your first query only returns one document because there is only one
clause selecting results -- it doesn't matter whether you write "Table AND
NOT Chair" or "Table OR NOT Chair" -- the only clause building up a list
of documents is "Table" ... the "NOT Chair" part of the query can only
take away
Hi,
I posted a few weeks ago with an issue that revolved around parens in a
query. Since then, we've been testing other booleans and came across this
anomaly. The test code is almost the same, I'm just modifying the queries.
Before I enter it as a bug, I wanted to run it by this group to see if
I have documents that have a variety of IDs and names by which people may
commonly refer to them. There is one guaranteed unique ID and multiple
other names, synonyms, etc. that are "almost unique". Furthermore, any
document may have text that refers to another document by any of these
various id
Hi,
I have a question on index generation. What if the index generation fails for
some reason, may be disk full, or any other reason? Does it make the index
corrupt? I mean, can we still use the index created so far or we need to
re-generate the entire index?
Secondly, what are possible scenar
Can this be done as an offline task?
On Nov 15, 2006, at 1:07 PM, Phil Rosen wrote:
Thanks for your help!
Here is an example, I have 100 items, each with a set of
potentially unique
attributes. Attributes could be color, size, length, density, etc.
So an
example document could be:
Id: 1
Phil Rosen wrote:
I would like to get the sum of frequency counts for each term in the fields
I specify across the search results. I can just iterate through the
documents and use getTermFreqVector() for each desired field on each
document, then sum that; but this seems slow to me.
It seems
Thanks for your help!
Here is an example, I have 100 items, each with a set of potentially unique
attributes. Attributes could be color, size, length, density, etc. So an
example document could be:
Id: 1
ItemType: foo
Blob-field: all sorts of text handled normally
Outer-Color: Red
Size: Large
T
Phil Rosen wrote:
I am building an application that requires I index a set of documents on
the scale of hundreds of thousands.
A document can have a varying number of attribute fields with an unknown
set of potential values. I realize that just indexing a blob of fields
would be much faster, ho
Why do you think you need term frequencies in the first place? What is it
that you're trying to do that just searching wouldn't accomplish?
I've often jumped into the middle of something and made it way too
complex, so I'm asking to see if you're doing something similar .
Lucene has no requi
Hello,
Thanks in advance for your help, I am really stumped I feel.
I am building an application that requires I index a set of documents on
the scale of hundreds of thousands.
A document can have a varying number of attribute fields with an unknown
set of potential values. I realize th
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