2019-02-15 15:39:39 +05:30
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# frozen_string_literal: true
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2016-09-29 09:46:39 +05:30
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# https://www.periscopedata.com/blog/medians-in-sql.html
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module Gitlab
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module Database
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module Median
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2018-03-27 19:54:05 +05:30
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NotSupportedError = Class.new(StandardError)
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2016-09-29 09:46:39 +05:30
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def median_datetime(arel_table, query_so_far, column_sym)
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2018-03-27 19:54:05 +05:30
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extract_median(execute_queries(arel_table, query_so_far, column_sym)).presence
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end
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def median_datetimes(arel_table, query_so_far, column_sym, partition_column)
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extract_medians(execute_queries(arel_table, query_so_far, column_sym, partition_column)).presence
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2016-09-29 09:46:39 +05:30
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end
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def extract_median(results)
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result = results.compact.first
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if Gitlab::Database.postgresql?
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result = result.first.presence
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2018-03-27 19:54:05 +05:30
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result['median']&.to_f if result
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2016-09-29 09:46:39 +05:30
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elsif Gitlab::Database.mysql?
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result.to_a.flatten.first
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end
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end
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2018-03-27 19:54:05 +05:30
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def extract_medians(results)
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median_values = results.compact.first.values
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median_values.each_with_object({}) do |(id, median), hash|
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hash[id.to_i] = median&.to_f
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end
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end
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2016-09-29 09:46:39 +05:30
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def mysql_median_datetime_sql(arel_table, query_so_far, column_sym)
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2019-02-15 15:39:39 +05:30
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query = arel_table.from
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2017-09-10 17:25:29 +05:30
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.from(arel_table.project(Arel.sql('*')).order(arel_table[column_sym]).as(arel_table.table_name))
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.project(average([arel_table[column_sym]], 'median'))
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.where(
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2016-09-29 09:46:39 +05:30
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Arel::Nodes::Between.new(
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Arel.sql("(select @row_id := @row_id + 1)"),
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Arel::Nodes::And.new(
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[Arel.sql('@ct/2.0'),
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Arel.sql('@ct/2.0 + 1')]
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)
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)
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).
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# Disallow negative values
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where(arel_table[column_sym].gteq(0))
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[
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Arel.sql("CREATE TEMPORARY TABLE IF NOT EXISTS #{query_so_far.to_sql}"),
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Arel.sql("set @ct := (select count(1) from #{arel_table.table_name});"),
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Arel.sql("set @row_id := 0;"),
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query.to_sql,
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Arel.sql("DROP TEMPORARY TABLE IF EXISTS #{arel_table.table_name};")
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]
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end
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2018-03-27 19:54:05 +05:30
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def pg_median_datetime_sql(arel_table, query_so_far, column_sym, partition_column = nil)
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# Create a CTE with the column we're operating on, row number (after sorting by the column
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# we're operating on), and count of the table we're operating on (duplicated across) all rows
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# of the CTE. For example, if we're looking to find the median of the `projects.star_count`
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# column, the CTE might look like this:
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#
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# star_count | row_id | ct
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# ------------+--------+----
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# 5 | 1 | 3
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# 9 | 2 | 3
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# 15 | 3 | 3
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2018-03-27 19:54:05 +05:30
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#
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# If a partition column is used we will do the same operation but for separate partitions,
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# when that happens the CTE might look like this:
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#
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# project_id | star_count | row_id | ct
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# ------------+------------+--------+----
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# 1 | 5 | 1 | 2
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# 1 | 9 | 2 | 2
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# 2 | 10 | 1 | 3
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# 2 | 15 | 2 | 3
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# 2 | 20 | 3 | 3
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cte_table = Arel::Table.new("ordered_records")
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2016-09-29 09:46:39 +05:30
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cte = Arel::Nodes::As.new(
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cte_table,
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2018-03-27 19:54:05 +05:30
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arel_table.project(*rank_rows(arel_table, column_sym, partition_column)).
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2016-09-29 09:46:39 +05:30
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# Disallow negative values
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where(arel_table[column_sym].gteq(zero_interval)))
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# From the CTE, select either the middle row or the middle two rows (this is accomplished
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# by 'where cte.row_id between cte.ct / 2.0 AND cte.ct / 2.0 + 1'). Find the average of the
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# selected rows, and this is the median value.
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2018-03-27 19:54:05 +05:30
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result =
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cte_table
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.project(*median_projections(cte_table, column_sym, partition_column))
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.where(
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Arel::Nodes::Between.new(
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cte_table[:row_id],
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Arel::Nodes::And.new(
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[(cte_table[:ct] / Arel.sql('2.0')),
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(cte_table[:ct] / Arel.sql('2.0') + 1)]
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)
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2016-09-29 09:46:39 +05:30
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)
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)
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2018-03-27 19:54:05 +05:30
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.with(query_so_far, cte)
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result.group(cte_table[partition_column]).order(cte_table[partition_column]) if partition_column
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result.to_sql
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2016-09-29 09:46:39 +05:30
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end
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private
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2018-03-27 19:54:05 +05:30
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def median_queries(arel_table, query_so_far, column_sym, partition_column = nil)
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if Gitlab::Database.postgresql?
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pg_median_datetime_sql(arel_table, query_so_far, column_sym, partition_column)
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elsif Gitlab::Database.mysql?
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raise NotSupportedError, "partition_column is not supported for MySQL" if partition_column
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mysql_median_datetime_sql(arel_table, query_so_far, column_sym)
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end
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end
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def execute_queries(arel_table, query_so_far, column_sym, partition_column = nil)
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queries = median_queries(arel_table, query_so_far, column_sym, partition_column)
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Array.wrap(queries).map { |query| ActiveRecord::Base.connection.execute(query) }
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end
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2016-09-29 09:46:39 +05:30
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def average(args, as)
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Arel::Nodes::NamedFunction.new("AVG", args, as)
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end
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2018-03-27 19:54:05 +05:30
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def rank_rows(arel_table, column_sym, partition_column)
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column_row = arel_table[column_sym].as(column_sym.to_s)
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if partition_column
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partition_row = arel_table[partition_column]
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row_id =
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Arel::Nodes::Over.new(
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Arel::Nodes::NamedFunction.new('rank', []),
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Arel::Nodes::Window.new.partition(arel_table[partition_column])
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.order(arel_table[column_sym])
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).as('row_id')
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2019-02-15 15:39:39 +05:30
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count = arel_table.from.from(arel_table.alias)
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.project('COUNT(*)')
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2018-03-27 19:54:05 +05:30
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.where(arel_table[partition_column].eq(arel_table.alias[partition_column]))
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.as('ct')
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[partition_row, column_row, row_id, count]
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else
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row_id =
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Arel::Nodes::Over.new(
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Arel::Nodes::NamedFunction.new('row_number', []),
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Arel::Nodes::Window.new.order(arel_table[column_sym])
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).as('row_id')
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count = arel_table.project("COUNT(1)").as('ct')
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[column_row, row_id, count]
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end
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end
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def median_projections(table, column_sym, partition_column)
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projections = []
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projections << table[partition_column] if partition_column
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projections << average([extract_epoch(table[column_sym])], "median")
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projections
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end
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2016-09-29 09:46:39 +05:30
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def extract_epoch(arel_attribute)
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Arel.sql(%Q{EXTRACT(EPOCH FROM "#{arel_attribute.relation.name}"."#{arel_attribute.name}")})
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end
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2017-08-17 22:00:37 +05:30
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def extract_diff_epoch(diff)
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return diff unless Gitlab::Database.postgresql?
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Arel.sql(%Q{EXTRACT(EPOCH FROM (#{diff.to_sql}))})
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end
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2016-09-29 09:46:39 +05:30
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# Need to cast '0' to an INTERVAL before we can check if the interval is positive
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def zero_interval
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Arel::Nodes::NamedFunction.new("CAST", [Arel.sql("'0' AS INTERVAL")])
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end
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end
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end
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end
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