Integrating Lucene in a RDBMS has two separate concern:
- Integrate it as index to receive notification when a row change
and that the optimizer can choose a right execution plan based on the
index statistics.
- Replace Lucene file system store to align database changes with
Lucene changes, it means both should be part of one transaction.
For H2, first point seem to be viable of implement with more or less
efforts, for the second I don't know how H2 manage BLOB storage.
My experience with Oracle-Lucene Integration is that replacing the
file-system store by BLOB do not impose a big overhead and we get
rollback, replication and fault tolerance functionality for free :)
Best regards, Marcelo.

PD: Sure Lucene Index is small inside a database, we need to store as
UN_TOKENIZED the rowid, for the content of the other indexes field the
database has faster access than Lucene.
Cool. I mention H2 because it does have some Lucene code in it yes.
Also according to some benchmarks it's the fastest of the open source
databases. I think it's possible to integrate realtime search for H2.
I suppose there is no need to store the data in Lucene in this case?
One loses the multiple values per field Lucene offers, and the schema
become static. Perhaps it's a trade off?
On Mon, Sep 8, 2008 at 6:17 PM, J. Delgado wrote:
Yes, both Marcelo and I would be interested.

We looked into H2 and it looks like something similar to Oracle's ODCI can
be implemented. Plus the primitive full-text implementación is based on
I say primitive because looking at the code I saw that one cannot define an
Analyzer and for each scan corresponding to a where clause a searcher is
open and closed, instead of having a pool, plus it does not have any way to
queue changes to reduce the use of the IndexWriter, etc.

But its open source and that is a great starting point!

-- Joaquin

On Mon, Sep 8, 2008 at 2:05 PM, Jason Rutherglen
Perhaps an interesting project would be to integrate Ocean with H2
www.h2database.com to take advantage of both models. I'm not sure how
exactly that would work, but it seems like it would not be too
difficult. Perhaps this would solve being able to perform faster
hierarchical queries and perhaps other types of queries that Lucene is
not capable of.

Is this something Joaquin you are interested in collaborating on? I
am definitely interested in it.

On Sun, Sep 7, 2008 at 4:04 AM, J. Delgado <joaquin.delgado@gmail.com>
On Sat, Sep 6, 2008 at 1:36 AM, Otis Gospodnetic
Regarding real-time search and Solr, my feeling is the focus should be
first adding real-time search to Lucene, and then we'll figure out how
incorporate that into Solr later.

Otis, what do you mean exactly by "adding real-time search to Lucene"?
that Lucene, being a indexing/search library (and not a full blown
engine), is by definition "real-time": once you add/write a document to
index it becomes immediately searchable and if a document is logically
deleted and no longer returned in a search, though physical deletion
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
(i.e. SOLR, Nutch, Ocean), specially if these transactions are known to
I/O expensive and thus are usually implemented bached proceeses with
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
different search services which powered a broker based distributed
interface. The most recent documents provided to the indexers were
added to the smaller in-memory (RAM) indexes which usually could absorbe
load of a bulk "add" transaction and later would be merged into larger
based indexes and then flushed to make them ready to absorbe new fresh
We even had further partitioning of the indexes that reflected time
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
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
search capablities (without the benefit of full reletional algebra --
example joins are not possible using SOLR). Notice that "real-time" CRUD
operations and transactionality are core DB concepts adn have been
and developed by database communities for aquite long time. There has
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
http://java-source.net/open-source/database-engines) in order to blend
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
some fuzziness about the whole things in my head - is "Ocean" something
already works, a separate project on googlecode.com? I think so. If
and if you are working on getting it integrated into Lucene, would it
it less confusing to just refer to it as "real-time search", so there
is no

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
replication kind-of makes sense because the replication approach is
tied to real-time search - all query nodes need to see index changes
But Lucene itself offers no replication mechanism, so maybe the
is something to figure out separately, say on the Solr level, later on
we get there". I think even just the essential real-time search
substantial changes to Lucene (I remember seeing large patches in
which makes it hard to digest, understand, comment on, and ultimately
(hence the luke warm response, I think). Bringing other non-essential
elements into discussion at the same time makes it more difficult t o
process all this new stuff, at least for me. Am I the only one who
this hard?

That said, it sounds like we have some discussion going (Karl...), so I
look forward to understanding more! :)

Sematext -- http://sematext.com/ -- Lucene - Solr - Nutch

----- Original Message ----
From: Yonik Seeley <yonik@apache.org>
To: java-dev@lucene.apache.org
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
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
I think the problem with integration with SOLR is it was designed
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
minutes. It just made things easier/possible at the time. But tons
of Solr and Lucene users want almost instantaneous visibility of
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.


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Marcelo F. Ochoa
Do you Know DBPrism? Look @ DB Prism's Web Site
More info?
Chapter 17 of the book "Programming the Oracle Database using Java &
Web Services"
Chapter 21 of the book "Professional XML Databases" - Wrox Press
Chapter 8 of the book "Oracle & Open Source" - O'Reilly

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