Thanks Mathieu, On your comments on partitioning of data -
<<Mathieu>> Yes. You can index unfolded data, wich take lot of space, or use two query in two index. The first build a Filter for the second, just like with the previous JDBC example. You can even cache the filter, like Solr does with its faceted search. <<Rajesh>> I am looking for a way to use single query to run across two indexes (static and dynamic index) and the search query will have fields from both these indexes. Rajesh --- Mathieu Lecarme <[EMAIL PROTECTED]> wrote: > > Le 11 avr. 08 à 19:29, Rajesh parab a écrit : > > Thanks for these pointers Mathieu. > > > > We have earlier looked at Compass, but the main > issue > > with database index is DB vendor support for BLOB > > locator. I understand that Oracle provides has > this > > support to get the partial data from BLOB, but I > guess > > the simiar support is not available in SQL Server > and > > DB2. Our application currently supports all these > 3 > > databases. > You misanderstood something. Compass can use JDBC > Index, but it's only > an option, classical file index is available too. > Other specific index > is GigaSpace and Terracotta, for cluster > environment. > > > Secondly I am reading that search performance > degrades > > drastically with database index. > You can build a Filter from JDBC query to mix it > with Lucene search. > If your JDBC query use too much join, it will be > slow, so, your Lucene > search, wich wait its Filter, will be slow two. > Building a Filter > froma Set of id is not slow. > > > Will it be possible to partition data like main > index > > and relationship index using File System Lucne > index > > and search across these indexes? > Yes. You can index unfolded data, wich take lot of > space, or use two > query in two index. The first build a Filter for the > second, just like > with the previous JDBC example. > You can even cache the filter, like Solr does with > its faceted search. > > M. > > > > > > > Regards, > > Rajesh > > > > --- Mathieu Lecarme <[EMAIL PROTECTED]> > wrote: > > > >> Have a look at Compass 2.0M3 > >> > http://www.kimchy.org/searchable-cascading-mapping/ > >> > >> Your multiple index will be nice for massive > write. > >> In a classical > >> read/write ratio, Compass will be much easier. > >> > >> M. > >> > >> Rajesh parab a écrit : > >>> Hi, > >>> > >>> We are using Lucene 2.0 to index data stored > >> inside > >>> relational database. Like any relational > database, > >> our > >>> database has quite a few one-to-one and > >> one-to-many > >>> relationships. For example, letâs say an > Object > >> A has > >>> one-to-many relationship with Object X and > Object > >> Y. > >>> As we need to de-normalize relational data as > >>> key-value pairs before storing it inside Lucene > >> index, > >>> we have de-normalized these relationships > (Object > >> X > >>> and Object Y) while building an index on Object > A. > >>> > >>> We have large no of such object relationships > and > >> most > >>> of the times, the related objects are modified > >> more > >>> frequently than the base objects. For example, > in > >> our > >>> above case, objects X and Y are updated in the > >> system > >>> very frequently, whereas Object A is not updated > >> that > >>> often. Still, we will need to update Object A > >> entries > >>> inside the index, every time its related objects > X > >>> and/or Y are modified. > >>> > >>> To avoid the above situation, we were thinking > of > >>> having 2 separate indexes â first index will > >> only > >>> index data of base objects (Object A in above > >> example) > >>> and second index will contain data about its > >>> relationship objects (Object X and Y above), > which > >> are > >>> updated more frequently. This way, the more > >> frequent > >>> updates to Object X and Y will only impact > second > >>> index that stores relationship information and > >> reduce > >>> the cost to re-index object A. However, I > donât > >> think, > >>> MultiSearcher will be helpful if we want to > search > >> for > >>> data which spans across both indexes (e.g. some > >> fields > >>> of Object A in first index and some fields of > >> Object X > >>> or Y in second index). > >>> > >>> Do we have any option in Lucene to handle such > >>> scenario? Can we search across multiple indexes > >> which > >>> have some relationships between them and search > >> for > >>> fields that span across these indexes? > >>> > >>> Regards, > >>> Rajesh > >>> > >>> > __________________________________________________ > >>> Do You Yahoo!? > >>> Tired of spam? Yahoo! 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