Postgresql – Huge database logging of event type rows and ways to optimize it

Looks like your clustered index page splits are going to be painful because the clustered index holds the actual data and this will need new pages to be allocated and the data moved to these. This is likely to cause page locking and thus blocking.

Remember also that your clustered index key is 21 bytes and this will need to be stored in all of your secondary indexes as a bookmark.

Have you considered making your primary key identity column your clustered index, not only will this reduce the size of your other indexes, it will also mean that you will reduce the number of page splits in your clustered index. It's worth a try if you can stomach rebuilding your indexes.

Using partitioning is only going to help your query performance if the partitioning scheme is built to serve your specific queries.

You're going to have to review your query patterns and see how they are accessing the table in order to identify the best approach. The reason for this is you can only partition on a single column (the partitioning key) and this is what will be used for partition elimination.

There are two factors that affect if partition elimination can occur and how well it will perform:

1. Partition Key - Partitioning can only occur on a single column and your query must include that column. For example, if your table is partitioned on date and your query uses that date column, then partition elimination should occur. However, if you don’t include the partition key within the query predicate, the engine can not perform elimination.
2. Granularity - If your partitions are to big, you won’t gain any benefit from elimination because it will still pull back more data than it needs to. However, make it to small and it becomes difficult to manage.

In many ways, partitioning is just like using any other index, with some added benefits. However, you don’t realize those benefits unless you're dealing with incredibly large tables. Personally, I don't even consider partitioning until my table is over 250 GB in size. Most of the time, well defined indexing will cover many of the use cases on tables smaller than that. Based on your description, you're not seeing huge data growth, so it could be that a properly index table will perform just fine for your table.

I would strongly recommend that you review whether partitioning is actually necessary to solve your issues. One would usually partition a very large table for the purpose of:

• Distributing data between different types of disk so that more “active” data can be placed on faster, more expensive storage while less active data is placed on cheaper, slower storage. This is mostly a cost savings measure.
• Assisting in index maintenance for extremely large tables. Since you can rebuild partitions individually, this can assist in keeping indexes properly maintained with minimal impact.
• Leveraging partitioning for improved archival process. See sliding windows.