Re: Why creating GIN table index is so slow than inserting data into empty table with the same index?

Tom Lane wrote:
> Sergey Burladyan <eshkinkot(at)gmail(dot)com> writes:
>> show maintenance_work_mem ;
>> maintenance_work_mem
>> ----------------------
>> 128MB
>
>> create table a (i1 int, i2 int, i3 int, i4 int, i5 int, i6 int);
>> insert into a select n, n, n, n, n, n from generate_series(1, 100000) as n;
>> create index arr_gin on a using gin ( (array[i1, i2, i3, i4, i5, i6]) );
>
> [ takes forever ]
>
> Seems the reason this is so awful is that the incoming data is exactly
> presorted, meaning that the tree structure that ginInsertEntry() is
> trying to build degenerates to a linear list (ie, every new element
> becomes the right child of the prior one). So the processing becomes
> O(N^2) up till you reach maintenance_work_mem and flush the tree. With
> a large setting for maintenance_work_mem it gets spectacularly slow.

Yes, this is probably the same issue I bumped into a while ago:

http://archives.postgresql.org/message-id/49350A13.3020105@enterprisedb.com

> I think a reasonable solution for this might be to keep an eye on
> maxdepth and force a flush if that gets too large (more than a few
> hundred, perhaps?). Something like this:
>
> /* If we've maxed out our available memory, dump everything to the index */
> + /* Also dump if the tree seems to be getting too unbalanced */
> - if (buildstate->accum.allocatedMemory >= maintenance_work_mem * 1024L)
> + if (buildstate->accum.allocatedMemory >= maintenance_work_mem * 1024L ||
> + buildstate->accum.maxdepth > DEPTH_LIMIT)
> {
>
> The new fast-insert code likely will need a similar defense.

I fooled around with a balanced tree, which solved the problem but
unfortunately made the unsorted case slower. Limiting the depth like
that should avoid that so it's worth trying.

--
Heikki Linnakangas
EnterpriseDB http://www.enterprisedb.com