Enhanded TODO:
* Experiment with multi-threaded backend better resource utilization
This would allow a single query to make use of multiple CPU's or
multiple I/O channels simultaneously. One idea is to create a
background reader that can pre-fetch sequential and index scan
pages needed by other backends. This could be expanded to allow
concurrent reads from multiple devices in a partitioned table.
The issue of parallism is basically a sliding scale, meaning what do you
want to do concurrently. In this case, we are trying to do I/O and CPU
concurrently. Another idea is to do I/O for partitioned tables
concurrently, and of course there are many CPU concurrent cases like
sorting.
---------------------------------------------------------------------------
Tom Lane wrote:
> Myron Scott <[EMAIL PROTECTED]> writes:
> > Gregory Maxwell wrote:
> >> There are other cases where it is useful to perform parallel I/O
> >> without parallel processing..
>
> > I have done some testing more along these lines with an old fork of
> > postgres code (2001). In my tests, I used a thread to delegate out
> > the actual heap scan of the SeqScan. The job of the "slave" thread
> > the was to fault in buffer pages and determine the time validity of
> > the tuples. ItemPointers are passed back to the "master" thread via a
> > common memory area guarded by mutex locking.
>
> I was considering a variant idea in the shower this morning: suppose
> that we invent one or more "background reader" processes that have
> basically the same infrastructure as the background writer, but have
> the responsibility of causing buffer reads to happen at useful times
> (whereas the writer causes writes to happen at useful times). The
> idea would be for backends to signal the readers when they know they
> will need a given block soon, and then hopefully when they need it
> it'll already be in shared buffers. For instance, in a seqscan it'd be
> pretty trivial to request block N+1 just after reading block N, and then
> doing our actual processing on block N while (we hope) some reader
> process is faulting in N+1. Bitmap indexscans could use this structure
> too; I'm less sure about whether plain indexscans could do much with it
> though.
>
> The major issues I can see are:
>
> 1. We'd need a shared-memory queue of read requests, probably much like
> the queue of fsync requests. We've already seen problems with
> contention for the fsync queue, IIRC, and that's used much less heavily
> than the read request queue would be. So there might be some
> performance issues with getting the block requests sent over to the
> readers.
>
> 2. There are some low-level assumptions that no one reads in pages of
> a relation without having some kind of lock on the relation (consider
> eg the case where the relation is being dropped). A bgwriter-like
> process wouldn't be able to hold lmgr locks, and we wouldn't really want
> it to be thrashing the lmgr shared data structures for each read anyway.
> So you'd have to design some interlock to guarantee that no backend
> abandons a query (and releases its own lmgr locks) while an async read
> request it made is still pending. Ugh.
>
> regards, tom lane
>
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--
Bruce Momjian http://candle.pha.pa.us
EnterpriseDB http://www.enterprisedb.com
+ If your life is a hard drive, Christ can be your backup. +
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