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
trace: java.lang.OutOfMemoryError: Java heap space
at java.awt.image.DataBufferInt.<init>(DataBufferInt.java:75)
at java.awt.image.Raster.createPackedRaster(Raster.java:467)
at java.awt.image.DirectColorModel.createCompatibleWritableRaster(DirectColorModel.java:1032)
at java.awt.image.BufferedImage.<init>(BufferedImage.java:331)
at net.yacy.document.parser.images.bmpParser$IMAGEMAP.<init>(bmpParser.java:149)
at net.yacy.document.parser.images.bmpParser.parse(bmpParser.java:69)
at net.yacy.document.parser.images.genericImageParser.parse(genericImageParser.java:116)
parsing into individual pages and add them all using different URLs.
These constructed urls are generated from the source url with an
appended page=<pagenumber> attribute to the url get/post properties.
This will distinguish the different page entries. The search result list
will then replace the post parameter with a url anchor # mark which
causes that the original url is presented in the search result. These
URLs can be opened directly on the correct page using pdf.js which is
now built-in into firefox. That means: if you find a search hit on page
5 and click on the search result, firefox will open the pdf viewer and
shows page 5.
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.
this extracts clickable links in pdf and adds it to the list of links
include a test case for this function
this is the corrected comment for commit:
aa2e15d846
tested with IE11 and Firefox 32 (change worked for both to show 2nd line without cutting off height)
+fix charset parameter in metadataImageParser
+update start errMsgTxt to "java 1.7"
This is a modified genericImageParser adding tif (and psd) support even if java ImageIO plugin for tif is not installed in JDK.
Adds just tif and psd to the available parsers.
Uses the same library to extract metadata, so could eventually be merged with genericImageParser.
All detected metadata are added to the parsed document (potentially some more as with genericImageParser)
genericImageParser uses javax ImageIO, supported images depend on available plugins for ImageIO package (this is JDK installation specific). Jpeg, png and gif are availabel by default. Tif and others only on avalable plugin (in classpath).
Add supported image type dynamically on startup.
the parser initialization. To make the apk parser usable, the handling
of application type links had to be modified. Now all documents which
have not a parser attached are placed to the noload-queue while all
other documents are parsed using the associated parser class. This may
have side-Effects on other parsers and the display of different file
classes (images, apps, videos).
- type detection (rss/atom)
- init type parameter overwritten during parse, parameter obsolete
- detection by endtag changed to simpler first-tag evaluation
- channel image not used, removed related extra parser handling
- remove unused code (set/getImage) in rssfeed
- atom link extraction to account for possible multipe link tags
- spec limits link to one with rel="alternate" or one without rel attribute
not accounting for the follwing type & hreflang exception yet:
o atom:entry elements MUST NOT contain more than one atom:link
element with a rel attribute value of "alternate" that has the
same combination of type and hreflang attribute values.
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.
generic parser but extracts links like the htmlParser. This should be
used for ASCII documents without known text format annotation like
source code files or json documents. Probably also good for xml files
without known schema.
- some outboundlinks_anchortext_txt in index contain e.g. <span>text</span> or more tags,
remove all tags for text property (inline img tags are still parsed)
- added test case for above (to htmlParserTest)
- fix solr test case
This organizes all urls to be loaded in separate queues for each host.
Each host separates the crawl depth into it's own queue. The primary
rule for urls taken from any queue is, that the crawl depth is minimal.
This produces a crawl depth which is identical to the clickdepth.
Furthermorem the crawl is able to create a much better balancing over
all hosts which is fair to all hosts that are in the queue.
This process will create a very large number of files for wide crawls in
the QUEUES folder: for each host a directory, for each crawl depth a
file inside the directory. A crawl with maxdepth = 4 will be able to
create 10.000s of files. To be able to use that many file readers, it
was necessary to implement a new index data structure which opens the
file only if an access is wanted (OnDemandOpenFileIndex). The usage of
such on-demand file reader shall prevent that the number of file
pointers is over the system limit, which is usually about 10.000 open
files. Some parts of YaCy had to be adopted to handle the crawl depth
number correctly. The logging and the IndexCreateQueues servlet had to
be adopted to show the crawl queues differently, because the host name
is attached to the port on the host to differentiate between http,
https, and ftp services.
stack on html tag objects, not using a recursive parse-again method
which may cause bad performance and huge memory allocation. The new
method also produced better parsed image objects with exact anchor text
references.
reger