Re: Dynamic Partitioning using Segment Visibility Maps

On Wed, 2008-01-09 at 20:03 +0100, Gavin Sherry wrote:

> I think Simon's approach is
> probably more complex from an implementation POV.

Much of the implementation is exactly the same, and I'm sure we agree on
more than 50% of how this should work already. We just need to close in
on the remainder.

My current opinion on the SE approach is the opposite of the one above,
though it gets us nowhere just to state it. I'm trying to avoid opinion
and look at the details, which is the reason my viewpoint recently
changed in favour of the dynamic approach as the main thrust for
implementation.

I've written a detailed email this morning to explain where and how the
problems lie, which are nowhere near the syntax level. I haven't ruled
out a declarative approach yet, but I need some detailed technical
review of the issues. I hope you'll be replying to that?

> > 3. If, rather than blindly following, we create something at least
> > quasi-new, there is the chance of doing fundamentally better.
> >
> > This very thing happened when it was discovered that IBM had a
> > patent on the ARC cacheing scheme; the "clock" system that emerged
> > was a lot better than ARC ever was.
>
> Well, I don't think I'm proposing we /blindly follow/ others. I propose
> we choose a grammar which takes the best of what others have tried to
> do. Oracle's grammar is hideous, IBM's is too restrictive, for example.

I assume the new grammar is good and if we do go that way, it sounds
like the right starting place.

> > > One major advantage of the dynamic approach is that it can work on
> > > multiple dimensions simultaneously, which isn't possible with
> > > declarative partitioning. For example if you have a table of Orders then
> > > you will be able to benefit from Segment Exclusion on all of these
> > > columns, rather than just one of them: OrderId, OrderDate,
> > > RequiredByDate, LastModifiedDate. This will result in some "sloppiness"
> > > in the partitioning, e.g. if we fill 1 partition a day of Orders, then
> > > the OrderId and OrderData columns will start out perfectly arranged. Any
> > > particular RequiredByDate will probably be spread out over 7 partitions,
> > > but thats way better than being spread out over 365+ partitions.
> >
> > I think it's worth observing both the advantages and demerits of this
> > together.
> >
> > In effect, with the dynamic approach, Segment Exclusion provides its
> > benefits as an emergent property of the patterns of how INSERTs get
> > drawn into segments.
> >
> > The tendancy will correspondly be that Segment Exclusion will be able
> > to provide useful constraints for those patterns that can naturally
> > emerge from the INSERTs.
>
> Many people, in my experience, doing the kind of data processing which
> benefits from partitioning are regularly loading data, rather than
> collecting it in an OLTP fashion. Lets take the easily understandable
> concept of processing web site traffic. If the amount of data is large
> enough to benefit from partitioning, they probably have multiple web
> servers and therefore almost certainly multiple log files. If these
> files are not sorted into a single file, the records will not have a
> naturally progressing chronology: every file we go back to the beginning
> of the period of time the load covers. If you add parallelism to your load,
> things look even more different. This means you could end up with a
> bunch of partitions, under the dynamic model, which all cover the same
> time range.

Depends how big we make the partitions and how sloppy this is as to
whether that is a problem or not. We might still expect a x100 gain from
using the SE approach depending upon the data volume.

> Then there's the way that really big databases are used (say, up around
> Simon's upper bound of 16 TB). It is expensive to keep data online so
> people aren't. They're loading and unloading data all the time, to
> perform different forms of analysis.

That isn't my experience. That sounds very time consuming.

The storage cost issue was the reason Andrew wanted offline segments,
and why I have been talking about hierarchical storage.

> A common scenario in the example
> above might be to unload all but the current month's data and then load
> the same month from the previous year. The unload step needs to be
> costly (i.e., TRUNCATE). Then, there's no guarantee that what they're
> interested in is the date range at all. They may want to compare user
> agent (look at bot activity). In this case, the partitioning is across a
> small list of strings (well, numbers most likely). Here, the partitions
> would all have the same range. Partitioning would be useless.

I take it you mean SE-based partitioning would be useless, but
declarative partitioning would be useful? I would agree, assuming they
run queries with a few of the small list of strings. Seems like a
contrived case.

> Some of the biggest I've seen are GIS information or network
> information.

Those are good examples of where a declarative approach would be the
only way of getting partitioning to work well. So based on that I'll
agree that some people *need* a declarative approach to get the benefits
of partitioning, rather than just want.

We do already have constraint exclusion. Can we get by with constraint
and segment exclusion together?

> Also, what about people with there own data types? It may
> be that the data types do not support ordering so range partitioning
> does not make sense.

I'd like to hear some examples. Oleg?

> There's also a cost involved with calculating all this in the dymanic
> approach. Consider tables with a non-trivial number of columns.

True, but that balances the cost of doing that at load time.

--
Simon Riggs
2ndQuadrant http://www.2ndQuadrant.com