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.
solr to the YaCy built-in solr search servlet. Its not complete and not
fully correct (there is still a utf8 encoding problem) but it is a way
to get easily requests forwarded through YaCy to an external Solr.
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.
with metadata retrieval from connectors directly. This should cause
better usage of the cache. Automatically increase the metadata cache if
more memory is available.
- 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.
url along with the load date. While this takes much more memory, it
eliminates database lookups for getURL() requests, which happen equally
often. This speeds up remote solr configurations.
The resource observer is now able to recognize free disk space AND
available space for YaCy. The amount of space which is assigned for YaCy
are defined in new settings in the configuration file.
Furthermore, there is now a cleanup process which deletes files in case
that an autodelete is activated. The autodelete is now BY DEFAULT ON if
the disk space is low, which means that YaCy starts to delete documents
when the disk is full!
- redesigned the instance mirror class (which was a mess)
- added final method to close a searcher (which otherwise keeps a cache)
- changed cache clear method which iterates over resources and calls
clear to all caches in the searcher resources
- refactored all code which uses URIMetadataRow as standard for word
hash length and word hash ordering and moved that to the class 'Word',
becuase the class URIMetadataRow defined the old metadata data structure
and should be superfluous in the future
- removed unused methods from URIMetadataRow as preparation for further
removal of that class
- all non-dht targets (previously separated into 'robinson' for dht-like
queries and 'node' for solr queries) are non 'extra' peers, which are
queries using solr
- these extra-peers are now selected using a ranking on last-seen,
peer-tag-matches, node-peer flags, peer age, and link count. The ranking
is done using a weight and a random factor.
- the number of extra peers is 50% of the dht peers
- the dht peers now exclude too young peers to prevent bad results
during strong growth of the network
- the number of dht peers (and therefore extra-peers) is reduced when
the memory of the peer is low and/or some documents still appear in the
indexing-queue. This shall prevent a peer from deadlocks when p2p
queries are made in a fast sequence on weak hardware.
causes Solr error (and wordindex likely finds suggestion)
org.apache.solr.core.SolrCore org.apache.solr.common.SolrException: org.apache.solr.search.SyntaxError: Cannot parse 'text_t:""d"': Lexical error at line 1, column 12. Encountered: <EOF> after : ""
at org.apache.solr.handler.component.QueryComponent.prepare(QueryComponent.java:171)
at org.apache.solr.handler.component.SearchHandler.handleRequestBody(SearchHandler.java:187)
at org.apache.solr.handler.RequestHandlerBase.handleRequest(RequestHandlerBase.java:135)
at net.yacy.cora.federate.solr.connector.EmbeddedSolrConnector.query(EmbeddedSolrConnector.java:179)
at net.yacy.cora.federate.solr.connector.EmbeddedSolrConnector$DocListSearcher.<init>(EmbeddedSolrConnector.java:345)
at net.yacy.cora.federate.solr.connector.EmbeddedSolrConnector.getCountByQuery(EmbeddedSolrConnector.java:364)
at net.yacy.cora.federate.solr.connector.MirrorSolrConnector.getCountByQuery(MirrorSolrConnector.java:326)
at net.yacy.cora.federate.solr.connector.ConcurrentUpdateSolrConnector.getCountByQuery(ConcurrentUpdateSolrConnector.java:440)
at net.yacy.search.index.Segment.getWordCountGuess(Segment.java:464)
at net.yacy.data.DidYouMean.getSuggestions(DidYouMean.java:181)
at suggest.respond(suggest.java:73)
- 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.
as path for solr index dumps (instead of the SEGMENTS path). This will
make a maintenance of index backups easier. It will also provide a tool
to migrate from an freeworld index to a webportal index.
work around the unfolding process in Solr's BinaryResponseWriter.
This was a huge performance bottleneck in the embedded solr connector
and the problem is actually on Solr side, but we have now a workaround.
- This made it possible to abstract a high-performance index access
method which is implemented as method getDocumentListByParams. That
method is also implemented in the SolrServerConnector and provides a
very efficient access to a solr index if the index is embedded.
- a popular use of the document list retrieval is a result count which
can now also make use of the new method, via getDocumentCountByParams.
- enhanced the Error cache which now does not store error documents
within the ram cache if the document is also written to solr. When
documents are retrieved from the cache, they are partly read from the
ram cache and if not existent there, from the Solr index.
servlet since YaCy 1.63. This is much more performant for the client
than using the XMLResponseWriter because parsing of XML data is very CPU
intensive. Older YaCy peers are still requested using the
XMLResponseWriter but the majority of YaCy peers already respond with
the binary writer. This makes remote searches much faster and less CPU
intensive.
not-flushed Solr cache is now handled in this way:
- it is smaller by default
- an Solr-internal process is started to flush the cache periodically
(this does NOT clean the cache, just removes old objects)
- a Solr-external process (the standard YaCy cleanup-process) now has
direct access to the solr internal cache and flushes them completely.
The time frame for such a flush is defined by the cleanup-process
frequency, by default 10 minutes.
the embedded Solr (the default). This was obtained by cirumventing solrj
search encapsulation and the implementation of direct index access
methods to Solr.
The effect will not only be seen during search, but this has also a
strong effect on suggestions (much more) and less CPU power usage during
index distribution (which needs many search requests)