How to Efficiently Count Events within Dynamic Time Intervals in PostgreSQL?

How to Efficiently Count Events by Time Intervals

Introduction

Applications often necessitate extracting insights from event-based data, such as counting events within specific time intervals. This task poses a challenge when the interval size varies dynamically.

Problem Statement

A data table with timestamped events requires a dynamic SQL query that groups events by arbitrary time intervals, including weekly, daily, hourly, or even 15-minute intervals.

Solution

Postgres 14 or Newer

For Postgres versions 14 and以降, the date_bin() function provides a straightforward solution. To retrieve one row per time slot with data, use the following query:

SELECT date_bin('15 min', e.ts, '2018-05-01') AS start_time
     , count(e.ts) AS events
FROM   event e
GROUP  BY 1
ORDER  BY 1;

To get all time slots since a specific date, adjust the query as follows:

SELECT start_time, COALESCE(events, 0) AS events
FROM  (
   SELECT generate_series(timestamp '2018-05-01', max(ts), interval '15 min')
   FROM   event
   ) g(start_time)
LEFT   JOIN (
   SELECT date_bin('15 min', e.ts, '2018-05-01'), count(e.ts)
   FROM   event e
   WHERE  e.ts >= '2018-05-01'  -- filter early (optional)
   GROUP  BY 1
   ) e(start_time, events) USING (start_time)
ORDER  BY 1;

Postgres 13 or Older

For older Postgres versions, the following query can be used:

WITH grid AS (
   SELECT start_time
        , lead(start_time, 1, 'infinity') OVER (ORDER BY start_time) AS end_time
   FROM  (
      SELECT generate_series(min(ts), max(ts), interval '17 min') AS start_time
      FROM   event
      ) sub
   )
SELECT start_time, count(e.ts) AS events
FROM   grid       g
LEFT   JOIN event e ON e.ts >= g.start_time
                   AND e.ts <  g.end_time
GROUP  BY start_time
ORDER  BY start_time;

This query provides one row for each time slot, with a count of 0 for slots without events.

Optimization

Pre-storing interval data in the event table can improve performance. However, this approach doubles the table size. If the trade-off is acceptable, it can provide a significant speed boost.

Additional Considerations

• Handle upper and lower time bounds correctly.
• Use the to_char() function to format timestamps for display purposes.
• Utilize the generate_series() function to generate a full set of time slots.

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