<property> <name>http.agent.name</name> <value></value> <description>HTTP 'User-Agent' request header. MUST NOT be empty - please set this to a single word uniquely related to your organization. NOTE: You should also check other related properties: http.robots.agents http.agent.description http.agent.url http.agent.email http.agent.version and set their values appropriately. </description> </property> <property> <name>http.agent.description</name> <value></value> <description>Further description of our bot- this text is used in the User-Agent header. It appears in parenthesis after the agent name. </description> </property> <property> <name>http.agent.url</name> <value></value> <description>A URL to advertise in the User-Agent header. This will appear in parenthesis after the agent name. Custom dictates that this should be a URL of a page explaining the purpose and behavior of this crawler. </description> </property> <property> <name>http.agent.email</name> <value></value> <description>An email address to advertise in the HTTP 'From' request header and User-Agent header. A good practice is to mangle this address (e.g. 'info at example dot com') to avoid spamming. </description> </property>
Katta is a scalable, failure tolerant, distributed, data storage for real time access.
Katta serves large, replicated, indices as shards to serve high loads and very large data sets. These indices can be of different type. Currently implementations are available for Lucene and Hadoop mapfiles.
* Makes serving large or high load indices easy
* Serves very large Lucene or Hadoop Mapfile indices as index shards on many servers
* Replicate shards on different servers for performance and fault-tolerance
* Supports pluggable network topologies
* Master fail-over
* Fast, lightweight, easy to integrate
* Plays well with Hadoop clusters
* Apache Version 2 License
U. Schindler, and I. Drost. Java Magazin, (2010)Zusätzlich interessante Punkte die im Artikel erwähnt werden:
1) Die Häufigkeit einzelner Suchanfragen ist meist zipf-verteilt.
2) Abstandsberechnung bei Geodaten über Haversinus.
3) Cartesian Tiers
4) Wissenschaftliches Infosystem PANGAEA
5) KML Regionen Dokumentation von Google
6) Geohshes.
D. Hiemstra, and C. Hauff. Multilingual and Multimodal Information Access Evaluation, volume 6360 of Lecture Notes in Computer Science, page 64--69. Berlin, Springer Verlag, (2010)
N. Ferro, and D. Harman. Multilingual Information Access Evaluation I. Text Retrieval Experiments, volume 6241 of Lecture Notes in Computer Science, Springer, Berlin / Heidelberg, (2010)