mainly to reduce the frequent metadat checks like
> EmbeddedSolrConnector.query QUERY: q={!cache=false raw f=id}xXxXxX&rows=1&start=0&fl=id,load_date_dt
(p.s. direct servlet queries logged via AccessTracker.addToDump)
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
Differentiate mime() and getContentType() which gives the raw header field.
This improves parser detection if charsets are included in http content-type field.
use getAttributes() to get query parameters as clear text (w/o url encoding)
use getSearchpartMap() to get in internal format (url encoded)
fix for http://mantis.tokeek.de/view.php?id=606
function with a numeric date field:
"unexpected docvalues type NUMERIC for field 'last_modified' (expected
one of [SORTED, SORTED_SET]). Use UninvertingReader or index with
docvalues."
This is a well-known bug inside solr which prevents that now the 'sort
by date' in the YaCy search interface can be used. Without this patch no
results at all is displayed (since the exception prevents that). Now
there is at least a result but it is not ordered properly.
In case of error we deleted the original document and added the new doc to the index.
This is not valid for partial update documents (which contain only a subset of the fields).
Remove the "delete" error handling step.
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.
- fixed superfluous space in query field list
- fixed filter query logic
- removed look-ahead query which caused that each new search page
submitted two solr queries
- fixed random solr result orders in case that the solr score was equal:
this was then re-ordered by YaCy using the document hash which came from
the solr object and that appeared to be random. Now the hash of the url
is used and the score is additionally modified by the url length to
prevent that this particular case appears at all.
reger