remote crawl.
On startup we save the resources for remote crawler if disabled. Once started
threads are running idle after disable remote crawl. Now threads are terminated
to save the resources also while disabeling during runtime.
+ remove empty class Channels
Update the result score result field with the result queue ranking value to reflect
the actual calculated/used score,
for rwi & solr stack results.
(calc. etc. is unchanged, it's just that result entry carries the latest val
as api retrieves the number from it)
Collection is not available in pure rwi entries (but in local solr metadata)
But if user wishes to filter by query constraint also rwi shall adhere to this
(even if only rwi entries with parsed or solr received metadata may fit)
1-char tokens and also more-than-1-char tokens, then remove the 1-char
tokens to prevent that we are to strict. This will make it possible to
be a bit more fuzzy in the search where it is appropriate.
(regardless if these fields part of update).
Switch partial update option off in postprocessing if schema contains *_dts (multivalued date field).
see http://mantis.tokeek.de/view.php?id=601
moved and was not cleared anymore. This results in an huge fieldcache.
(http://lucene.apache.org/#highlights-of-the-lucene-release-includehttps://issues.apache.org/jira/browse/LUCENE-5666)
Here I try to use DovValues where it is possible.
For this I used the Api-Scheme as new basis für the Solr-Schema.
This needs at least a complete optimization of the Solr-Index to get a
smaller FieldCache.
Everything that is indexed with these setting will not use the
Fieldcache at all.
bayesian filters. This can be used to classify documents during
indexing-time using a pre-definied bayesian filter.
New wordings:
- a context is a class where different categories are possible. The
context name is equal to a facet name.
- a category is a facet type within a facet navigation. Each context
must have several categories, at least one custom name (things you want
to discover) and one with the exact name "negative".
To use this, you must do:
- for each context, you must create a directory within
DATA/CLASSIFICATION with the name of the context (the facet name)
- within each context directory, you must create text files with one
document each per line for every categroy. One of these categories MUST
have the name 'negative.txt'.
Then, each new document is classified to match within one of the given
categories for each context.
reger