Chris, thanks again for your replies.
I realize now that I don't have the 'getConfig' method -- I'm writing a server
plugin and I only get the GraphDatabaseService interface passed to my method,
not a EmbeddedGraphDatabase. Is there an equivalent way of getting the highest
node index through the interface?
Thanks.
> Date: Thu, 10 Nov 2011 12:01:31 +0200
> From: chris.gio...@neotechnology.com
> To: user@lists.neo4j.org
> Subject: Re: [Neo4j] Sampling a Neo4j instance?
>
> Answers inline.
>
> 2011/11/9 Anders Lindström <andli...@hotmail.com>:
> >
> > Thanks to the both of you. I am very grateful that you took your time to
> > put this into code -- how's that for community!
> > I presume this way of getting 'highId' is constant in time? It looks rather
> > messy though -- is it really the most straightforward way to do it?
>
> This is the safest way to do it, that takes into consideration crashes
> and HA cluster membership.
>
> Another way to do it is
>
> long highId = db.getConfig().getIdGeneratorFactory().get( IdType.NODE
> ).getHighId();
>
> which can return the same value with the first, if some conditions are
> met. It is shorter and cast-free but i'd still use the first way.
>
> getHighId() is a constant time operation for both ways described - it
> is just a field access, with an additional long comparison for the
> first case.
>
> > I am thinking about how efficient this will be. As I understand it, the
> > "sampling misses" come from deleted nodes that once was there. But if I
> > remember correctly, Neo4j tries to reuse these unused node indices when new
> > nodes are added. But is an unused node index _guaranteed_ to be used given
> > that there is one, or could inserting another node result in increasing
> > 'highId' even though some indices below it are not used?
>
> During the lifetime of a Neo4j instance there is no id reuse for Nodes
> and Relationships - deleted ids are saved however and will be reused
> the next time Neo4j starts. This means that if during run A you
> deleted nodes 3 and 5, the first two nodes returned by createNode() on
> the next run will have ids 3 and 5 - so highId will not change.
> Additionally, during run A, after deleting nodes 3 and 5, no new nodes
> would have the id 3 or 5. A crash (or improper shutdown) of the
> database will break this however, since the ids-to-recycle will
> probably not make it to disk.
>
> So, in short, it is guaranteed that ids *won't* be reused in the same
> run but not guaranteed to be reused between runs.
>
> > My conclusion is that the "sampling misses" will increase with index usage
> > sparseness and that we will have a high rate of "sampling misses" when we
> > had many deletes and few insertions recently. Would you agree?
>
> Yes, that is true, especially given the cost of the "wasted" I/O and
> of handling the exception. However, this cost can go down
> significantly if you keep a hash set for the ids of nodes you have
> deleted and check that before asking for the node by id, instead of
> catching an exception. Persisting that between runs would move you
> away from encapsulated Neo4j constructs and would also be more
> efficient.
>
> > Thanks again.
> > Regards,Anders
> >
> >> Date: Wed, 9 Nov 2011 19:30:36 +0200
> >> From: chris.gio...@neotechnology.com
> >> To: user@lists.neo4j.org
> >> Subject: Re: [Neo4j] Sampling a Neo4j instance?
> >>
> >> Hi,
> >>
> >> Backing Jim's algorithm with some code:
> >>
> >> public static void main( String[] args )
> >> {
> >> long SAMPLE_SIZE = 10000;
> >> EmbeddedGraphDatabase db = new EmbeddedGraphDatabase(
> >> "path/to/db/" );
> >> // Determine the highest possible id for the node store
> >> long highId = ( (NeoStoreXaDataSource)
> >> db.getConfig().getTxModule().getXaDataSourceManager().getXaDataSource(
> >> Config.DEFAULT_DATA_SOURCE_NAME )
> >> ).getNeoStore().getNodeStore().getHighId();
> >> System.out.println( highId + " is the highest id" );
> >> long i = 0;
> >> long nextId;
> >>
> >> // Do the sampling
> >> Random random = new Random();
> >> while ( i < SAMPLE_SIZE )
> >> {
> >> nextId = Math.abs( random.nextLong() ) % highId;
> >> try
> >> {
> >> db.getNodeById( nextId );
> >> i++;
> >> System.out.println( "id " + nextId + " is there" );
> >> }
> >> catch ( NotFoundException e )
> >> {
> >> // NotFoundException is thrown when the node asked is not
> >> in use
> >> System.out.println( "id " + nextId + " not in use" );
> >> }
> >> }
> >> db.shutdown();
> >> }
> >>
> >> Like already mentioned, this will be slow. Random jumps around the
> >> graph are not something caches can keep up with - unless your whole db
> >> fits in memory. But accessing random pieces of an on-disk file cannot
> >> be done much faster.
> >>
> >> cheers,
> >> CG
> >>
> >> On Wed, Nov 9, 2011 at 6:08 PM, Jim Webber <j...@neotechnology.com> wrote:
> >> > Hi Anders,
> >> >
> >> > When you do getAllNodes, you're getting back an iterable so as you point
> >> > out the sample isn't random (unless it was written randomly to disk). If
> >> > you're prepared to take a scattergun approach and tolerate being
> >> > disk-bound, then you can ask for getNodeById using a made-up ID and deal
> >> > with the times when your ID's don't resolve.
> >> >
> >> > It'll be slow (since the chances of having the nodes in cache are low)
> >> > but as random as your random ID generator.
> >> >
> >> > Jim
> >> > _______________________________________________
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> >> >
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