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Re: Avoiding repeated snapshot computation

From: Robert Haas <robertmhaas(at)gmail(dot)com>
To: Pavan Deolasee <pavan(dot)deolasee(at)gmail(dot)com>
Cc: pgsql-hackers <pgsql-hackers(at)postgresql(dot)org>
Subject: Re: Avoiding repeated snapshot computation
Date: 2011-11-26 17:13:47
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Lists: pgsql-hackers
On Sat, Nov 26, 2011 at 10:52 AM, Pavan Deolasee
<pavan(dot)deolasee(at)gmail(dot)com> wrote:
> What we can do is when a transaction comes to compute its snapshot, it
> checks if some other transaction is already computing a snapshot for
> itself. If so, it just sleeps on the lock. When the other process
> finishes computing the snapshot, it saves the snapshot is a shared
> area and wakes up all processes waiting for the snapshot. All those
> processes then just copy the snapshot from the shared area and they
> are done. This will not only reduce the total CPU consumption by
> avoiding repetitive work, but would also reduce the total time for
> which ProcArrayLock is held in SHARED mode by avoiding pipeline of
> GetSnapshotData calls. I am currently trying the shared work queue
> mechanism to implement this, but I am sure we can do it this in some
> other way too.

I don't quite understand how this is going to work.  Transaction A
ends, invaliding the shared snapshot.  Now transactions B, C, and D
come along wishing to take snapshots.  B begins taking a snapshot, so
C and D wait (blech!) for that to be complete.  Then, they start
copying the snapshot.  Meanwhile, transaction E ends, invalidating the
shared snapshot, and then transaction F comes along, wanting to take a
snapshot.  If F constructs a new shared snapshot, then doesn't that
overwrite the same memory area C and D were busy copying?  It seems
like F needs some way to know that C and D are done with the old
shared snapshot before it starts writing a new one.  Furthermore, it's
hard to understand how this could be a net improvement in the general
case, because now both B and F are copying everything twice (once to
the shared area and one to backend-local memory) instead of just once
(to backend-local memory) and C and D are sleeping (yikes!).  That
could maybe be a gain at very high concurrency when spinlock
contention is eating us alive, but it doesn't seem like a good idea in
general.  Maybe I'm missing something; did you mean to attach a patch?

I had a different idea for avoiding repeated snapshot computation:
save the snapshot in backend-private memory.  When a process takes
ProcArrayLock in exclusive mode, it increments a 64-byte counter.
When a process takes ProcArrayLock in shared mode, it can check
whether the counter has changed; if not, it can reuse the snapshot it
took before.  I think there might be away to tinker with the snapshot
management so as to do this without any more copying than we do
presently, since CurrentSnapshotData and SecondarySnapshotData are
basically treated as scratch-pads anyhow.

Another idea would be to try to avoid taking ProcArrayLock at all.
For example, suppose we again have a 64-bit counter in shared memory.
A transaction wishing to do ProcArrayEndTransaction() takes
ProcArrayLock in exclusive mode, increments the counter, memory
barrier, clears its XID, memory barrier, increments the counter,
releases ProcArrayLock.  A transaction wishing to take a snapshot
first reads the counter.  If the value read from the counter is even,
then we continue like this: memory barrier, take snapshot, memory
barrier, recheck counter.  If we find that the counter is unchanged,
then nobody did ProcArrayEndTransaction() while we were taking the
snapshot, and we're good to go.  If the counter changed then we take
ProcArrayLock in shared mode and retake the snapshot.  (We also take
ProcArrayLock in shared mode if the initial value we read was odd.)
This seems like it would all but eliminate contention on the spinlock
protecting ProcArrayLock, but I'm not sure how much overhead it would
add in other cases.  In particular, if we have to retake the snapshot
more than very occasionally, it's not going to be good.

Robert Haas
The Enterprise PostgreSQL Company

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