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.
adjusted to smaller and 1-core devices.
- the workflow processor now starts no process at all. these are started
as soon as parser/condenser/indexing queues are filled.
- better abstraction
added solr highlighting / YaCy snippets to YaCy search results
- facets are now much more complete
- facets are computed and searched much faster
- snippet computation is done by solr if solr knows the snippet
superfluous. The target is to make a solr document as the core of YaCy
documents which would cause that many conversions can be removed. On the
way to this target the Equivalence of URIMetadataRow and URIMetadataNode
had to be removed to expose the usage of the old URIMetadataRow data
structure.
This refactoring already removes unneccessary conversions and should
make memory usage during indexing lower.
of the major CPU users during snippet verification. The class was not
efficient for two reasons:
- it used a too complex input stream; generated from sources and UTF8
byte-conversions. The BufferedReader applied a strong overhead.
- to feed data into the SentenceReader, multiple toString/getBytes had
been applied until a buffered Reader from an input stream was possible.
These superfluous conversions had been removed.
- the best source for the Sentence Reader is a String. Therefore the
production of Strings had been forced inside the Document class.
Michael Peter Christen