by_model|
if strategy.enabled?
models_with_missing_counts = models - counts_by_model.keys
break counts_by_model if models_with_missing_counts.empty?
counts = strategy.new(models_with_missing_counts).count
counts.each do |model, count|
counts_by_model[model] = count
end
end
end
end
end
end
end
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