Today I want to share an example of a simple optimization I’ve recently made for multiple reports I’ve had to generate. It basically boils down to moving work to your SQL server (your SQL server is awesome at crunching huge amounts of data).

Here’s the full story:

For four years now I’ve been developing the Festivalmanager - a web based management software used for internal attendances at the Wacken Open Air Festival.

The application has multiple views displaying aggregate informations, e.g. the number of attendances checked in per hour and per day, for every day the festival is running.

Checkin stats

The data for the above chart was original generated using this ruby snippet:

require 'date'

today = Date.today
# imagine we are interested in the past 10 days worth of data
days_in_timespan = (Date.new(today.year, today.month, today.day - 10)..today)
days_in_timespan.each do |date|
  23.times do |hour|
    from_date = Date.new(date.year, date.month, date.day, hour, 0)
    to_date = Date.new(date.year, date.month, date.day, hour + 1, 0)

    sql = <<-SQL
      SELECT count(*)
      FROM events
      WHERE
        events.created_at > '#{from_date.strftime('%Y-%m-%d %H:%M')}'
        AND events.created_at < '#{to_date.strftime('%Y-%m-%d %H:%M')}'
    SQL

    events_on_day_and_hour = execute(sql)
  end
end

Now this gives us correct results. But over the years, as the dataset continued to grow the report became slow to generate. The reason for this was the total number of SQL queries executed - x24, e.g. 240 SQL queries for 10 days.

While every single SQL query was blazing fast, they all require a roundtrip to the database server and back.

By moving the calculation of events per hour per day to the SQL server thus reducing the total number of SQL queries executed I was able to reduce the time to generate the above report from ~30 seconds to < 150ms (that’s an impressive speedup of nearly 200%!).

See the updated SQL query below:

WITH data (count, hour) AS (
  SELECT
    count(*) AS count,
    extract(hour FROM created_at) AS hour
  FROM events

  WHERE
    created_at::date = '#{date.strftime('%Y-%m-%d')}'::date

  GROUP BY hour
)

SELECT
  coalesce(data.count, 0) AS count,
  coalesce(data.hour, series.hour) AS hour
FROM data

RIGHT OUTER JOIN
  (SELECT 0, * FROM generate_series(0,23) AS hour) AS series
ON
  series.hour = data.hour;

As you can see I’m using PostgreSQL here along with Common Table Expressions to fetch the number of events of every hour of a single day. Because there might be timespans without data points I’ve had to right outer join the result set with a generated_series which only contains zero values.

Note that I’d always start with the first approach. But when the need arises it’s nice to know that there’s always plenty of room to speed things up :)

UPDATE After reading the last Postgres Weekly I’ve adjusted the query - while the original speed stayed the same it’s much more understandable now:

SELECT
  extract(hour from hour) as hour, count(*) as count
FROM
  generate_series('#{date.strftime("%Y-%m-%d")} 00:00'::timestamp, '#{date.strftime("%Y-%m-%d")} 23:00'::timestamp, '1 hour') AS hour
LEFT JOIN events
ON created_at::date = '2013-08-03'::date AND date_trunc('hour', created_at) = hour
GROUP BY 1
ORDER BY hour;

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