SlideShare ist ein Scribd-Unternehmen logo

LarKC Tutorial at ISWC 2009 - Architecture

•Als PPT, PDF herunterladen•
•
L
LarKC

The aim of the EU FP 7 Large-Scale Integrating Project LarKC is to develop the Large Knowledge Collider (LarKC, for short, pronounced “lark”), a platform for massive distributed incomplete reasoning that will remove the scalability barriers of currently existing reasoning systems for the Semantic Web. The LarKC platform is available at larkc.sourceforge.net. This talk, is part of a tutorial for early users of the LarKC platform, and describes the platform architecture

BildungTechnologie
1 von 31
LarKC Architecture and Technology Michael Witbrock, Cycorp Europe (+UIBK) with contributions from all LarKC developers
Realising the Architecture Workflow Support System Plug-in Registry Data Layer Plug-in API Data Layer API RDF Store Plug-in Manager
LarKC Plug-in API: General Plug-in Model ,[object Object],[object Object],[object Object],[object Object],[object Object],+ URI getIdentifier() + QoSInformation getQoSInformation() Plug-in ,[object Object],[object Object],[object Object],Plug-in description
LarKC Plug-in API: IDENTIFY ,[object Object],[object Object],[object Object],[object Object],+ Collection<InformationSet> identify (Query theQuery, Contract contract, Context context) Identifier
LarKC Plug-in API: TRANSFORM (1/2) ,[object Object],[object Object],[object Object],[object Object],[object Object],+ Set<Query> transform(Query theQuery, Contract theContract, Context theContext) QueryTransformer
LarKC Plug-in API: TRANSFORM (2/2) ,[object Object],[object Object],[object Object],[object Object],+ InformationSet transform(InformationSet theInformationSet, Contract theContract, Context theContext) InformationSetTransformer
LarKC Plug-in API: SELECT ,[object Object],[object Object],[object Object],[object Object],+ SetOfStatements select(SetOfStatements theSetOfStatements, Contract contract, Context context) Selecter
LarKC Plug-in API: REASON ,[object Object],[object Object],[object Object],[object Object],[object Object],+ V ariableBinding sparqlSelect(SPARQLQuery theQuery, SetOfStatements theSetOfStatements, Contract contract, Context context) + SetOfStatements sparqlConstruct(SPARQLQuery theQuery, SetOfStatements theSetOfStatements, Contract contract, Context context) + SetOfStatements sparqlDescribe(SPARQLQuery theQuery, SetOfStatements theSetOfStatements, Contract contract, Context context) + BooleanInformationSet sparqlAsk(SPARQLQuery theQuery, S etOfStatements theSetOfStatements, Contract contract, Context context) Reasoner
LarKC Plug-in API: DECIDE ,[object Object],[object Object],[object Object],+ V ariableBinding sparqlSelect(SPARQLQuery theQuery, QoSParameters theQoSParameters) + SetOfStatements sparqlConstruct(SPARQLQuery theQuery, QoSParameters theQoSParameters) + SetOfStatements sparqlDescribe(SPARQLQuery theQuery, QoSParameters theQoSParameters) + BooleanInformationSet sparqlAsk(SPARQLQuery theQuery, QoSParameters theQoSParameters) Decider
Released System: larkc.sourceforge.net ,[object Object],[object Object],[object Object],[object Object],[object Object],Decider Plug-in API Plug-in Manager Query Transformer Plug-in API Plug-in Manager Identifier Plug-in API Plug-in Manager Info. Set Transformer Plug-in API Plug-in Manager Selecter Plug-in API Plug-in Manager Reasoner Plug-in API Plug-in Registry Pipeline Support System
LarKC Plug-in API + Collection<InformationSet> identify (Query theQuery, Contract contract, Context context) Identifier + Set<Query> transform(Query theQuery, Contract theContract, Context theContext) QueryTransformer + InformationSet transform(InformationSet theInformationSet, Contract theContract, Context theContext) InformationSetTransformer + SetOfStatements select(SetOfStatements theSetOfStatements, Contract contract, Context context) Selecter + VariableBinding sparqlSelect(SPARQLQuery theQuery, SetOfStatements theSetOfStatements, Contract contract, Context context) + SetOfStatements sparqlConstruct(SPARQLQuery theQuery, SetOfStatements theSetOfStatements, Contract contract, Context context) + SetOfStatements sparqlDescribe(SPARQLQuery theQuery, SetOfStatements theSetOfStatements, Contract contract, Context context) + BooleanInformationSet sparqlAsk(SPARQLQuery theQuery, S etOfStatements theSetOfStatements, Contract contract, Context context) Reasoner + VariableBinding sparqlSelect(SPARQLQuery theQuery, QoSParameters theQoSParameters) + SetOfStatements sparqlConstruct(SPARQLQuery theQuery, QoSParameters theQoSParameters) + SetOfStatements sparqlDescribe(SPARQLQuery theQuery, QoSParameters theQoSParameters) + BooleanInformationSet sparqlAsk(SPARQLQuery theQuery, QoSParameters theQoSParameters) Decider ,[object Object],[object Object],[object Object],[object Object]
LarKC Plug-in API LarKC Architecture Data Layer API Pipeline Support System Plug-in Registry RDF Store RDF Store RDF Store RDF Doc RDF Doc RDF Doc Data Layer Decider Plug-in API Plug-in Manager Query Transformer Plug-in API Plug-in Manager Identifier Plug-in API Plug-in Manager Info. Set Transformer Plug-in API Plug-in Manager Selecter Plug-in API Plug-in Manager Reasoner Plug-in API Application Platform Utility Functionality APIs Plug-ins External systems External data sources Plug-in API Plug-in API Plug-in API Plug-in API Plug-in API Plug-in API
What does a workflow look like? Decider Plug-in API Plug-in Manager Query Transformer Plug-in API Plug-in Manager Identifier Plug-in API Plug-in Manager Info. Set Transformer Plug-in API Plug-in Manager Selecter Plug-in API Plug-in Manager Reasoner Plug-in API Plug-in Registry Workflow Support System RDF Store Identifier Info Set Transformer Reasoner Decider Selecter Query Transformer
What Does a Workflow Look Like? Decider Plug-in API Plug-in Manager Query Transformer Plug-in API Plug-in Manager Identifier Plug-in API Plug-in Manager Info. Set Transformer Plug-in API Plug-in Manager Selecter Plug-in API Plug-in Manager Reasoner Plug-in API Plug-in Registry Workflow Support System RDF Store Identifier Info Set Transformer Reasoner Decider Selecter Query Transformer Data Layer Data Layer Data Layer Data Layer RDF Graph RDF Graph RDF Graph RDF Graph RDF Graph RDF Graph Default Graph RDF Graph RDF Graph RDF Graph RDF Graph RDF Graph RDF Graph RDF Graph
LarKC Data Model :Transport By Reference RDF Graph Dataset: Collection of named graphs Labeled Set: Pointers to data Current Scale: O(10 10 ) triples RDF Graph RDF Graph RDF Graph RDF Graph RDF Graph Default Graph RDF Graph RDF Graph RDF Graph RDF Graph RDF Graph RDF Graph RDF Graph
What Does a Workflow Look Like? Decider Plug-in API Plug-in Manager Query Transformer Plug-in API Plug-in Manager Identifier Plug-in API Plug-in Manager Info. Set Transformer Plug-in API Plug-in Manager Selecter Plug-in API Plug-in Manager Reasoner Plug-in API Plug-in Registry Workflow Support System RDF Store Identifier Info Set Transformer Reasoner Decider Selecter Query Transformer Data Layer Data Layer Data Layer Data Layer RDF Graph RDF Graph RDF Graph RDF Graph RDF Graph RDF Graph Default Graph RDF Graph RDF Graph RDF Graph RDF Graph RDF Graph RDF Graph RDF Graph
What Does a Pipeline Look Like? Info Set Transformer Identifier Identifier Decider Plug-in API Plug-in Manager Query Transformer Plug-in API Plug-in Manager Identifier Plug-in API Plug-in Manager Info. Set Transformer Plug-in API Plug-in Manager Selecter Plug-in API Plug-in Manager Reasoner Plug-in API Plug-in Registry Wlorkflow Support System RDF Store Identifier Info Set Transformer Reasoner Decider Selecter Query Transformer Data Layer Data Layer Data Layer Data Layer
Remote and Heterogeneous Plug-ins Remote Plug-in Manager Adaptor External or non-Java Code TRANSFORM SPARQL-CycL Research Cyc TRANSFORM SPARQL- GATE API GATE IDENTIFY SPARQL SINDICE IDENTIFY SPARQL Medical Data Data Layer
What Does a Workflow Look Like? Info Set Transformer Identifier Identifier Info Set Transformer Reasoner Decider Plug-in API Plug-in Manager Query Transformer Plug-in API Plug-in Manager Identifier Plug-in API Plug-in Manager Info. Set Transformer Plug-in API Plug-in Manager Selecter Plug-in API Plug-in Manager Reasoner Plug-in API Plug-in Registry Workflow Support System RDF Store Identifier Info Set Transformer Reasoner Decider Selecter Query Transformer Data Layer Data Layer Data Layer Data Layer
Decider Using Plug-in Registry to Create Pipeline D 1.3.1 ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Q T I S R VB A Q T I S R VB B
LarKC Plug-ins ,[object Object],[object Object],[object Object],[object Object],Plug-in Manager Query Transformer Plug-in API Plug-in Manager Identifier Plug-in API ,[object Object],Plug-in Manager Transformer Plug-in API Plug-in Manager Identifier Plug-in API ransformer Transformer Transformer Plug-in Manager Identifier Plug-in API Plug-in Manager Identifier Plug-in API Plug-in Manager Selector Plug-in API Plug-in Manager Selector Plug-in API ,[object Object]
LarKC Data Layer Data Layer API Data Layer Data Layer API Pipeline Support System Plug-in Registry RDF Store RDF Store RDF Store RDF Doc RDF Doc RDF Doc Data Layer Decider Plug-in API Plug-in Manager Query Transformer Plug-in API Plug-in Manager Identifier Plug-in API Plug-in Manager Info. Set Transformer Plug-in API Plug-in Manager Selecter Plug-in API Plug-in Manager Reasoner Plug-in API Application Platform Utility Functionality APIs Plug-ins External systems External data sources
LarKC Data Layer ,[object Object],[object Object],[object Object],[object Object],[object Object],RDF Graph RDF Graph RDF Graph RDF Graph RDF Graph RDF Graph Default Graph RDF Graph RDF Graph RDF Graph RDF Graph RDF Graph RDF Graph RDF Graph Dataset Labeled Set
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],LarKC Data Layer Performance
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],LarKC Data Layer Evaluation: Linked Data
Plug-in Architecture Signs of Success ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Plug-in Manager Identifier Plug-in API
Active and Ready for the Public ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Project Timeline 14 Surveys (plug-ins, platform) & Requirements (use cases) Prototype Internal Release Public Release Final Release 42 0 6 18 33 10 Plug-ins Use Cases V1 Use Cases V2 Use Cases V3 Data caching Offer computing resources Anytime behaviour Monitoring & instrumentation
Rapid Progress, but We’re Not Finished… ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Data Layer API Pipeline Support System Plug-in Registry RDF Store RDF Store RDF Store RDF Doc RDF Doc RDF Doc Data Layer Decider Plug-in API Plug-in Manager Query Transformer Plug-in API Plug-in Manager Identifier Plug-in API Plug-in Manager Info. Set Transformer Plug-in API Plug-in Manager Selecter Plug-in API Plug-in Manager Reasoner Plug-in API Application ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Detailed information in D5.3.1 Requirements Analysis and report on lessons learned during prototyping Requirements (WP 5)
[object Object],[object Object],[object Object],[object Object],[object Object],Open Issues & Next Steps ,[object Object],[object Object],Platform validation Early Adopters
fin

Empfohlen

Iswc 2009 LarKC Tutorial: Architecture
Iswc 2009 LarKC Tutorial: ArchitectureIswc 2009 LarKC Tutorial: Architecture
Iswc 2009 LarKC Tutorial: ArchitectureMichael Witbrock
 
IQPC Canada XML 2001: How to Use XML Parsing to Enhance Electronic Communication
IQPC Canada XML 2001: How to Use XML Parsing to Enhance Electronic CommunicationIQPC Canada XML 2001: How to Use XML Parsing to Enhance Electronic Communication
IQPC Canada XML 2001: How to Use XML Parsing to Enhance Electronic CommunicationTed Leung
 
Spark Cassandra Connector: Past, Present, and Future
Spark Cassandra Connector: Past, Present, and FutureSpark Cassandra Connector: Past, Present, and Future
Spark Cassandra Connector: Past, Present, and FutureRussell Spitzer
 
How Pony ORM translates Python generators to SQL queries
How Pony ORM translates Python generators to SQL queriesHow Pony ORM translates Python generators to SQL queries
How Pony ORM translates Python generators to SQL queriesponyorm
 
SQL on everything, in memory
SQL on everything, in memorySQL on everything, in memory
SQL on everything, in memoryJulian Hyde
 
Topic-based Federated Query Engine
Topic-based Federated Query EngineTopic-based Federated Query Engine
Topic-based Federated Query EngineEster Giallonardo
 
20140908 spark sql & catalyst
20140908 spark sql & catalyst20140908 spark sql & catalyst
20140908 spark sql & catalystTakuya UESHIN
 
New developments in open source ecosystem spark3.0 koalas delta lake
New developments in open source ecosystem spark3.0 koalas delta lakeNew developments in open source ecosystem spark3.0 koalas delta lake
New developments in open source ecosystem spark3.0 koalas delta lakeXiao Li
 

Empfohlen

Iswc 2009 LarKC Tutorial: Architecture
Iswc 2009 LarKC Tutorial: ArchitectureIswc 2009 LarKC Tutorial: Architecture
Iswc 2009 LarKC Tutorial: ArchitectureMichael Witbrock
 
IQPC Canada XML 2001: How to Use XML Parsing to Enhance Electronic Communication
IQPC Canada XML 2001: How to Use XML Parsing to Enhance Electronic CommunicationIQPC Canada XML 2001: How to Use XML Parsing to Enhance Electronic Communication
IQPC Canada XML 2001: How to Use XML Parsing to Enhance Electronic CommunicationTed Leung
 
Spark Cassandra Connector: Past, Present, and Future
Spark Cassandra Connector: Past, Present, and FutureSpark Cassandra Connector: Past, Present, and Future
Spark Cassandra Connector: Past, Present, and FutureRussell Spitzer
 
How Pony ORM translates Python generators to SQL queries
How Pony ORM translates Python generators to SQL queriesHow Pony ORM translates Python generators to SQL queries
How Pony ORM translates Python generators to SQL queriesponyorm
 
SQL on everything, in memory
SQL on everything, in memorySQL on everything, in memory
SQL on everything, in memoryJulian Hyde
 
Topic-based Federated Query Engine
Topic-based Federated Query EngineTopic-based Federated Query Engine
Topic-based Federated Query EngineEster Giallonardo
 
20140908 spark sql & catalyst
20140908 spark sql & catalyst20140908 spark sql & catalyst
20140908 spark sql & catalystTakuya UESHIN
 
New developments in open source ecosystem spark3.0 koalas delta lake
New developments in open source ecosystem spark3.0 koalas delta lakeNew developments in open source ecosystem spark3.0 koalas delta lake
New developments in open source ecosystem spark3.0 koalas delta lakeXiao Li
 
Overview of running R in the Oracle Database
Overview of running R in the Oracle DatabaseOverview of running R in the Oracle Database
Overview of running R in the Oracle DatabaseBrendan Tierney
 
Building a modern Application with DataFrames
Building a modern Application with DataFramesBuilding a modern Application with DataFrames
Building a modern Application with DataFramesSpark Summit
 
Kotlin Receiver Types 介紹
Kotlin Receiver Types 介紹Kotlin Receiver Types 介紹
Kotlin Receiver Types 介紹Kros Huang
 
Functional Composition of Sensor Web APIs
Functional Composition of Sensor Web APIsFunctional Composition of Sensor Web APIs
Functional Composition of Sensor Web APIsRuben Verborgh
 
Easy, scalable, fault tolerant stream processing with structured streaming - ...
Easy, scalable, fault tolerant stream processing with structured streaming - ...Easy, scalable, fault tolerant stream processing with structured streaming - ...
Easy, scalable, fault tolerant stream processing with structured streaming - ...Databricks
 
From Big to Fast Data. How #kafka and #kafka-connect can redefine you ETL and...
From Big to Fast Data. How #kafka and #kafka-connect can redefine you ETL and...From Big to Fast Data. How #kafka and #kafka-connect can redefine you ETL and...
From Big to Fast Data. How #kafka and #kafka-connect can redefine you ETL and...Landoop Ltd
 
Doctrine ORM with eZ Platform REST API and GraphQL
Doctrine ORM with eZ Platform REST API and GraphQLDoctrine ORM with eZ Platform REST API and GraphQL
Doctrine ORM with eZ Platform REST API and GraphQLJani Tarvainen
 
Apache Calcite: A Foundational Framework for Optimized Query Processing Over ...
Apache Calcite: A Foundational Framework for Optimized Query Processing Over ...Apache Calcite: A Foundational Framework for Optimized Query Processing Over ...
Apache Calcite: A Foundational Framework for Optimized Query Processing Over ...Julian Hyde
 
[Spark meetup] Spark Streaming Overview
[Spark meetup] Spark Streaming Overview[Spark meetup] Spark Streaming Overview
[Spark meetup] Spark Streaming OverviewStratio
 
Session 40 : SAGA Overview and Introduction
Session 40 : SAGA Overview and Introduction Session 40 : SAGA Overview and Introduction
Session 40 : SAGA Overview and Introduction ISSGC Summer School
 
OGSA-DAI DQP: A Developer's View
OGSA-DAI DQP: A Developer's ViewOGSA-DAI DQP: A Developer's View
OGSA-DAI DQP: A Developer's ViewBartosz Dobrzelecki
 
Why You Should Use TAPIs
Why You Should Use TAPIsWhy You Should Use TAPIs
Why You Should Use TAPIsJeffrey Kemp
 
OVH-Change Data Capture in production with Apache Flink - Meetup Rennes 2019-...
OVH-Change Data Capture in production with Apache Flink - Meetup Rennes 2019-...OVH-Change Data Capture in production with Apache Flink - Meetup Rennes 2019-...
OVH-Change Data Capture in production with Apache Flink - Meetup Rennes 2019-...Yann Pauly
 
Vertica And Spark: Connecting Computation And Data
Vertica And Spark: Connecting Computation And DataVertica And Spark: Connecting Computation And Data
Vertica And Spark: Connecting Computation And DataSpark Summit
 
Multiplaform Solution for Graph Datasources
Multiplaform Solution for Graph DatasourcesMultiplaform Solution for Graph Datasources
Multiplaform Solution for Graph DatasourcesStratio
 
Introduction to Spark SQL & Catalyst
Introduction to Spark SQL & CatalystIntroduction to Spark SQL & Catalyst
Introduction to Spark SQL & CatalystTakuya UESHIN
 
Drill / SQL / Optiq
Drill / SQL / OptiqDrill / SQL / Optiq
Drill / SQL / OptiqJulian Hyde
 
Apache Spark, the Next Generation Cluster Computing
Apache Spark, the Next Generation Cluster ComputingApache Spark, the Next Generation Cluster Computing
Apache Spark, the Next Generation Cluster ComputingGerger
 
Spark Streaming @ Berlin Apache Spark Meetup, March 2015
Spark Streaming @ Berlin Apache Spark Meetup, March 2015Spark Streaming @ Berlin Apache Spark Meetup, March 2015
Spark Streaming @ Berlin Apache Spark Meetup, March 2015Stratio
 
Riak 2.0 : For Beginners, and Everyone Else
Riak 2.0 : For Beginners, and Everyone ElseRiak 2.0 : For Beginners, and Everyone Else
Riak 2.0 : For Beginners, and Everyone ElseEngin Yoeyen
 
LarKC Tutorial at ISWC 2009 - Introduction
LarKC Tutorial at ISWC 2009 - IntroductionLarKC Tutorial at ISWC 2009 - Introduction
LarKC Tutorial at ISWC 2009 - IntroductionLarKC
 
LarKC Tutorial at ISWC 2009 - Parallelisation
LarKC Tutorial at ISWC 2009 - ParallelisationLarKC Tutorial at ISWC 2009 - Parallelisation
LarKC Tutorial at ISWC 2009 - ParallelisationLarKC
 

Weitere ähnliche Inhalte

Was ist angesagt?

Overview of running R in the Oracle Database
Overview of running R in the Oracle DatabaseOverview of running R in the Oracle Database
Overview of running R in the Oracle DatabaseBrendan Tierney
 
Building a modern Application with DataFrames
Building a modern Application with DataFramesBuilding a modern Application with DataFrames
Building a modern Application with DataFramesSpark Summit
 
Kotlin Receiver Types 介紹
Kotlin Receiver Types 介紹Kotlin Receiver Types 介紹
Kotlin Receiver Types 介紹Kros Huang
 
Functional Composition of Sensor Web APIs
Functional Composition of Sensor Web APIsFunctional Composition of Sensor Web APIs
Functional Composition of Sensor Web APIsRuben Verborgh
 
Easy, scalable, fault tolerant stream processing with structured streaming - ...
Easy, scalable, fault tolerant stream processing with structured streaming - ...Easy, scalable, fault tolerant stream processing with structured streaming - ...
Easy, scalable, fault tolerant stream processing with structured streaming - ...Databricks
 
From Big to Fast Data. How #kafka and #kafka-connect can redefine you ETL and...
From Big to Fast Data. How #kafka and #kafka-connect can redefine you ETL and...From Big to Fast Data. How #kafka and #kafka-connect can redefine you ETL and...
From Big to Fast Data. How #kafka and #kafka-connect can redefine you ETL and...Landoop Ltd
 
Doctrine ORM with eZ Platform REST API and GraphQL
Doctrine ORM with eZ Platform REST API and GraphQLDoctrine ORM with eZ Platform REST API and GraphQL
Doctrine ORM with eZ Platform REST API and GraphQLJani Tarvainen
 
Apache Calcite: A Foundational Framework for Optimized Query Processing Over ...
Apache Calcite: A Foundational Framework for Optimized Query Processing Over ...Apache Calcite: A Foundational Framework for Optimized Query Processing Over ...
Apache Calcite: A Foundational Framework for Optimized Query Processing Over ...Julian Hyde
 
[Spark meetup] Spark Streaming Overview
[Spark meetup] Spark Streaming Overview[Spark meetup] Spark Streaming Overview
[Spark meetup] Spark Streaming OverviewStratio
 
Session 40 : SAGA Overview and Introduction
Session 40 : SAGA Overview and Introduction Session 40 : SAGA Overview and Introduction
Session 40 : SAGA Overview and Introduction ISSGC Summer School
 
OGSA-DAI DQP: A Developer's View
OGSA-DAI DQP: A Developer's ViewOGSA-DAI DQP: A Developer's View
OGSA-DAI DQP: A Developer's ViewBartosz Dobrzelecki
 
Why You Should Use TAPIs
Why You Should Use TAPIsWhy You Should Use TAPIs
Why You Should Use TAPIsJeffrey Kemp
 
OVH-Change Data Capture in production with Apache Flink - Meetup Rennes 2019-...
OVH-Change Data Capture in production with Apache Flink - Meetup Rennes 2019-...OVH-Change Data Capture in production with Apache Flink - Meetup Rennes 2019-...
OVH-Change Data Capture in production with Apache Flink - Meetup Rennes 2019-...Yann Pauly
 
Vertica And Spark: Connecting Computation And Data
Vertica And Spark: Connecting Computation And DataVertica And Spark: Connecting Computation And Data
Vertica And Spark: Connecting Computation And DataSpark Summit
 
Multiplaform Solution for Graph Datasources
Multiplaform Solution for Graph DatasourcesMultiplaform Solution for Graph Datasources
Multiplaform Solution for Graph DatasourcesStratio
 
Introduction to Spark SQL & Catalyst
Introduction to Spark SQL & CatalystIntroduction to Spark SQL & Catalyst
Introduction to Spark SQL & CatalystTakuya UESHIN
 
Drill / SQL / Optiq
Drill / SQL / OptiqDrill / SQL / Optiq
Drill / SQL / OptiqJulian Hyde
 
Apache Spark, the Next Generation Cluster Computing
Apache Spark, the Next Generation Cluster ComputingApache Spark, the Next Generation Cluster Computing
Apache Spark, the Next Generation Cluster ComputingGerger
 
Spark Streaming @ Berlin Apache Spark Meetup, March 2015
Spark Streaming @ Berlin Apache Spark Meetup, March 2015Spark Streaming @ Berlin Apache Spark Meetup, March 2015
Spark Streaming @ Berlin Apache Spark Meetup, March 2015Stratio
 
Riak 2.0 : For Beginners, and Everyone Else
Riak 2.0 : For Beginners, and Everyone ElseRiak 2.0 : For Beginners, and Everyone Else
Riak 2.0 : For Beginners, and Everyone ElseEngin Yoeyen
 

Was ist angesagt? (20)

Overview of running R in the Oracle Database
Overview of running R in the Oracle DatabaseOverview of running R in the Oracle Database
Overview of running R in the Oracle Database
 
Building a modern Application with DataFrames
Building a modern Application with DataFramesBuilding a modern Application with DataFrames
Building a modern Application with DataFrames
 
Kotlin Receiver Types 介紹
Kotlin Receiver Types 介紹Kotlin Receiver Types 介紹
Kotlin Receiver Types 介紹
 
Functional Composition of Sensor Web APIs
Functional Composition of Sensor Web APIsFunctional Composition of Sensor Web APIs
Functional Composition of Sensor Web APIs
 
Easy, scalable, fault tolerant stream processing with structured streaming - ...
Easy, scalable, fault tolerant stream processing with structured streaming - ...Easy, scalable, fault tolerant stream processing with structured streaming - ...
Easy, scalable, fault tolerant stream processing with structured streaming - ...
 
From Big to Fast Data. How #kafka and #kafka-connect can redefine you ETL and...
From Big to Fast Data. How #kafka and #kafka-connect can redefine you ETL and...From Big to Fast Data. How #kafka and #kafka-connect can redefine you ETL and...
From Big to Fast Data. How #kafka and #kafka-connect can redefine you ETL and...
 
Doctrine ORM with eZ Platform REST API and GraphQL
Doctrine ORM with eZ Platform REST API and GraphQLDoctrine ORM with eZ Platform REST API and GraphQL
Doctrine ORM with eZ Platform REST API and GraphQL
 
Apache Calcite: A Foundational Framework for Optimized Query Processing Over ...
Apache Calcite: A Foundational Framework for Optimized Query Processing Over ...Apache Calcite: A Foundational Framework for Optimized Query Processing Over ...
Apache Calcite: A Foundational Framework for Optimized Query Processing Over ...
 
[Spark meetup] Spark Streaming Overview
[Spark meetup] Spark Streaming Overview[Spark meetup] Spark Streaming Overview
[Spark meetup] Spark Streaming Overview
 
Session 40 : SAGA Overview and Introduction
Session 40 : SAGA Overview and Introduction Session 40 : SAGA Overview and Introduction
Session 40 : SAGA Overview and Introduction
 
OGSA-DAI DQP: A Developer's View
OGSA-DAI DQP: A Developer's ViewOGSA-DAI DQP: A Developer's View
OGSA-DAI DQP: A Developer's View
 
Why You Should Use TAPIs
Why You Should Use TAPIsWhy You Should Use TAPIs
Why You Should Use TAPIs
 
OVH-Change Data Capture in production with Apache Flink - Meetup Rennes 2019-...
OVH-Change Data Capture in production with Apache Flink - Meetup Rennes 2019-...OVH-Change Data Capture in production with Apache Flink - Meetup Rennes 2019-...
OVH-Change Data Capture in production with Apache Flink - Meetup Rennes 2019-...
 
Vertica And Spark: Connecting Computation And Data
Vertica And Spark: Connecting Computation And DataVertica And Spark: Connecting Computation And Data
Vertica And Spark: Connecting Computation And Data
 
Multiplaform Solution for Graph Datasources
Multiplaform Solution for Graph DatasourcesMultiplaform Solution for Graph Datasources
Multiplaform Solution for Graph Datasources
 
Introduction to Spark SQL & Catalyst
Introduction to Spark SQL & CatalystIntroduction to Spark SQL & Catalyst
Introduction to Spark SQL & Catalyst
 
Drill / SQL / Optiq
Drill / SQL / OptiqDrill / SQL / Optiq
Drill / SQL / Optiq
 
Apache Spark, the Next Generation Cluster Computing
Apache Spark, the Next Generation Cluster ComputingApache Spark, the Next Generation Cluster Computing
Apache Spark, the Next Generation Cluster Computing
 
Spark Streaming @ Berlin Apache Spark Meetup, March 2015
Spark Streaming @ Berlin Apache Spark Meetup, March 2015Spark Streaming @ Berlin Apache Spark Meetup, March 2015
Spark Streaming @ Berlin Apache Spark Meetup, March 2015
 
Riak 2.0 : For Beginners, and Everyone Else
Riak 2.0 : For Beginners, and Everyone ElseRiak 2.0 : For Beginners, and Everyone Else
Riak 2.0 : For Beginners, and Everyone Else
 

Andere mochten auch

LarKC Tutorial at ISWC 2009 - Introduction
LarKC Tutorial at ISWC 2009 - IntroductionLarKC Tutorial at ISWC 2009 - Introduction
LarKC Tutorial at ISWC 2009 - IntroductionLarKC
 
LarKC Tutorial at ISWC 2009 - Parallelisation
LarKC Tutorial at ISWC 2009 - ParallelisationLarKC Tutorial at ISWC 2009 - Parallelisation
LarKC Tutorial at ISWC 2009 - ParallelisationLarKC
 
LarKC Tutorial at ISWC 2009 - Urban Computing
LarKC Tutorial at ISWC 2009 - Urban ComputingLarKC Tutorial at ISWC 2009 - Urban Computing
LarKC Tutorial at ISWC 2009 - Urban ComputingLarKC
 
Integrando C com Python
Integrando C com PythonIntegrando C com Python
Integrando C com Pythongsroma
 
Introduction to CLIPS Expert System
Introduction to CLIPS Expert SystemIntroduction to CLIPS Expert System
Introduction to CLIPS Expert SystemMotaz Saad
 

Andere mochten auch (8)

LarKC Tutorial at ISWC 2009 - Introduction
LarKC Tutorial at ISWC 2009 - IntroductionLarKC Tutorial at ISWC 2009 - Introduction
LarKC Tutorial at ISWC 2009 - Introduction
 
LarKC Tutorial at ISWC 2009 - Parallelisation
LarKC Tutorial at ISWC 2009 - ParallelisationLarKC Tutorial at ISWC 2009 - Parallelisation
LarKC Tutorial at ISWC 2009 - Parallelisation
 
LarKC Tutorial at ISWC 2009 - Urban Computing
LarKC Tutorial at ISWC 2009 - Urban ComputingLarKC Tutorial at ISWC 2009 - Urban Computing
LarKC Tutorial at ISWC 2009 - Urban Computing
 
Integrando C com Python
Integrando C com PythonIntegrando C com Python
Integrando C com Python
 
CLIPS
CLIPS CLIPS
CLIPS
 
CLIPS Basic Student Guide
CLIPS Basic Student GuideCLIPS Basic Student Guide
CLIPS Basic Student Guide
 
Inference engine
Inference engineInference engine
Inference engine
 
Introduction to CLIPS Expert System
Introduction to CLIPS Expert SystemIntroduction to CLIPS Expert System
Introduction to CLIPS Expert System
 

Ähnlich wie LarKC Tutorial at ISWC 2009 - Architecture

Web Scale Reasoning and the LarKC Project
Web Scale Reasoning and the LarKC ProjectWeb Scale Reasoning and the LarKC Project
Web Scale Reasoning and the LarKC ProjectSaltlux Inc.
 
Parallelizing Existing R Packages
Parallelizing Existing R PackagesParallelizing Existing R Packages
Parallelizing Existing R PackagesCraig Warman
 
Apache spark - Architecture , Overview & libraries
Apache spark - Architecture , Overview & librariesApache spark - Architecture , Overview & libraries
Apache spark - Architecture , Overview & librariesWalaa Hamdy Assy
 
Apache Spark - Intro to Large-scale recommendations with Apache Spark and Python
Apache Spark - Intro to Large-scale recommendations with Apache Spark and PythonApache Spark - Intro to Large-scale recommendations with Apache Spark and Python
Apache Spark - Intro to Large-scale recommendations with Apache Spark and PythonChristian Perone
 
Refactoring Design Patterns the Functional Way (in Scala)
Refactoring Design Patterns the Functional Way (in Scala)Refactoring Design Patterns the Functional Way (in Scala)
Refactoring Design Patterns the Functional Way (in Scala)Kfir Bloch
 
Design pattern-refactor-functional
Design pattern-refactor-functionalDesign pattern-refactor-functional
Design pattern-refactor-functionalKfir Bloch
 
6° Sessione - Ambiti applicativi nella ricerca di tecnologie statistiche avan...
6° Sessione - Ambiti applicativi nella ricerca di tecnologie statistiche avan...6° Sessione - Ambiti applicativi nella ricerca di tecnologie statistiche avan...
6° Sessione - Ambiti applicativi nella ricerca di tecnologie statistiche avan...Jürgen Ambrosi
 
High-level Programming Languages: Apache Pig and Pig Latin
High-level Programming Languages: Apache Pig and Pig LatinHigh-level Programming Languages: Apache Pig and Pig Latin
High-level Programming Languages: Apache Pig and Pig LatinPietro Michiardi
 
Visualizing Big Data in Realtime
Visualizing Big Data in RealtimeVisualizing Big Data in Realtime
Visualizing Big Data in RealtimeDataWorks Summit
 
Parallelize R Code Using Apache Spark
Parallelize R Code Using Apache Spark Parallelize R Code Using Apache Spark
Parallelize R Code Using Apache Spark Databricks
 
A Tale of Two APIs: Using Spark Streaming In Production
A Tale of Two APIs: Using Spark Streaming In ProductionA Tale of Two APIs: Using Spark Streaming In Production
A Tale of Two APIs: Using Spark Streaming In ProductionLightbend
 
ScalaTo July 2019 - No more struggles with Apache Spark workloads in production
ScalaTo July 2019 - No more struggles with Apache Spark workloads in productionScalaTo July 2019 - No more struggles with Apache Spark workloads in production
ScalaTo July 2019 - No more struggles with Apache Spark workloads in productionChetan Khatri
 
Sustainable queryable access to Linked Data
Sustainable queryable access to Linked DataSustainable queryable access to Linked Data
Sustainable queryable access to Linked DataRuben Verborgh
 
Building Scalable Data Pipelines - 2016 DataPalooza Seattle
Building Scalable Data Pipelines - 2016 DataPalooza SeattleBuilding Scalable Data Pipelines - 2016 DataPalooza Seattle
Building Scalable Data Pipelines - 2016 DataPalooza SeattleEvan Chan
 
Apache® Spark™ 1.6 presented by Databricks co-founder Patrick Wendell
Apache® Spark™ 1.6 presented by Databricks co-founder Patrick WendellApache® Spark™ 1.6 presented by Databricks co-founder Patrick Wendell
Apache® Spark™ 1.6 presented by Databricks co-founder Patrick WendellDatabricks
 
Dot Net 串接 SAP
Dot Net 串接 SAPDot Net 串接 SAP
Dot Net 串接 SAPLearningTech
 
Synchronize AD and OpenLDAP with LSC
Synchronize AD and OpenLDAP with LSCSynchronize AD and OpenLDAP with LSC
Synchronize AD and OpenLDAP with LSCLDAPCon
 
Simplifying Apache Cascading
Simplifying Apache CascadingSimplifying Apache Cascading
Simplifying Apache CascadingMing Yuan
 
Microsoft R - ScaleR Overview
Microsoft R - ScaleR OverviewMicrosoft R - ScaleR Overview
Microsoft R - ScaleR OverviewKhalid Salama
 

Ähnlich wie LarKC Tutorial at ISWC 2009 - Architecture (20)

Web Scale Reasoning and the LarKC Project
Web Scale Reasoning and the LarKC ProjectWeb Scale Reasoning and the LarKC Project
Web Scale Reasoning and the LarKC Project
 
Parallelizing Existing R Packages
Parallelizing Existing R PackagesParallelizing Existing R Packages
Parallelizing Existing R Packages
 
Apache spark - Architecture , Overview & libraries
Apache spark - Architecture , Overview & librariesApache spark - Architecture , Overview & libraries
Apache spark - Architecture , Overview & libraries
 
Apache Spark - Intro to Large-scale recommendations with Apache Spark and Python
Apache Spark - Intro to Large-scale recommendations with Apache Spark and PythonApache Spark - Intro to Large-scale recommendations with Apache Spark and Python
Apache Spark - Intro to Large-scale recommendations with Apache Spark and Python
 
Refactoring Design Patterns the Functional Way (in Scala)
Refactoring Design Patterns the Functional Way (in Scala)Refactoring Design Patterns the Functional Way (in Scala)
Refactoring Design Patterns the Functional Way (in Scala)
 
Design pattern-refactor-functional
Design pattern-refactor-functionalDesign pattern-refactor-functional
Design pattern-refactor-functional
 
6° Sessione - Ambiti applicativi nella ricerca di tecnologie statistiche avan...
6° Sessione - Ambiti applicativi nella ricerca di tecnologie statistiche avan...6° Sessione - Ambiti applicativi nella ricerca di tecnologie statistiche avan...
6° Sessione - Ambiti applicativi nella ricerca di tecnologie statistiche avan...
 
High-level Programming Languages: Apache Pig and Pig Latin
High-level Programming Languages: Apache Pig and Pig LatinHigh-level Programming Languages: Apache Pig and Pig Latin
High-level Programming Languages: Apache Pig and Pig Latin
 
Visualizing Big Data in Realtime
Visualizing Big Data in RealtimeVisualizing Big Data in Realtime
Visualizing Big Data in Realtime
 
Parallelize R Code Using Apache Spark
Parallelize R Code Using Apache Spark Parallelize R Code Using Apache Spark
Parallelize R Code Using Apache Spark
 
A Tale of Two APIs: Using Spark Streaming In Production
A Tale of Two APIs: Using Spark Streaming In ProductionA Tale of Two APIs: Using Spark Streaming In Production
A Tale of Two APIs: Using Spark Streaming In Production
 
SPARQList
SPARQListSPARQList
SPARQList
 
ScalaTo July 2019 - No more struggles with Apache Spark workloads in production
ScalaTo July 2019 - No more struggles with Apache Spark workloads in productionScalaTo July 2019 - No more struggles with Apache Spark workloads in production
ScalaTo July 2019 - No more struggles with Apache Spark workloads in production
 
Sustainable queryable access to Linked Data
Sustainable queryable access to Linked DataSustainable queryable access to Linked Data
Sustainable queryable access to Linked Data
 
Building Scalable Data Pipelines - 2016 DataPalooza Seattle
Building Scalable Data Pipelines - 2016 DataPalooza SeattleBuilding Scalable Data Pipelines - 2016 DataPalooza Seattle
Building Scalable Data Pipelines - 2016 DataPalooza Seattle
 
Apache® Spark™ 1.6 presented by Databricks co-founder Patrick Wendell
Apache® Spark™ 1.6 presented by Databricks co-founder Patrick WendellApache® Spark™ 1.6 presented by Databricks co-founder Patrick Wendell
Apache® Spark™ 1.6 presented by Databricks co-founder Patrick Wendell
 
Dot Net 串接 SAP
Dot Net 串接 SAPDot Net 串接 SAP
Dot Net 串接 SAP
 
Synchronize AD and OpenLDAP with LSC
Synchronize AD and OpenLDAP with LSCSynchronize AD and OpenLDAP with LSC
Synchronize AD and OpenLDAP with LSC
 
Simplifying Apache Cascading
Simplifying Apache CascadingSimplifying Apache Cascading
Simplifying Apache Cascading
 
Microsoft R - ScaleR Overview
Microsoft R - ScaleR OverviewMicrosoft R - ScaleR Overview
Microsoft R - ScaleR Overview
 

Kürzlich hochgeladen

Full Stack Web Development Course for Beginners
Full Stack Web Development Course for BeginnersFull Stack Web Development Course for Beginners
Full Stack Web Development Course for BeginnersSabitha Banu
 
Daily Lesson Plan in Mathematics Quarter 4
Daily Lesson Plan in Mathematics Quarter 4Daily Lesson Plan in Mathematics Quarter 4
Daily Lesson Plan in Mathematics Quarter 4JOYLYNSAMANIEGO
 
HỌC TỐT TIẾNG ANH 11 THEO CHƯƠNG TRÌNH GLOBAL SUCCESS ĐÁP ÁN CHI TIẾT - CẢ NĂ...
HỌC TỐT TIẾNG ANH 11 THEO CHƯƠNG TRÌNH GLOBAL SUCCESS ĐÁP ÁN CHI TIẾT - CẢ NĂ...HỌC TỐT TIẾNG ANH 11 THEO CHƯƠNG TRÌNH GLOBAL SUCCESS ĐÁP ÁN CHI TIẾT - CẢ NĂ...
HỌC TỐT TIẾNG ANH 11 THEO CHƯƠNG TRÌNH GLOBAL SUCCESS ĐÁP ÁN CHI TIẾT - CẢ NĂ...Nguyen Thanh Tu Collection
 
4.16.24 Poverty and Precarity--Desmond.pptx
4.16.24 Poverty and Precarity--Desmond.pptx4.16.24 Poverty and Precarity--Desmond.pptx
4.16.24 Poverty and Precarity--Desmond.pptxmary850239
 
4.16.24 21st Century Movements for Black Lives.pptx
4.16.24 21st Century Movements for Black Lives.pptx4.16.24 21st Century Movements for Black Lives.pptx
4.16.24 21st Century Movements for Black Lives.pptxmary850239
 
Concurrency Control in Database Management system
Concurrency Control in Database Management systemConcurrency Control in Database Management system
Concurrency Control in Database Management systemChristalin Nelson
 
Active Learning Strategies (in short ALS).pdf
Active Learning Strategies (in short ALS).pdfActive Learning Strategies (in short ALS).pdf
Active Learning Strategies (in short ALS).pdfPatidar M
 
ANG SEKTOR NG agrikultura.pptx QUARTER 4
ANG SEKTOR NG agrikultura.pptx QUARTER 4ANG SEKTOR NG agrikultura.pptx QUARTER 4
ANG SEKTOR NG agrikultura.pptx QUARTER 4MiaBumagat1
 
Keynote by Prof. Wurzer at Nordex about IP-design
Keynote by Prof. Wurzer at Nordex about IP-designKeynote by Prof. Wurzer at Nordex about IP-design
Keynote by Prof. Wurzer at Nordex about IP-designMIPLM
 
Field Attribute Index Feature in Odoo 17
Field Attribute Index Feature in Odoo 17Field Attribute Index Feature in Odoo 17
Field Attribute Index Feature in Odoo 17Celine George
 
INTRODUCTION TO CATHOLIC CHRISTOLOGY.pptx
INTRODUCTION TO CATHOLIC CHRISTOLOGY.pptxINTRODUCTION TO CATHOLIC CHRISTOLOGY.pptx
INTRODUCTION TO CATHOLIC CHRISTOLOGY.pptxHumphrey A Beña
 
How to do quick user assign in kanban in Odoo 17 ERP
How to do quick user assign in kanban in Odoo 17 ERPHow to do quick user assign in kanban in Odoo 17 ERP
How to do quick user assign in kanban in Odoo 17 ERPCeline George
 
Food processing presentation for bsc agriculture hons
Food processing presentation for bsc agriculture honsFood processing presentation for bsc agriculture hons
Food processing presentation for bsc agriculture honsManeerUddin
 
Difference Between Search & Browse Methods in Odoo 17
Difference Between Search & Browse Methods in Odoo 17Difference Between Search & Browse Methods in Odoo 17
Difference Between Search & Browse Methods in Odoo 17Celine George
 
ENGLISH 7_Q4_LESSON 2_ Employing a Variety of Strategies for Effective Interp...
ENGLISH 7_Q4_LESSON 2_ Employing a Variety of Strategies for Effective Interp...ENGLISH 7_Q4_LESSON 2_ Employing a Variety of Strategies for Effective Interp...
ENGLISH 7_Q4_LESSON 2_ Employing a Variety of Strategies for Effective Interp...JhezDiaz1
 
ISYU TUNGKOL SA SEKSWLADIDA (ISSUE ABOUT SEXUALITY
ISYU TUNGKOL SA SEKSWLADIDA (ISSUE ABOUT SEXUALITYISYU TUNGKOL SA SEKSWLADIDA (ISSUE ABOUT SEXUALITY
ISYU TUNGKOL SA SEKSWLADIDA (ISSUE ABOUT SEXUALITYKayeClaireEstoconing
 
How to Add Barcode on PDF Report in Odoo 17
How to Add Barcode on PDF Report in Odoo 17How to Add Barcode on PDF Report in Odoo 17
How to Add Barcode on PDF Report in Odoo 17Celine George
 

Kürzlich hochgeladen (20)

Raw materials used in Herbal Cosmetics.pptx
Raw materials used in Herbal Cosmetics.pptxRaw materials used in Herbal Cosmetics.pptx
Raw materials used in Herbal Cosmetics.pptx
 
Full Stack Web Development Course for Beginners
Full Stack Web Development Course for BeginnersFull Stack Web Development Course for Beginners
Full Stack Web Development Course for Beginners
 
Daily Lesson Plan in Mathematics Quarter 4
Daily Lesson Plan in Mathematics Quarter 4Daily Lesson Plan in Mathematics Quarter 4
Daily Lesson Plan in Mathematics Quarter 4
 
HỌC TỐT TIẾNG ANH 11 THEO CHƯƠNG TRÌNH GLOBAL SUCCESS ĐÁP ÁN CHI TIẾT - CẢ NĂ...
HỌC TỐT TIẾNG ANH 11 THEO CHƯƠNG TRÌNH GLOBAL SUCCESS ĐÁP ÁN CHI TIẾT - CẢ NĂ...HỌC TỐT TIẾNG ANH 11 THEO CHƯƠNG TRÌNH GLOBAL SUCCESS ĐÁP ÁN CHI TIẾT - CẢ NĂ...
HỌC TỐT TIẾNG ANH 11 THEO CHƯƠNG TRÌNH GLOBAL SUCCESS ĐÁP ÁN CHI TIẾT - CẢ NĂ...
 
4.16.24 Poverty and Precarity--Desmond.pptx
4.16.24 Poverty and Precarity--Desmond.pptx4.16.24 Poverty and Precarity--Desmond.pptx
4.16.24 Poverty and Precarity--Desmond.pptx
 
4.16.24 21st Century Movements for Black Lives.pptx
4.16.24 21st Century Movements for Black Lives.pptx4.16.24 21st Century Movements for Black Lives.pptx
4.16.24 21st Century Movements for Black Lives.pptx
 
Concurrency Control in Database Management system
Concurrency Control in Database Management systemConcurrency Control in Database Management system
Concurrency Control in Database Management system
 
Active Learning Strategies (in short ALS).pdf
Active Learning Strategies (in short ALS).pdfActive Learning Strategies (in short ALS).pdf
Active Learning Strategies (in short ALS).pdf
 
ANG SEKTOR NG agrikultura.pptx QUARTER 4
ANG SEKTOR NG agrikultura.pptx QUARTER 4ANG SEKTOR NG agrikultura.pptx QUARTER 4
ANG SEKTOR NG agrikultura.pptx QUARTER 4
 
Keynote by Prof. Wurzer at Nordex about IP-design
Keynote by Prof. Wurzer at Nordex about IP-designKeynote by Prof. Wurzer at Nordex about IP-design
Keynote by Prof. Wurzer at Nordex about IP-design
 
Field Attribute Index Feature in Odoo 17
Field Attribute Index Feature in Odoo 17Field Attribute Index Feature in Odoo 17
Field Attribute Index Feature in Odoo 17
 
INTRODUCTION TO CATHOLIC CHRISTOLOGY.pptx
INTRODUCTION TO CATHOLIC CHRISTOLOGY.pptxINTRODUCTION TO CATHOLIC CHRISTOLOGY.pptx
INTRODUCTION TO CATHOLIC CHRISTOLOGY.pptx
 
How to do quick user assign in kanban in Odoo 17 ERP
How to do quick user assign in kanban in Odoo 17 ERPHow to do quick user assign in kanban in Odoo 17 ERP
How to do quick user assign in kanban in Odoo 17 ERP
 
Food processing presentation for bsc agriculture hons
Food processing presentation for bsc agriculture honsFood processing presentation for bsc agriculture hons
Food processing presentation for bsc agriculture hons
 
Difference Between Search & Browse Methods in Odoo 17
Difference Between Search & Browse Methods in Odoo 17Difference Between Search & Browse Methods in Odoo 17
Difference Between Search & Browse Methods in Odoo 17
 
ENGLISH 7_Q4_LESSON 2_ Employing a Variety of Strategies for Effective Interp...
ENGLISH 7_Q4_LESSON 2_ Employing a Variety of Strategies for Effective Interp...ENGLISH 7_Q4_LESSON 2_ Employing a Variety of Strategies for Effective Interp...
ENGLISH 7_Q4_LESSON 2_ Employing a Variety of Strategies for Effective Interp...
 
YOUVE GOT EMAIL_FINALS_EL_DORADO_2024.pptx
YOUVE GOT EMAIL_FINALS_EL_DORADO_2024.pptxYOUVE GOT EMAIL_FINALS_EL_DORADO_2024.pptx
YOUVE GOT EMAIL_FINALS_EL_DORADO_2024.pptx
 
FINALS_OF_LEFT_ON_C'N_EL_DORADO_2024.pptx
FINALS_OF_LEFT_ON_C'N_EL_DORADO_2024.pptxFINALS_OF_LEFT_ON_C'N_EL_DORADO_2024.pptx
FINALS_OF_LEFT_ON_C'N_EL_DORADO_2024.pptx
 
ISYU TUNGKOL SA SEKSWLADIDA (ISSUE ABOUT SEXUALITY
ISYU TUNGKOL SA SEKSWLADIDA (ISSUE ABOUT SEXUALITYISYU TUNGKOL SA SEKSWLADIDA (ISSUE ABOUT SEXUALITY
ISYU TUNGKOL SA SEKSWLADIDA (ISSUE ABOUT SEXUALITY
 
How to Add Barcode on PDF Report in Odoo 17
How to Add Barcode on PDF Report in Odoo 17How to Add Barcode on PDF Report in Odoo 17
How to Add Barcode on PDF Report in Odoo 17
 

LarKC Tutorial at ISWC 2009 - Architecture

  • 1. LarKC Architecture and Technology Michael Witbrock, Cycorp Europe (+UIBK) with contributions from all LarKC developers
  • 2. Realising the Architecture Workflow Support System Plug-in Registry Data Layer Plug-in API Data Layer API RDF Store Plug-in Manager
  • 3.
  • 4.
  • 5.
  • 6.
  • 7.
  • 8.
  • 9.
  • 10.
  • 11.
  • 12. LarKC Plug-in API LarKC Architecture Data Layer API Pipeline Support System Plug-in Registry RDF Store RDF Store RDF Store RDF Doc RDF Doc RDF Doc Data Layer Decider Plug-in API Plug-in Manager Query Transformer Plug-in API Plug-in Manager Identifier Plug-in API Plug-in Manager Info. Set Transformer Plug-in API Plug-in Manager Selecter Plug-in API Plug-in Manager Reasoner Plug-in API Application Platform Utility Functionality APIs Plug-ins External systems External data sources Plug-in API Plug-in API Plug-in API Plug-in API Plug-in API Plug-in API
  • 13. What does a workflow look like? Decider Plug-in API Plug-in Manager Query Transformer Plug-in API Plug-in Manager Identifier Plug-in API Plug-in Manager Info. Set Transformer Plug-in API Plug-in Manager Selecter Plug-in API Plug-in Manager Reasoner Plug-in API Plug-in Registry Workflow Support System RDF Store Identifier Info Set Transformer Reasoner Decider Selecter Query Transformer
  • 14. What Does a Workflow Look Like? Decider Plug-in API Plug-in Manager Query Transformer Plug-in API Plug-in Manager Identifier Plug-in API Plug-in Manager Info. Set Transformer Plug-in API Plug-in Manager Selecter Plug-in API Plug-in Manager Reasoner Plug-in API Plug-in Registry Workflow Support System RDF Store Identifier Info Set Transformer Reasoner Decider Selecter Query Transformer Data Layer Data Layer Data Layer Data Layer RDF Graph RDF Graph RDF Graph RDF Graph RDF Graph RDF Graph Default Graph RDF Graph RDF Graph RDF Graph RDF Graph RDF Graph RDF Graph RDF Graph
  • 15. LarKC Data Model :Transport By Reference RDF Graph Dataset: Collection of named graphs Labeled Set: Pointers to data Current Scale: O(10 10 ) triples RDF Graph RDF Graph RDF Graph RDF Graph RDF Graph Default Graph RDF Graph RDF Graph RDF Graph RDF Graph RDF Graph RDF Graph RDF Graph
  • 16. What Does a Workflow Look Like? Decider Plug-in API Plug-in Manager Query Transformer Plug-in API Plug-in Manager Identifier Plug-in API Plug-in Manager Info. Set Transformer Plug-in API Plug-in Manager Selecter Plug-in API Plug-in Manager Reasoner Plug-in API Plug-in Registry Workflow Support System RDF Store Identifier Info Set Transformer Reasoner Decider Selecter Query Transformer Data Layer Data Layer Data Layer Data Layer RDF Graph RDF Graph RDF Graph RDF Graph RDF Graph RDF Graph Default Graph RDF Graph RDF Graph RDF Graph RDF Graph RDF Graph RDF Graph RDF Graph
  • 17. What Does a Pipeline Look Like? Info Set Transformer Identifier Identifier Decider Plug-in API Plug-in Manager Query Transformer Plug-in API Plug-in Manager Identifier Plug-in API Plug-in Manager Info. Set Transformer Plug-in API Plug-in Manager Selecter Plug-in API Plug-in Manager Reasoner Plug-in API Plug-in Registry Wlorkflow Support System RDF Store Identifier Info Set Transformer Reasoner Decider Selecter Query Transformer Data Layer Data Layer Data Layer Data Layer
  • 18. Remote and Heterogeneous Plug-ins Remote Plug-in Manager Adaptor External or non-Java Code TRANSFORM SPARQL-CycL Research Cyc TRANSFORM SPARQL- GATE API GATE IDENTIFY SPARQL SINDICE IDENTIFY SPARQL Medical Data Data Layer
  • 19. What Does a Workflow Look Like? Info Set Transformer Identifier Identifier Info Set Transformer Reasoner Decider Plug-in API Plug-in Manager Query Transformer Plug-in API Plug-in Manager Identifier Plug-in API Plug-in Manager Info. Set Transformer Plug-in API Plug-in Manager Selecter Plug-in API Plug-in Manager Reasoner Plug-in API Plug-in Registry Workflow Support System RDF Store Identifier Info Set Transformer Reasoner Decider Selecter Query Transformer Data Layer Data Layer Data Layer Data Layer
  • 20.
  • 21.
  • 22. LarKC Data Layer Data Layer API Data Layer Data Layer API Pipeline Support System Plug-in Registry RDF Store RDF Store RDF Store RDF Doc RDF Doc RDF Doc Data Layer Decider Plug-in API Plug-in Manager Query Transformer Plug-in API Plug-in Manager Identifier Plug-in API Plug-in Manager Info. Set Transformer Plug-in API Plug-in Manager Selecter Plug-in API Plug-in Manager Reasoner Plug-in API Application Platform Utility Functionality APIs Plug-ins External systems External data sources
  • 23.
  • 24.
  • 25.
  • 26.
  • 27.
  • 28. Project Timeline 14 Surveys (plug-ins, platform) & Requirements (use cases) Prototype Internal Release Public Release Final Release 42 0 6 18 33 10 Plug-ins Use Cases V1 Use Cases V2 Use Cases V3 Data caching Offer computing resources Anytime behaviour Monitoring & instrumentation
  • 29.
  • 30.
  • 31. fin