Hi Yuval,
1. Regarding the performances - the similarity class (And my subtype
as well) gets the IDF and TF and SQUARED SUMS calculations as inputs -
they just factor them differently. Even though I ignore the values they
are being computed.
Good point. However I think that these values are
Hi Yuval,
You can just override Similarity, rather than DefaultSimilarity - that way you
don't burn any CPU cycles on TF/IDF calculations.
Alan
On 22 Feb 2012, at 07:17, Yuval Kesten wrote:
Hi Em,
1. Regarding the performances - the similarity class (And my subtype as well)
gets the IDF
Hi all,
Inspired by another thread here (Question about CustomScoreQuery) I am using
this solution which is working really well (with one drawback):
I discovered that some of my problems were due to the fact that my assumption
was wrong:
I did have many fields/queries terms with the same field
Hello,
I am currently experimenting with tuning of max merged segment MB
parameter on TieredMergePolicy in Lucene 3.5, and seeing significant
gains in index writing speed from values dramatically lower than the
default (5 Gb). For instance, when setting it to 5 or 10 MB, I can see
my writing
Hi,
I am using Taxonomy Search to build a facet comprising things such as
“/author/American/Mark Twain”.
Since the word author has a synonym of writer, can I use writer
instead of author to get the path?
Currently I can only use exactly the word author to do it.
Thanks
Hi Cheng,
You will need to use the exact path labels in order to get to the category
'Mark Twain', unless you index multiple paths from start, e.g.:
/author/American/Mark Twain
/writer/American/Mart Twain
The taxonomy index does not process the CategoryPath labels in anyway to
e.g. produce
Thank you. The alternative sounds reasonable.
On Thu, Feb 23, 2012 at 12:54 PM, Shai Erera ser...@gmail.com wrote:
Hi Cheng,
You will need to use the exact path labels in order to get to the category
'Mark Twain', unless you index multiple paths from start, e.g.:
/author/American/Mark Twain
I have a solr instance with about 400m docs. For text searches it is perfectly
fine. When I do searches that calculate the amount of times a word appeared in
the doc set for every day of a month, it usually causes solr to crash with out
of memory errors.
I calculate this by running ~30
Hi,
You could consider storing date field as String in MMDD format. This
will save space and it will perform better.
Regards
Aditya
www.findbestopensource.com
On Thu, Feb 23, 2012 at 11:55 AM, Jason Toy jason...@gmail.com wrote:
I have a solr instance with about 400m docs. For text
Hello all,
I am using v3.5 with all default options. In my index the deletes are not
removed. When will it be removed? I have not done optimize (forced merge).
1618714 Feb 22 20:42 _11y_l.del
499 Feb 22 20:42 _195_k.del
591 Feb 22 20:42 _1hs_l.del
556 Feb 22 20:42 _1pl_l.del
Hello all,
This debate we might have had more frequently in the group. Yet one more time,
i want to clarify.
I was using multiple indexes (per week one index) with previous versions of
Lucene (2.4 - 3.0.3). The performance was really good for incremental indexing.
I used to optimize once per
Can I still do range searches on a string? It seems like it would be more
efficient to store as an integer.
Hi,
You could consider storing date field as String in MMDD format. This
will save space and it will perform better.
Regards
Aditya
www.findbestopensource.com
On Thu, Feb
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