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# frozen_string_literal: true
# https://www.periscopedata.com/blog/medians-in-sql.html
module Gitlab
module Database
module Median
NotSupportedError = Class.new(StandardError)
def median_datetime(arel_table, query_so_far, column_sym)
extract_median(execute_queries(arel_table, query_so_far, column_sym)).presence
end
def median_datetimes(arel_table, query_so_far, column_sym, partition_column)
extract_medians(execute_queries(arel_table, query_so_far, column_sym, partition_column)).presence
end
def extract_median(results)
result = results.compact.first
if Gitlab::Database.postgresql?
result = result.first.presence
result['median']&.to_f if result
elsif Gitlab::Database.mysql?
result.to_a.flatten.first
end
end
def extract_medians(results)
median_values = results.compact.first.values
median_values.each_with_object({}) do |(id, median), hash|
hash[id.to_i] = median&.to_f
end
end
def mysql_median_datetime_sql(arel_table, query_so_far, column_sym)
query = arel_table.from
.from(arel_table.project(Arel.sql('*')).order(arel_table[column_sym]).as(arel_table.table_name))
.project(average([arel_table[column_sym]], 'median'))
.where(
Arel::Nodes::Between.new(
Arel.sql("(select @row_id := @row_id + 1)"),
Arel::Nodes::And.new(
[Arel.sql('@ct/2.0'),
Arel.sql('@ct/2.0 + 1')]
)
)
).
# Disallow negative values
where(arel_table[column_sym].gteq(0))
[
Arel.sql("CREATE TEMPORARY TABLE IF NOT EXISTS #{query_so_far.to_sql}"),
Arel.sql("set @ct := (select count(1) from #{arel_table.table_name});"),
Arel.sql("set @row_id := 0;"),
query.to_sql,
Arel.sql("DROP TEMPORARY TABLE IF EXISTS #{arel_table.table_name};")
]
end
def pg_median_datetime_sql(arel_table, query_so_far, column_sym, partition_column = nil)
# Create a CTE with the column we're operating on, row number (after sorting by the column
# we're operating on), and count of the table we're operating on (duplicated across) all rows
# of the CTE. For example, if we're looking to find the median of the `projects.star_count`
# column, the CTE might look like this:
#
# star_count | row_id | ct
# ------------+--------+----
# 5 | 1 | 3
# 9 | 2 | 3
# 15 | 3 | 3
#
# If a partition column is used we will do the same operation but for separate partitions,
# when that happens the CTE might look like this:
#
# project_id | star_count | row_id | ct
# ------------+------------+--------+----
# 1 | 5 | 1 | 2
# 1 | 9 | 2 | 2
# 2 | 10 | 1 | 3
# 2 | 15 | 2 | 3
# 2 | 20 | 3 | 3
cte_table = Arel::Table.new("ordered_records")
cte = Arel::Nodes::As.new(
cte_table,
arel_table.project(*rank_rows(arel_table, column_sym, partition_column)).
# Disallow negative values
where(arel_table[column_sym].gteq(zero_interval)))
# From the CTE, select either the middle row or the middle two rows (this is accomplished
# by 'where cte.row_id between cte.ct / 2.0 AND cte.ct / 2.0 + 1'). Find the average of the
# selected rows, and this is the median value.
result =
cte_table
.project(*median_projections(cte_table, column_sym, partition_column))
.where(
Arel::Nodes::Between.new(
cte_table[:row_id],
Arel::Nodes::And.new(
[(cte_table[:ct] / Arel.sql('2.0')),
(cte_table[:ct] / Arel.sql('2.0') + 1)]
)
)
)
.with(query_so_far, cte)
result.group(cte_table[partition_column]).order(cte_table[partition_column]) if partition_column
result.to_sql
end
private
def median_queries(arel_table, query_so_far, column_sym, partition_column = nil)
if Gitlab::Database.postgresql?
pg_median_datetime_sql(arel_table, query_so_far, column_sym, partition_column)
elsif Gitlab::Database.mysql?
raise NotSupportedError, _("partition_column is not supported for MySQL") if partition_column
mysql_median_datetime_sql(arel_table, query_so_far, column_sym)
end
end
def execute_queries(arel_table, query_so_far, column_sym, partition_column = nil)
queries = median_queries(arel_table, query_so_far, column_sym, partition_column)
Array.wrap(queries).map { |query| ActiveRecord::Base.connection.execute(query) }
end
def average(args, as)
Arel::Nodes::NamedFunction.new("AVG", args, as)
end
def rank_rows(arel_table, column_sym, partition_column)
column_row = arel_table[column_sym].as(column_sym.to_s)
if partition_column
partition_row = arel_table[partition_column]
row_id =
Arel::Nodes::Over.new(
Arel::Nodes::NamedFunction.new('rank', []),
Arel::Nodes::Window.new.partition(arel_table[partition_column])
.order(arel_table[column_sym])
).as('row_id')
count = arel_table.from.from(arel_table.alias)
.project('COUNT(*)')
.where(arel_table[partition_column].eq(arel_table.alias[partition_column]))
.as('ct')
[partition_row, column_row, row_id, count]
else
row_id =
Arel::Nodes::Over.new(
Arel::Nodes::NamedFunction.new('row_number', []),
Arel::Nodes::Window.new.order(arel_table[column_sym])
).as('row_id')
count = arel_table.project("COUNT(1)").as('ct')
[column_row, row_id, count]
end
end
def median_projections(table, column_sym, partition_column)
projections = []
projections << table[partition_column] if partition_column
projections << average([extract_epoch(table[column_sym])], "median")
projections
end
def extract_epoch(arel_attribute)
Arel.sql(%Q{EXTRACT(EPOCH FROM "#{arel_attribute.relation.name}"."#{arel_attribute.name}")})
end
def extract_diff_epoch(diff)
return diff unless Gitlab::Database.postgresql?
Arel.sql(%Q{EXTRACT(EPOCH FROM (#{diff.to_sql}))})
end
# Need to cast '0' to an INTERVAL before we can check if the interval is positive
def zero_interval
Arel::Nodes::NamedFunction.new("CAST", [Arel.sql("'0' AS INTERVAL")])
end
end
end
end
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