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Clusterpoint

Clusterpoint. Margarita Sudņika ms11077. RDBMS & NoSQL. Databases & tables → Document stores Columns, rows → Schemaless documents Scales UP → Scales UP & OUT Replications → Sharding & Replications For table like data → Unstructured data Legacy & mature → New. Clusterpoint.

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Clusterpoint

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  1. Clusterpoint Margarita Sudņika ms11077

  2. RDBMS & NoSQL Databases & tables → Document stores Columns, rows → Schemaless documents Scales UP → Scales UP & OUT Replications → Sharding & Replications For table like data → Unstructured data Legacy & mature → New

  3. Clusterpoint A scalable high-speed NoSQL database technology with Google-like search Manually ranking (svara piešķiršana) Solves 2 bigdataaccessproblems: • Long time waiting for query execution • Querry execution 0,005-0,5 seconds • Loadsofinformation

  4. Application Arhitecture HTTP Clusterpoint server software STAND-ALONE SERVER CLUSTER NODES (multi-server hardware) DOCUMENTS CUSTOMERS CONTACTS PROJECTS MAILS EMPLOYEES

  5. Clusterpoint Data storage model • xml Supported formats • Json • Xml • HTML • Text

  6. Features Full context search Unlimted database size Guaranteed querry size <0,5 s Clustering as default feature Scallable database mirroring Snippets with search hits Web friendly api Flexible data relevancy rules

  7. Access

  8. Search Free text Phrase Wildcards Patterns matches by lookup • John Smith In XML database structure Did you mean “...?” feature Faceted search and navigation Full data index for xml data

  9. API Simple, robust XML messagingXML request/response similar to SOAP Transport • http, https (post, get) • tcp • unix domain socket > 20 API commands Libraries: PHP, .NET (web service)

  10. API message <?xml version=”1.0” encoding=”REQUEST-ENCODING”?> <cpse:request xmlns:cpse=”www.clusterpoint.com”> <cpse:storage>storage name</cpse:storage> <cpse:command>command name</cpse:command> <cpse:timestamp>message date and time</cpse:timestamp> <cpse:requestid>message number</cpse:requestid> <cpse:application>creator of message</cpse:application> <cpse:user>user name</cpse:user> <cpse:password>user password</cpse:password> <cpse:reply_charset>reply encoding</cpse:reply_charset> <cpse:content> </cpse:content> </cpse:request> Lookup <document> <id>document id</id> </document> Insert <document> <id>document id</id> <title>document title</title> <rate>document rate</rate> <info>meta data</info> <site>document id</site> <text>textual information</text> <hidden>information that is not shown</hidden> </document> Search <query> search query </query> <docs> number of documents </docs> <offset> intend from the beginning </offset> <case_sensitive> boolean type parameter</case_sensitive> <relevance> boolean type parameter</relevance> <group_size> maximum from one group</group_size> <rate_from> FROM value </rate_from> <rete_to> TO value </rate_to>

  11. Platform Runs on *nix (tested on Linux and FreeBSD) Written in C/C++ Optimized for multi-core processors Source code is IP of Clusterpointwritten from the scratch PORTS Data tcp: 5550, 80 Unix domains sockets Cluster discovery UDP: 234.25.25.25:5550

  12. Parameters Disk space • 1.,5-2 times more than disk space • Data of 100 GB = 150-200 GB • The amount doesn’t include space for log files, as its possible rotate and backup files, • While file load and indexing size can increase 3-4 times, then return to normal size RAM • more RAM - more cached data –better performance • usually recomended >4 GB

  13. Use ComplementarySolving performance issues and bottlenecks of existing database systems StandaloneApplication is implemented using Clusterpoint DBMS USERS APP server Clusterpoint XML DBMS SQL XML USERS APP server

  14. Thank you

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