On Mon, Mar 10, 2025 at 10:43 AM Naga Appani wrote:
> Hi,
>
> I would like to propose exposing an internal PostgreSQL function called
> ReadMultiXactCounts() to allow for efficient monitoring of MultiXact
> member usage. This function provides an accurate, real-time view of
> MultiXact activity by directly retrieving the actual member count, rather
> than relying on storage-based calculations.
>
> *Current Challenges: *The existing approach we are currently using to
> estimate MultiXact member usage has several drawbacks:
>
>- *Filesystem scanning overhead: *These functions recursively scan the
>pg_multixact directory, iterating over potentially thousands or
>millions of files, and retrieving file sizes using stat() calls, which
>introduces significant I/O overhead.
>- *Potential performance bottleneck:* On systems with high transaction
>throughput generating large numbers of MultiXact members, the
>filesystem-based approach scales poorly due to the latency of stat() calls,
>especially on network-based filesystems like RDS/Aurora.
>- *Not a real-time or memory-efficient solution:* The current approach
>does not provide a direct, in-memory view of MultiXact activity.
>
> *Proposed Solution*The internal ReadMultiXactCounts() function,
> implemented in multixact.c, directly calculates the number of MultiXact
> members by reading live state from shared memory. This approach avoids the
> performance issues of the current filesystem-based estimation methods.
>
> ...
>
My apologies for re-posting. This is my first time writing to the hackers
list, and I accidentally used HTML formatting. Below is the original
request in plain text:
**
I would like to propose exposing an internal PostgreSQL function called
ReadMultiXactCounts()[1] to allow for efficient monitoring of MultiXact
member usage. This function provides an accurate, real-time view of
MultiXact activity by directly retrieving the actual member count, rather
than relying on storage-based calculations.
Current Challenges
The existing approach we are currently using to estimate MultiXact member
usage has several drawbacks:
- Filesystem scanning overhead: These functions recursively scan the
pg_multixact directory, iterating over potentially thousands or millions of
files, and retrieving file sizes using stat() calls, which introduces
significant I/O overhead.
- Potential performance bottleneck: On systems with high transaction
throughput generating large numbers of MultiXact members, the
filesystem-based approach scales poorly due to the latency of stat() calls,
especially on network-based filesystems like RDS/Aurora.
- Not a real-time or memory-efficient solution: The current approach does
not provide a direct, in-memory view of MultiXact activity.
=
Proposal
=
The internal ReadMultiXactCounts() function, implemented in multixact.c,
directly calculates the number of MultiXact members by reading live state
from shared memory. This approach avoids the performance issues of the
current filesystem-based estimation methods.
By exposing ReadMultiXactCounts() for external use, we can provide
PostgreSQL users with an efficient way to monitor MultiXact member usage.
This could be particularly useful for integrating with tools like Amazon
RDS Performance Insights and Amazon CloudWatch to provide enhanced database
insights and proactive managed monitoring for users.
=
Performance comparison
=
The performance comparison between the current and proposed approaches
shows a significant improvement, with the proposed solution taking only a
fraction of a millisecond to retrieve the MultiXact member count, compared
to tens or hundreds of milliseconds for the current filesystem-based
approach. And as more members are generated, the gap widens.
Following is the comparison of performance between calculating storage of
MultiXact members directory and retrieving the count of members.
Implementation | Used size |
MultiXact members
+-+--
EC2 community (RDS version of pg_ls_multixactdir) | 8642 MB | 1.8
billion
Linux du command| 8642 MB | 1.8
billion
Proposal (ReadMultiXactCounts) | 8642 MB | 1.8
billion
Sample runs
Using "du -h"
postgres=# \! tim
