Re: PATCH: logical_work_mem and logical streaming of large in-progress transactions

On Mon, Jan 13, 2020 at 3:18 PM Dilip Kumar <dilipbalaut(at)gmail(dot)com> wrote:
>
> On Thu, Jan 9, 2020 at 12:09 PM Amit Kapila <amit(dot)kapila16(at)gmail(dot)com> wrote:
> >
> > On Thu, Jan 9, 2020 at 10:30 AM Dilip Kumar <dilipbalaut(at)gmail(dot)com> wrote:
> > >
> > > On Thu, Jan 9, 2020 at 9:35 AM Amit Kapila <amit(dot)kapila16(at)gmail(dot)com> wrote:
> > > >
> > > > > The problem is that when we
> > > > > get a toasted chunks we remember the changes in the memory(hash table)
> > > > > but don't stream until we get the actual change on the main table.
> > > > > Now, the problem is that we might get the change of the toasted table
> > > > > and the main table in different streams. So basically, in a stream,
> > > > > if we have only got the toasted tuples then even after
> > > > > ReorderBufferStreamTXN the memory usage will not be reduced.
> > > > >
> > > >
> > > > I think we can't split such changes in a different stream (unless we
> > > > design an entirely new solution to send partial changes of toast
> > > > data), so we need to send them together. We can keep a flag like
> > > > data_complete in ReorderBufferTxn and mark it complete only when we
> > > > are able to assemble the entire tuple. Now, whenever, we try to
> > > > stream the changes once we reach the memory threshold, we can check
> > > > whether the data_complete flag is true

Here, we can also consider streaming the changes when data_complete is
false, but some additional changes have been added to the same txn as
the new changes might complete the tuple.

> > > > , if so, then only send the
> > > > changes, otherwise, we can pick the next largest transaction. I think
> > > > we can retry it for few times and if we get the incomplete data for
> > > > multiple transactions, then we can decide to spill the transaction or
> > > > maybe we can directly spill the first largest transaction which has
> > > > incomplete data.
> > > >
> > > Yeah, we might do something on this line. Basically, we need to mark
> > > the top-transaction as data-incomplete if any of its subtransaction is
> > > having data-incomplete (it will always be the latest sub-transaction
> > > of the top transaction). Also, for streaming, we are checking the
> > > largest top transaction whereas for spilling we just need the larget
> > > (sub) transaction. So we also need to decide while picking the
> > > largest top transaction for streaming, if we get a few transactions
> > > with in-complete data then how we will go for the spill. Do we spill
> > > all the sub-transactions under this top transaction or we will again
> > > find the larget (sub) transaction for spilling.
> > >
> >
> > I think it is better to do later as that will lead to the spill of
> > only required (minimum changes to get the memory below threshold)
> > changes.
> I think instead of doing this can't we just spill the changes which
> are in toast_hash. Basically, at the end of the stream, we have some
> toast tuple which we could not stream because we did not have the
> insert for the main table then we can spill only those changes which
> are in tuple hash.
>

Hmm, I think this can turn out to be inefficient because we can easily
end up spilling the data even when we don't need to so. Consider
cases, where part of the streamed changes are for toast, and remaining
are the changes which we would have streamed and hence can be removed.
In such cases, we could have easily consumed remaining changes for
toast without spilling. Also, I am not sure if spilling changes from
the hash table is a good idea as they are no more in the same order as
they were in ReorderBuffer which means the order in which we serialize
the changes normally would change and that might have some impact, so
we would need some more study if we want to pursue this idea.

--
With Regards,
Amit Kapila.
EnterpriseDB: http://www.enterprisedb.com