How to Efficiently Count Rows by Time Intervals in SQL?

Counting Rows by Time Intervals: Unveiling the Best Approach

Applications often deal with time-stamped events and require analyzing data based on specific time intervals. To effectively count the number of events within each interval, developers may ponder over various approaches.

1. Dynamic SQL Query for Arbitrary Intervals

Using a SQL query to group events by arbitrary time intervals is an efficient and preferred method. However, Postgres does not natively support this functionality.

2. Brute Force Method with Time Sorting

Querying all records within a start/end timeframe and manually tallying them by desired intervals is a straightforward but cumbersome approach. It requires sorting the results by timestamp and lacks dynamic interval customization.

3. Pre-Storing Interval Data

Maintaining separate fields for each interval in the event table can avoid runtime computations and simplify reporting. However, this method doubles the table size, which may not be optimal.

Best Practice

The best practice depends on the application's specific requirements and data size:

• For a significant number of intervals or arbitrary interval customization, a dynamic SQL query is suitable. While Postgres lacks built-in support, workarounds exist using window functions like lead().
• For a small number of fixed intervals (e.g., days or weeks), pre-storing interval data can simplify query execution but increases table size.
• For a real-time solution or where table growth is a concern, the brute force method with time sorting may be more appropriate.

Postgres 14 with date_bin() Function

For Postgres 14 and newer, the date_bin() function allows direct grouping of timestamps into intervals. This simplifies queries and provides efficient results.

Example: Counting Events in Every 15-Minute Interval

To count events in every 15-minute interval within a given time range using the date_bin() function:

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;

Note:

For Postgres 13 and earlier, alternative approaches using generate_series() and window functions are available.

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