On Friday 09 January 2009 22:30:14 Marvin Humphrey wrote:
On Fri, Jan 09, 2009 at 08:11:31PM +0100, Karl Wettin wrote:

SSD is pretty close to RAM when it comes to seeking. Wouldn't that
mean that a bitset stored on an SSD would be more or less as fast as a
bitset in RAM?
Provided that your index can fit in the system i/o cache and stay there, you
get the speed of RAM regardless of the underlying permanent storage type.
There's no reason to wait on SSDs before implementing such a feature.
Since this started by thinking out loud, I'd like to continue doing that.

I've been thinking about how to add a decent skipTo() to something that
compresses better than an (Open)BitSet, and this turns out to be an
integer set implemented as a B plus tree (all leafs on the same level) of
only integers with key/data compression by a frame of reference for
every node (see LUCENE-1410).

I found a java implementation for a B plus tree on sourceforge: BpLusDotNet
in the BplusJ package, see http://bplusdotnet.sourceforge.net/ .
This has nice transaction semantics on a file system and it has a BSD licence,
so it could be used as a starting point, but:
- it only has strings as index values, so it will need quite some simplification
to work on integers as keys and data, and
- it has no built in compression as far as I could see on first inspection.

The questions:

Would someone know of a better starting point for a B plus tree of integers
with node compression?

For example, how close is the current lucene code base to implementing
a b plus tree for the doc ids of a single term?

How valuable are transaction semantics for such an integer set? It is
tempting to try and implement such an integer set by starting from the
ground up, but I don't have any practical programming experience with
transaction semantics, so it may be better to start from something that
has transactions right from the start.

Paul Elschot

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postedJan 9, '09 at 7:12p
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