Re: Parallel Apply

On Wed, Aug 13, 2025 at 09:50:27AM +0530, Amit Kapila wrote:
> On Tue, Aug 12, 2025 at 10:40 PM Bruce Momjian <bruce@momjian.us> wrote:
> > > Currently, PostgreSQL supports parallel apply only for large streaming
> > > transactions (streaming=parallel). This proposal aims to extend
> > > parallelism to non-streaming transactions, thereby improving
> > > replication performance in workloads dominated by smaller, frequent
> > > transactions.
> >
> > I thought the approach for improving WAL apply speed, for both binary
> > and logical, was pipelining:
> >
> >         https://en.wikipedia.org/wiki/Instruction_pipelining
> >
> > rather than trying to do all the steps in parallel.
> >
> 
> It is not clear to me how the speed for a mix of dependent and
> independent transactions can be improved using the technique you
> shared as we still need to follow the commit order for dependent
> transactions. Can you please elaborate more on the high-level idea of
> how this technique can be used to improve speed for applying logical
> WAL records?

This blog post from February I think has some good ideas for binary
replication pipelining:

    https://www.cybertec-postgresql.com/en/end-of-the-road-for-postgresql-streaming-replication/

    Surprisingly, what could be considered the actual replay work
    seems to be a minority of the total workload. The largest parts
    involve reading WAL and decoding page references from it, followed
    by looking up those pages in the cache, and pinning them so they
    are not evicted while in use. All of this work could be performed
    concurrently with the replay loop. For example, a separate
    read-ahead process could handle these tasks, ensuring that the
    replay process receives a queue of transaction log records with
    associated cache references already pinned, ready for application.

The beauty of the approach is that there is no need for dependency
tracking.  I have CC'ed the author, Ants Aasma.

-- 
  Bruce Momjian  <bruce@momjian.us>        https://momjian.us
  EDB                                      https://enterprisedb.com

  Do not let urgent matters crowd out time for investment in the future.