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.
- 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.
during surrogate reading: those attributes from the dump are removed
during the import process and replaced by new detected attributes
according to the setting of the YaCy peer.
This may cause that all such attributes are removed if the importing
peer has no synonyms and/or no vocabularies defined.
This is a very complex migration: many classes had been renamed or
removed, dependencies changed and the solr index type is now aligned to
be a solr cloud repository.
Together with the Solr 5.2 library update, one other dependent library
had been updated as well: httpclient 4.4->4.4.1
Older indexes are migrated from 4_10 to 5_2. However, the new index
structure is more efficient and we recommend to re-index everything.
Please use the index export before you do the update to a large
surrogate xml file. After the update, start with an empty index and then
initialize this with your dump.
export function is also now the default export option. The export file
format for a full solr export is very similar to a solr search result
xml, only the <lst name="responseHeader"> tag is missing.
The exported xml has a special line termination feature: all documents
will be exported into a single line without any CR in between. That
means that every document is completely inside a single line. While this
is not readable at all for humans, it is very useful for linux line
processing scripts, like grep. Using grep it will be easy to select
single documents which match for a given pattern.
Such dumps shall be importable with the DATA/SURROGATE/in import
function, but that import is not yet adopted to the new file format.
by instatiation from URIMetadataNode, by eleminating differentiation of ResultEntry/URIMetadataNode.
- moved remaining ResultEntry functionallity to URIMetadataNode
- for 1:1 functionallity added a function makeResultEntry()
- removed ResultEntry
- refactored related code
Main difference is after makeResultEntry the text_t content is removed and alternative title/url strings for display are calculated.
Main difference left is, that
If remote crawl option is not activated, skip init of remoteCrawlJob to save the resources of queue and ideling thread.
Deploy of the remoteCrawlJob deferred on activation of the option.
keeping surrogates after processing is essential for some users. If the
space they are taking is too high, please set up an automatic deletion
process (like a cronjob).
as we flag if a peer is accesible via https, we need to know the port if we want to use is (e.g. for interYaCy communication)
start to provide / tansport the port by recording it in peers dna.
- add https link on the Network.html lock symbol
to support the new time parser and search functions in YaCy a high
precision detection of date and time on the day is necessary. That
requires that the time zone of the document content and the time zone of
the user, doing a search, is detected. The time zone of the search
request is done automatically using the browsers time zone offset which
is delivered to the search request automatically and invisible to the
user. The time zone for the content of web pages cannot be detected
automatically and must be an attribute of crawl starts. The advanced
crawl start now provides an input field to set the time zone in minutes
as an offset number. All parsers must get a time zone offset passed, so
this required the change of the parser java api. A lot of other changes
had been made which corrects the wrong handling of dates in YaCy which
was to add a correction based on the time zone of the server. Now no
correction is added and all dates in YaCy are UTC/GMT time zone, a
normalized time zone for all peers.
collections in search result. When selecting one of them in another
search, switch off the previously selected collection. This actually
turns the collection navigation modifier into a radio-button like
behaviour
- if less or equal of 8 facet options are present, they are shown by
default
- if more facet options are present, they are hidden
To view or hide all facets, just click on the facet header bar
for location nav facet of field coordinate_p does not return results, now using coordinate_p_0_coordinate as alternative to get facet counts. As the actual facet value is not used this should not harm any analysis (even if facet is a incomplete location).
If facet value is used in future likely *_geohash field could be introduced (for facet and other ... as transport value)
interface to distinguish rich and poor document data.
This also reverts some changes from commit
796770e070 because the firstSeen database
is the wrong method to distinguish these types of data
to considere description_txt always (solr hl & internal).
For now just added desc to text list for computation, could be further equalized with hl computation.
- if an eventDate is given in the search result, replace the document
date with the event date and prefix it with the string "on ".
- the document date is omitted if a date from the cent is shown
Added also the date as fields in the json and rss result sets.
- date navigation
The date is taken from the CONTENT of the documents / web pages, NOT
from a date submitted in the context of metadata (i.e. http header or
html head form). This makes it possible to search for documents in the
future, i.e. when documents contain event descriptions for future
events.
The date is written to an index field which is now enabled by default.
All documents are scanned for contained date mentions.
To visualize the dates for a specific search results, a histogram
showing the number of documents for each day is displayed. To render
these histograms the morris.js library is used. Morris.js requires also
raphael.js which is now also integrated in YaCy.
The histogram is now also displayed in the index browser by default.
To select a specific range from a search result, the following modifiers
had been introduced:
from:<date>
to:<date>
These modifiers can be used separately (i.e. only 'from' or only 'to')
to describe an open interval or combined to have a closed interval. Both
dates are inclusive. To select a specific single date only, use the
'to:' - modifier.
The histogram shows blue and green lines; the green lines denot weekend
days (saturday and sunday).
Clicking on bars in the histogram has the following reaction:
1st click: add a from:<date> modifier for the date of the bar
2nd click: add a to:<date> modifier for the date of the bar
3rd click: remove from and date modifier and set a on:<date> for the bar
When the on:<date> modifier is used, the histogram shows an unlimited
time period. This makes it possible to click again (4th click) which is
then interpreted as a 1st click again (sets a from modifier).
The display feature is NOT switched on by default; to switch it on use
the /ConfigSearchPage_p.html servlet.
calculated from boostfields config, making sure title, description, keywords and content is always searched.
- apply change to solrServlet makes sure every remote query uses at least all locally defined boost fields for search
- apply to local solr search
- simplify select query by using QF defaults
given css class and extends a given vocabulary with a term consisting
with the text content of the html class tag. Additionally, the term is
included into the semantic facet of the document. This allows the
creation of faceted search to documents without the pre-creation of
vocabularies; instead, the vocabulary is created on-the-fly, possibly
for use in other crawls. If any of the term scraping for a specific
vocabulary is successful on a document, this vocabulary is excluded for
auto-annotation on the page.
To use this feature, do the following:
- create a vocabulary on /Vocabulary_p.html (if not existent)
- in /CrawlStartExpert.html you will now see the vocabularies as column
in a table. The second column provides text fields where you can name
the class of html entities where the literal of the corresponding
vocabulary shall be scraped out
- when doing a search, you will see the content of the scraped fields in
a navigation facet for the given vocabulary
reger