When a crawl is started, a new field to exclude content from scraping is
available. The field can be identified with the class name of div tags.
All text contained in such a div tag where the configured class name(s)
match are not indexed, while the remaining page is indexed.
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.
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
notions within the fulltext of a document. This class attempts to
identify also dates given abbreviated or with missing year or described
with names for special days, like 'Halloween'. In case that a date has
no year given, the current year and following years are considered.
This process is therefore able to identify a large set of dates to a
document, either because there are several dates given in the document
or the date is ambiguous. Four new Solr fields are used to store the
parsing result:
dates_in_content_sxt:
if date expressions can be found in the content, these dates are listed
here in order of the appearances
dates_in_content_count_i:
the number of entries in dates_in_content_sxt
date_in_content_min_dt:
if dates_in_content_sxt is filled, this contains the oldest date from
the list of available dates
#date_in_content_max_dt:
if dates_in_content_sxt is filled, this contains the youngest date from
the list of available dates, that may also be possibly in the future
These fields are deactiviated by default because the evaluation of
regular expressions to detect the date is yet too CPU intensive. Maybe
future enhancements will cause that this is switched on by default.
The purpose of these fields is the creation of calendar-like search
facets, to be implemented next.
- snapshots can now also be xml files which are extracted from the solr
index and stored as individual xml files in the snapshot directory along
the pdf and jpg images
- a transaction layer was placed above of the snapshot directory to
distinguish snapshots into 'inventory' and 'archive'. This may be used
to do transactions of index fragments using archived solr search results
between peers. This is currently unfinished, we need a protocol to move
snapshots from inventory to archive
- the SNAPSHOT directory was renamed to snapshot and contains now two
snapshot subdirectories: inventory and archive
- snapshots may now be generated by everyone, not only such peers
running on a server with xkhtml2pdf installed. The expert crawl starts
provides the option for snapshots to everyone. PDF snapshots are now
optional and the option is only shown if xkhtml2pdf is installed.
- the snapshot api now provides the request for historised xml files,
i.e. call:
http://localhost:8090/api/snapshot.xml?urlhash=Q3dQopFh1hyQ
The result of such xml files is identical with solr search results with
only one hit.
The pdf generation has been moved from the http loading process to the
solr document storage process. This may slow down the process a lot and
a different version of the process may be needed.
so viewed text and metadata (stored) info is similar
- to archive it, use request with profile to allow indexing (defaultglobaltext) and update index
(the resource is loaded, parsed anyway, so it's not a expensive operation)
Request: remove 2 unused init parameter
- number of anchors of the parent
- forkfactor sum of anchors of all ancestors
be transcoded into jpg for image previews. To create such pdfs you must
do:
Add wkhtmltopdf and imagemagick to your OS, which you can do:
On a Mac download wkhtmltox-0.12.1_osx-cocoa-x86-64.pkg from
http://wkhtmltopdf.org/downloads.html and downloadh
ttp://cactuslab.com/imagemagick/assets/ImageMagick-6.8.9-9.pkg.zip
In Debian do "apt-get install wkhtmltopdf imagemagick"
Then check in /Settings_p.html?page=ProxyAccess: "Transparent Proxy" and
"Always Fresh" - this is used by wkhtmltopdf to fetch web pages using
the YaCy proxy. Using "Always Fresh" it is possible to get all pages
from the proxy cache.
Finally, you will see a new option when starting an expert web crawl.
You can set a maximum depth for crawling which should cause a pdf
generation. The resulting pdfs are then available in
DATA/HTCACHE/SNAPSHOTS/<host>.<port>/<depth>/<shard>/<urlhash>.<date>.pdf
attribute in the <a> tag for each crawl. This introduces a lot of
changes because it extends the usage of the AnchorURL Object type which
now also has a different toString method that the underlying
DigestURL.toString. It is therefore not advised to use .toString at all
for urls, just just toNormalform(false) instead.
introduced, it was also used for search facets. The generic search
facets are now deduced from generic solr fields which makes jena as tool
for facet semantics superfluous.
- the admin user name can be configured, in apiExec calls the default "admin" username is used.
TODO: the bin/apicall.sh script should likely take that into account.
the right content domain (i.e. identifying that it is an image, text
etc.) because it used the file extension and not an existing mime type
assignment.
- fixed the new setting that images shall be loaded for a better image
search.
- both fixes together makes it now possible to crawl
commons.wikimedia.org which makes use of 'funny' document names (i.e.
ending with .jpg while the document is html)
all unique links! This made it necessary, that a large portion of the
parser and link processing classes must be adopted to carry a different
type of link collection which carry a property attribute which are
attached to web anchors.
- introduction of a new URL class, AnchorURL
- the other url classes, DigestURI and MultiProtocolURI had been renamed
and refactored to fit into a new document package schema, document.id
- cleanup of net.yacy.cora.document package and refactoring
in intranets and the internet can now choose to appear as Googlebot.
This is an essential necessity to be able to compete in the field of
commercial search appliances, since most web pages are these days
optimized only for Google and no other search platform any more. All
commercial search engine providers have a built-in fake-Google User
Agent to be able to get the same search index as Google can do. Without
the resistance against obeying to robots.txt in this case, no
competition is possible any more. YaCy will always obey the robots.txt
when it is used for crawling the web in a peer-to-peer network, but to
establish a Search Appliance (like a Google Search Appliance, GSA) it is
necessary to be able to behave exactly like a Google crawler.
With this change, you will be able to switch the user agent when portal
or intranet mode is selected on per-crawl-start basis. Every crawl start
can have a different user agent.
jdk-based logger tend to block
at java.util.logging.Logger.log(Logger.java:476) in concurrent
environments. This makes logging a main performance issue. To overcome
this problem, this is a add-on to jdk logging to put log entries on a
concurrent message queue and log the messages one by one using a
separate process.
- FTPClient uses the concurrent logging instead of the log4j logger
without the file extension. This part of the file path is removed from
the multi-field url_paths_sxt, which has now not the file name as last
part of the path list.
The same applies to the new fields source_file_name_s and
target_file_name_s in the webgraph schema.
- added the field in crawl profile
- adopted logging end error management
- adopted duplicate document detection
- added a new rule to the indexing process to reject non-matching
content
- full redesign of the expert crawl start servlet
The new filter field can now be seen in /CrawlStartExpert_p.html at
Section "Document Filter", subsection item "Filter on Content of
Document"
URIMetadataNode which creates the opportunity to access Solr objects
directly and use their information richness
- lazy initialization of the URIMetadataNode object - should cause less
computation and memory usage during search.
- removed dead code
MultiProtocolURI during normalform computation because that should
always be done and also be done during initialization of the
MultiProtocolURI Object. The new normalform method takes only one
argument which should be 'true' unless you know exactly what you are
doing.
This can be used to add another stemming to solr using stemming files
that are expressed as synonyms for grammatical alternatives. The
synonym/stemming files must have the following form:
- each line is a comma-separated list of synonyms
- the list of synonyms may be enclosed with {} (like the GSA synonyms
file)
- the file may contain comments which are lines starting with a '#'
The synonym file(s) must be placed in DATA/DICTIONARIES/synonyms/ and
are activated by default whenever a synonym file is in place.
Then, for each word that is found in a document all synonyms are added
to a long text field which is stored into synonyms_t. Processes using
the synonyms must query with that field as optional matcher.
Michael Peter Christen