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From "J. Delgado" <>
Subject Re: Realtime Search for Social Networks Collaboration
Date Sun, 07 Sep 2008 08:04:58 GMT
On Sat, Sep 6, 2008 at 1:36 AM, Otis Gospodnetic <>

> Regarding real-time search and Solr, my feeling is the focus should be on
> first adding real-time search to Lucene, and then we'll figure out how to
> incorporate that into Solr later.

Otis, what do you mean exactly by "adding real-time search to Lucene"?  Note
that Lucene, being a indexing/search library (and not a full blown search
engine), is by definition "real-time": once you add/write a document to the
index it becomes immediately searchable and if a document is logically
deleted and no longer returned in a search, though physical deletion happens
during an index optimization.

Now, the problem of adding/deleting documents in bulk, as part of a
transaction and making these documents available for search immediately
after the transaction is commited sounds more like a search engine problem
(i.e. SOLR, Nutch, Ocean), specially if these transactions are known to be
I/O expensive and thus are usually implemented bached proceeses with some
kind of sync mechanism, which makes them non real-time.

For example, in my previous life, I designed and help implement a
quasi-realtime enterprise search engine using Lucene, having a set of
multi-threaded indexers hitting a set of multiple indexes alocatted accross
different search services which powered a broker based distributed search
interface. The most recent documents provided to the indexers were always
added to the smaller in-memory (RAM) indexes which usually could absorbe the
load of a bulk "add" transaction and later would be merged into larger disk
based indexes and then flushed to make them ready to absorbe new fresh docs.
We even had further partitioning of the indexes that reflected time periods
with caps on size for them to be merged into older more archive based
indexes which were used less (yes the search engine default search was on
data no more than 1 month old, though user could open the time window by
including archives).

As for SOLR and OCEAN,  I would argue that these semi-structured search
engines are becomming more and more like relational databases with full-text
search capablities (without the benefit of full reletional algebra -- for
example joins are not possible using SOLR). Notice that "real-time" CRUD
operations and transactionality are core DB concepts adn have been studied
and developed by database communities for aquite long time. There has been
recent efforts on how to effeciently integrate Lucene into releational
databases (see Lucene JVM ORACLE integration, see

I think we should seriously look at joining efforts with open-source
Database engine projects, written in Java (see in order to blend IR
and ORM for once and for all.

-- Joaquin

> I've read Jason's Wiki as well.  Actually, I had to read it a number of
> times to understand bits and pieces of it.  I have to admit there is still
> some fuzziness about the whole things in my head - is "Ocean" something that
> already works, a separate project on  I think so.  If so,
> and if you are working on getting it integrated into Lucene, would it make
> it less confusing to just refer to it as "real-time search", so there is no
> confusion?
> If this is to be initially integrated into Lucene, why are things like
> replication, crowding/field collapsing, locallucene, name service, tag
> index, etc. all mentioned there on the Wiki and bundled with description of
> how real-time search works and is to be implemented?  I suppose mentioning
> replication kind-of makes sense because the replication approach is closely
> tied to real-time search - all query nodes need to see index changes fast.
>  But Lucene itself offers no replication mechanism, so maybe the replication
> is something to figure out separately, say on the Solr level, later on "once
> we get there".  I think even just the essential real-time search requires
> substantial changes to Lucene (I remember seeing large patches in JIRA),
> which makes it hard to digest, understand, comment on, and ultimately commit
> (hence the luke warm response, I think).  Bringing other non-essential
> elements into discussion at the same time makes it more difficult to
>  process all this new stuff, at least for me.  Am I the only one who finds
> this hard?
> That said, it sounds like we have some discussion going (Karl...), so I
> look forward to understanding more! :)
> Otis
> --
> Sematext -- -- Lucene - Solr - Nutch
> ----- Original Message ----
> > From: Yonik Seeley <>
> > To:
> > Sent: Thursday, September 4, 2008 10:13:32 AM
> > Subject: Re: Realtime Search for Social Networks Collaboration
> >
> > On Wed, Sep 3, 2008 at 6:50 PM, Jason Rutherglen
> > wrote:
> > > I also think it's got a
> > > lot of things now which makes integration difficult to do properly.
> >
> > I agree, and that's why the major bump in version number rather than
> > minor - we recognize that some features will need some amount of
> > rearchitecture.
> >
> > > I think the problem with integration with SOLR is it was designed with
> > > a different problem set in mind than Ocean, originally the CNET
> > > shopping application.
> >
> > That was the first use of Solr, but it actually existed before that
> > w/o any defined use other than to be a "plan B" alternative to MySQL
> > based search servers (that's actually where some of the parameter
> > names come from... the default /select URL instead of /search, the
> > "rows" parameter, etc).
> >
> > But you're right... some things like the replication strategy were
> > designed (well, borrowed from Doug to be exact) with the idea that it
> > would be OK to have slightly "stale" views of the data in the range of
> > minutes.  It just made things easier/possible at the time.  But tons
> > of Solr and Lucene users want almost instantaneous visibility of added
> > documents, if they can get it.  It's hardly restricted to social
> > network applications.
> >
> > Bottom line is that Solr aims to be a general enterprise search
> > platform, and getting as real-time as we can get, and as scalable as
> > we can get are some of the top priorities going forward.
> >
> > -Yonik
> >
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