On Tue, Jan 16, 2024 at 11:58 AM Shubham Khanna
<khannashubham1197@gmail.com> wrote:
>
> On Thu, Dec 21, 2023 at 11:47 AM Amit Kapila <amit.kapila16@gmail.com> wrote:
> >
> >
> > 4. Can we see some numbers with various sizes of databases (cluster)
> > to see how it impacts the time for small to large-size databases as
> > compared to the traditional method? This might help us with giving
> > users advice on when to use this tool. We can do this bit later as
> > well when the patch is closer to being ready for commit.
>
> I have done the Performance testing and attached the results to
> compare the 'Execution Time' between 'logical replication' and
> 'pg_subscriber' for 100MB, 1GB and 5GB data:
> | 100MB | 1GB | 5GB
> Logical rep (2 w) | 1.815s | 14.895s | 75.541s
> Logical rep (4 w) | 1.194s | 9.484s | 46.938s
> Logical rep (8 w) | 0.828s | 6.422s | 31.704s
> Logical rep(10 w)| 0.646s | 3.843s | 18.425s
> pg_subscriber | 3.977s | 9.988s | 12.665s
>
> Here, 'w' stands for 'workers'. I have included the tests to see the
> test result variations with different values for
> 'max_sync_workers_per_subscription' ranging from 2 to 10. I ran the
> tests for different data records; for 100MB I put 3,00,000 Records,
> for 1GB I put 30,00,000 Records and for 5GB I put 1,50,00,000 Records.
> It is observed that 'pg_subscriber' is better when the table size is
> more.
>
Thanks for the tests. IIUC, it shows for smaller data this tool can
take more time. Can we do perf to see if there is something we can do
about reducing the overhead?
> Next I plan to run these tests for 10GB and 20GB to see if this trend
> continues or not.
>
Okay, that makes sense.
With Regards,
Amit Kapila.
