Gene wrote:
You are correct the main part I'm worried about is the updates, being so far from the originals.


Yeah, you won't benefit from the patch at all.
The reason I'm doing the clustering is I was hoping that with the "stable" non-updating partitions I could execute a CLUSTER at night (slow...) and it would compact the tables into their most efficient state for querying which always involves a date range. bad idea? In this fillfactor feature, will you be able to set it to 100% once you know that no more updates will occur? Or will doing a cluster effectively do this? Will the fill factor only apply for inserts?

That sounds like a good approach. CLUSTER obeys the fillfactor, so you'll want to set it to 100 for the older partitions before you CLUSTER.

You might want to experiment with the fillfactor. You might get the best performance if you just set it to 100 even for the latest partition, if your queries usually have to scan most of it anyway. Fillfactor 100 will help to keep it dense and in memory, so it won't matter so much if it's disorganized.
"Your best bet might be to partition the table into two subtables, one
with "stable" data and one with the fresh data, and transfer rows from
one to the other once they get stable.  Storage density in the "fresh"
part would be poor, but it should be small enough you don't care."

This sounds interesting, I could create a RULE/INSERT on the unstable table, I will know during the update if it is ready to be put in the stable table. What would be an efficient way to do the transfer? Since the updates occur somewhat randomly, wouldnt the tuples in the stable table then be out of natural timestamp order?
I'm not sure I understand the last sentence. I thought the updates usually occur within 30 minutes of the insert. So if you transfer the rows to the stable table after 30 minutes, there won't be updates to the stable table.

- Heikki



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