Web analytics schema with postgres

Question

I am building a web analytics tool and use Postgresql as a database. I will not insert postgres each user visit but only aggregated data each 5 seconds:

time    country    browser    num_visits
========================================
0       USA        Chrome     12
0       USA        IE         7
5       France     IE         5

As you can see each 5 seconds I insert multiple rows (one per each dimensions combination).

In order to reduce the number of rows need to be scanned in queries, I am thinking to have multiple tables with the above schema based on their resolution: 5SecondResolution, 30SecondResolution, 5MinResolution, ..., 1HourResolution. Now when the user asks about the last day I will go to the hour resolution table which is smaller than the 5 sec resolution table (although I could have used that one too - it's just more rows to scan).

Now what if the hour resolution table has data on hours 0,1,2,3,... but users asks to see hourly trend from 1:59 to 8:59. In order to get data for the 1:59-2:59 period I could do multiple queries to the different resolutions tables so I get 1:59:2:00 from 1MinResolution, 2:00-2:30 from 30MinResolution and etc. AFAIU I have traded one query to a huge table (that has many relevant rows to scan) with multiple queries to medium tables + combine results on client side.

Does this sound like a good optimization? Any other considerations on this?

Answer 1

Now what if the hour resolution table has data on hours 0,1,2,3,... but users asks to see hourly trend from 1:59 to 8:59. In order to get data for the 1:59-2:59 period I could do multiple queries to the different resolutions tables so I get 1:59:2:00 from 1MinResolution, 2:00-2:30 from 30MinResolution and etc.

You can't do that if you want your results to be accurate. Imagine if they're asking for one hour resolution from 01:30 to 04:30. You're imagining that you'd get the first and last half hour from the 5 second (or 1 minute) res table, then the rest from the one hour table.

The problem is that the one-hour table is offset by half an hour, so the answers won't actually be correct; each hour will be from 2:00 to 3:00, etc, when the user wants 2:30 to 3:30. It's an even more serious problem as you move to coarser resolutions.

So: This is a perfectly reasonable optimisation technique, but only if you limit your users' search start precision to the resolution of the aggregated table. If they want one hour resolution, force them to pick 1:00 , 2:00 , etc and disallow setting minutes. If they want 5 min resolution, make them pick 1:00, 1:05, 1:10, ... and so on. You don't have to limit the end precision the same way, since an incomplete ending interval won't affect data prior to the end and can easily be marked as incomplete when displayed. "Current day to date", "Hour so far", etc.

If you limit the start precision you not only give them correct results but greatly simplify the query. If you limit the end precision too then your query is purely against the aggregated table, but if you want "to date" data it's easy enough to write something like:

SELECT blah, mytimestamp
FROM mydata_1hour
WHERE mytimestamp BETWEEN current_date + INTERVAL '1' HOUR AND current_date + INTERVAL '4' HOUR
UNION ALL
SELECT sum(blah), current_date + INTERVAL '5' HOUR
FROM mydata_5second
WHERE mytimestamp BETWEEN current_date + INTERVAL '4' HOUR AND current_date + INTERVAL '5' HOUR;

... or even use several levels of union to satisfy requests for coarser resolutions.

Answer 2

You could use inheritance/partition. One resolution master table and many hourly resolution children tables ( and, perhaps, many minutes and seconds resolution children tables).

Thus you only have to select from the master table only, let the constraint of each children tables decide which is which.

Of course you have to add a trigger function to separate insert into appropriate children tables.

Complexities in insert versus complexities in display.

PostgreSQL - View or Partitioning?