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Oracle Text on Multiple Columns

egarrison
egarrison asked
on
Medium Priority
1,299 Views
Last Modified: 2010-01-27
I have a product table that I want to have a multi-column (oracle text CTXCAT) index on.  

Product_Table
ItemID,
Company_id,
Product_name varchar(255),
Product_brand varchar(50),
Product_description varchar(2000)

If a user executes a request for Apple iPod Nano.  I want the database to look at the product_name which will contain iPod Nano, then the Brand which will contain Apple, then the description.  Ideally, the description would be less important than the title and brand.

Second question – If I want to narrow the search by company_id, is that better to be a straight where companyID=123. Since I neeto narrow down by company_id, am I better to convert all query data into a clob format and use MDATA.



Does anyone have a suggestion or resource to point me to?

Eric
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To get the functionality you need is bit tricky and lot of it depends on kind of data entered. For e.g. the user may enter "iPod NANO Apple" - note that the company name is after the product and Nano is in upper case.  You may need to make the query case insensitive and rely on INSTR function if you wish to use only PL/SQL or SQL features.

However, Oracle is now providing Ultra Search Feature in the database.  Please check otn.oracle.com   -- database documentation.  This may be setup in the environment and with certain java api's it can be integrated with other applications.

Let me know if you need help in either of these approach.
Thanks,
Ritesh

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johnsoneSenior Oracle DBA
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Commented:
Oracle Text does provide case insensitive searching.

Another approach would be to add a CLOB column that contains the data in a XML format and use the Oracle text features of search XML.
egarrisonCEO / CTO
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Author

Commented:
I downloaded and installed the new Oracle Secure Enterprise Search, this is a replacement for UltraSearch.  SES is a much better application.  It is a little slower than I expected when generating the index. I am having it pull 750,000 records, so I didn't expect it to be instant.  It ran for many hours, the  document pull was fast, but indexing was the part that took a long time.
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