instead of loading the solr document, an index only for the last loading
time was created. This prevents that solr has to fetch from its index
while the index is created. Excessive re-loading of documents while
indexing has shown to produce deadlocks, so this should now be
prevented.
This makes possbile to set up much more advanced document crawl filters,
by filtering on one or more document indexed fields before inserting in
the index.
Especially for Turkish speaking users using "tr" as their system default
locale : strings for technical stuff (URLs, tag names, constants...)
must not be lower cased with the default locale, as 'I' doesn't becomes
'i' like in other locales such as "en", but becomes 'ı'.
to also support handling of urls w/o corresponding file-extension.
For this refactor use of document.getParserObject() to alway return a Parser (for clean logic)
and define/move the scraperObject as local var of AbstractParser.
Adjust related calls to getParserObject (where actually a scraperObject is wanted).
Addionally skip appending url token to parsed text for dht metadata entries
(by default returned as result by rwi index).
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.
hold a date for each URL to record when a url was first seen. This is
then used to overwrite the modification date for urls upon recrawl in
case that the first-seen date is before the latest document date. This
behaviour is necessary due to the common behaviour of content management
systems which attach always the current date to all documents. Using the
firstSeen database it is possible to approximate a real first document
creation date in case that the crawler starts frequently for the same
domain. As a result the search results ordered by date have a much
better quality and the usage of YaCy as search agent for latest news has
a better quality.
it is now possible to get the results in two steps:
- first retrieve all IDs as given for a query
- then retieve each document individually
This was necessary for very large result sets where a query may run for
hours and is possibly terminated by a solr-internal timeout. This occurs
regulary during postprocessing and therefore this commit may fix
unwanted postprocessing terminations.
during document parsing; instead use the same references that would also
be written into the webgraph. That should cause that the webgraph and
the citation index express the exact same semantic.
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.
- unique-postprocessing was destroying results from other
postprocessings; removed cross-updates as they had been not necessary
- unique-postprocessing did not restrict on same protocol
- inefficient concurrent update cache was redesigned completely
- increased limits for concurrent blocking queues to prevent early
time-out
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.
- added order option to solr queries to be able to retrieve document
lists in specific order, here: link length
- added HyperlinkEdge class which manages the link structure
- integrated the HyperlinkEdge class into clickdepth computation
- extended the linkstructure.json servlet to show also the clickdepth
and other statistic information
instead of TreeMaps)
- enhanced memory footprint of database indexes (by introduction of
optimize calls)
- optimize calls shrink the amount of used memory for index sets if they
are not changed afterwards any more
different from normal requests. This happens if the remote solr is
actually a solrCloud; in such cases the luke request returns only the
result of the single solr peer, not the whole cloud.
also done: some refactoring.
Michael Peter Christen