Can I use Argo to create Indexes for Structured data?
Hi, To search for employees who has stored some <i>word</i> in an infotype's text cluster takes time, specially when we also want those who has an relation in infotype 1001 to an object which again is connected to some other object where <i>word</i> appears in infotype 1002 - subtype 0001.
Open SQL cannot select directly from text clusters, so we need to read all entries for all employees an the scan the entries for <i>word</i>. So an index which connects <i>word</i> or <i>this is a phrase</i> or <i>department - description - all parent org.units</i> with employees would be nice to build to replace the open SQL.
The question is if Argo is a solution to build, develope, store and administrate such indexes?
Robert
Hello Robert,
Argo by itself does not index the content. Its our search engine TREX which does the indexing and searching.
If you are using ERP 2005, quite a few objects are already indexed by TREX. We have a Framework services called SES (Search Engine Services) which expects you to implement couple of methods viz. 1) the data to index and b) any updates to the index. SES interacts with TREX to index the content.
Regards,
Bala.
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You mentioned so many mistakes here, I don't know where to begin ...
vprabhu_2000 wrote:
There are different kinds of Index. B-tree Index is by default. Bit map index, function based index,index organized table.
B-tree index if the table is large This is incorrect. Small tables, even those consisting of rows within just one block, can benefit from an index. There is no table size too small in which an index might not be benefical. William Robertson in his post references links to my blog where I discuss this.
and if you want to retrieve 10 % or less of data then B-tree index is good. This is all wrong as well. A FTS on a (say) million row table could very well be more efficient when retrieving (say) just 1% of data. An index could very well be more efficient when retrieving 100% of data. There's nothing special about 10% and there is no such magic number ...
>
Bit Map Index - On low cardinality columns like Sex for eg which could have values Male,Female create a bit map index. Completely and utterly wrong. A bitmap index might be the perfect type of index, better than a B-Tree, even if there are (say) 100,000 distinct values in the table. That a bitmap index is only suitable for low cardinality columns is just not true. And what if it's an OLTP application, with lot's of concurrent DML on the underlining table, do you really think a bitmap index would be a good idea ?
>
You can also create an Index organized table if there are less rows to be stored so data is stored only once in index and not in table. Not sure what you mean here but an IOT can potentially be useful if you have very large numbers of rows in the table. The number of rows has nothing to do with whether an IOT is suitable or not.
>
Hope this info helps. Considering most of it is wrong, I'm not sure it really helps at all :(
Cheers
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