Parse has one of the world's largest and most complicated MongoDB deployments, with millions of collections, tens of millions of indexes, and hundreds of thousands of different workload types. In this talk we'll cover our experiences evaluating all three major storage engines — mmapv1, WiredTiger, and RocksDB, sharing benchmarks and compression rates and and fun anecdotes from all three. Igor Canadi will do a deeper dive into RocksDB — what is RocksDB, what is LSM storage, and what are a few of the similarities and differences between RocksDB and WiredTiger. We will then talk about why we are pursuing RocksDB as our primary workload storage engine moving forward, and share some thoughts about the future of MongoDB storage engine innovation.
Slides for talk given at IWMW 1998 held at the University of Newcastle on 15-17 September 1998.
See http://www.ukoln.ac.uk/web-focus/events/workshops/webmaster-sep1998/materials/
RocksDB storage engine for MySQL and MongoDBIgor Canadi
My talk from Percona Live Europe 2015. Presenting RocksDB storage engine for MySQL and MongoDB. The talk covers RocksDB story, its internals and gives some hints on performance tuning.
Fractal Tree Indexes : From Theory to PracticeTim Callaghan
Fractal Tree Indexes are compared to the indexing incumbent, B-trees. The capabilities are then shown what they bring to MySQL (in TokuDB) and MongoDB (in TokuMX).
Presented at Percona Live London 2013.
The Hive Think Tank: Rocking the Database World with RocksDBThe Hive
Dhruba Borthakur, Facebook
Dhruba Borthakur is an engineer at Facebook. He has been one of the founding engineer of RocksDB, an open-source key-value store optimized for storing data in flash and main-memory storage. He has been one of the founding architects of the Apache Hadoop Distributed File System and has been instrumental in scaling Facebook's Hadoop cluster to multiples of petabytes. Dhruba has contributed code to the Apache HBase project. Earlier, he contributed to the development of the Andrew File System (AFS). He has an M.S. in Computer Science from the University of Wisconsin, Madison and a B.S. in Computer Science BITS, Pilani, India.
Parse has one of the world's largest and most complicated MongoDB deployments, with millions of collections, tens of millions of indexes, and hundreds of thousands of different workload types. In this talk we'll cover our experiences evaluating all three major storage engines — mmapv1, WiredTiger, and RocksDB, sharing benchmarks and compression rates and and fun anecdotes from all three. Igor Canadi will do a deeper dive into RocksDB — what is RocksDB, what is LSM storage, and what are a few of the similarities and differences between RocksDB and WiredTiger. We will then talk about why we are pursuing RocksDB as our primary workload storage engine moving forward, and share some thoughts about the future of MongoDB storage engine innovation.
Slides for talk given at IWMW 1998 held at the University of Newcastle on 15-17 September 1998.
See http://www.ukoln.ac.uk/web-focus/events/workshops/webmaster-sep1998/materials/
RocksDB storage engine for MySQL and MongoDBIgor Canadi
My talk from Percona Live Europe 2015. Presenting RocksDB storage engine for MySQL and MongoDB. The talk covers RocksDB story, its internals and gives some hints on performance tuning.
Fractal Tree Indexes : From Theory to PracticeTim Callaghan
Fractal Tree Indexes are compared to the indexing incumbent, B-trees. The capabilities are then shown what they bring to MySQL (in TokuDB) and MongoDB (in TokuMX).
Presented at Percona Live London 2013.
The Hive Think Tank: Rocking the Database World with RocksDBThe Hive
Dhruba Borthakur, Facebook
Dhruba Borthakur is an engineer at Facebook. He has been one of the founding engineer of RocksDB, an open-source key-value store optimized for storing data in flash and main-memory storage. He has been one of the founding architects of the Apache Hadoop Distributed File System and has been instrumental in scaling Facebook's Hadoop cluster to multiples of petabytes. Dhruba has contributed code to the Apache HBase project. Earlier, he contributed to the development of the Andrew File System (AFS). He has an M.S. in Computer Science from the University of Wisconsin, Madison and a B.S. in Computer Science BITS, Pilani, India.
Artículo de José Luis Ares, Profesor Adjunto de Derecho Procesal Penal en la carrera de Abogacía de la Univ. Nacional del Sur, docente Tutor de la Especialización en Derecho Penal de la UNS, y Juez Correccional del Depto. Judicial de Bahía Blanca
Apache Jackrabbit Oak is a new JCR implementation with a completely new architecture. Based on concepts like eventual consistency and multi-version concurrency control, and borrowing ideas from distributed version control systems and cloud-scale databases, the Oak architecture is a major leap ahead for Jackrabbit. This presentation describes the Oak architecture and shows what it means for the scalability and performance of modern content applications. Changes to existing Jackrabbit functionality are described and the migration process is explained.
LOD2 plenary meeting in Paris: presentation of WP5: State of Play: Linked Data Visualization, Browsing and Authoring, by Renaud Delbru (National University of Ireland, Galway).
(http://lod2.eu/BlogPost/webinar-series) In this Webinar Michael Martin presents CubeViz - a facetted browser for statistical data utilizing the RDF Data Cube vocabulary which is the state-of-the-art in representing statistical data in RDF. This vocabulary is compatible with SDMX and increasingly being adopted. Based on the vocabulary and the encoded Data Cube, CubeViz is generating a facetted browsing widget that can be used to filter interactively observations to be visualized in charts. Based on the selected structure, CubeViz offer beneficiary chart types and options which can be selected by users.
If you are interested in Linked (Open) Data principles and mechanisms, LOD tools & services and concrete use cases that can be realised using LOD then join us in the free LOD2 webinar series!
http://lod2.eu/BlogPost/webinar-series
This webinar in the course of the LOD2 webinar series will present the release 3.0 of the LOD2 stack, which contains updates to
*) Virtuoso 7 [Openlink]: the original row store of the Virtuoso 6 universal server has now been replaced by a column store, increasing the performance of SPARQL queries significantly, the store is now up to three times as fast as the previous major version.
Linked Open Data Manager Suite [SWC]: the 'lodms' application allows the user to quickly set up pipelines for transforming linked data through the use of its many extensions. It also allows operations for extracting rdf from other types of data.
*) dbpedia-spotlight-ui [ULEI]: a graphical user interface component that allows the user to use a remote DBpedia spotlight instance to annotate a text with DBpedia concepts.
*) sparqlify [ULEI]: a scalable SPARQL-SQL rewriter, allowing you to query an SQL database as if it were a triple store.
*) SIREn [DERI]: a Lucene plugin that allows you to efficiently index and query RDF, as well as any textual document with an arbitrary amount of metadata fields.
*) CubeViz [ULEI]: CubeViz allows visualization of the Data Cube linked data representation of statistical data. It has support for the more advanced DataCube features, such as slices. It also allows the selection of a remote SPARQL endpoint and export of a modified cube.
*) R2R [UMA]: the R2R mapping API is now included directly into the lod2 demonstrator application, allowing users to experience the full effect of the R2R semantic mapping language through a graphical user interface.
*) ontowiki-csvimport [ULEI]: an OntoWiki extension that transforms CSV files to RDF. The extension can create Data Cubes that can be visualized by CubeViz.
If you are interested in Linked (Open) Data principles and mechanisms, LOD tools & services and concrete use cases that can be realised using LOD then join us in the free LOD2 webinar series!
Solr 4.0 dramatically improves scalability, performance, and flexibility. An overhauled Lucene underneath sports near real-time (NRT) capabilities allowing indexed documents to be rapidly visible and searchable. Lucene’s improvements also include pluggable scoring, much faster fuzzy and wildcard querying, and vastly improved memory usage. These Lucene improvements automatically make Solr much better, and Solr magnifies these advances with “SolrCloud.” SolrCloud enables highly available and fault tolerant clusters for large scale distributed indexing and searching. There are many other changes that will be surveyed as well. This talk will cover these improvements in detail, comparing and contrasting to previous versions of Solr.
This presentation presents OpenLink Virtuoso -- The Prometheus of RDF -- including Linked Data Verticals and Patterns, involving Web and Big Data, SPARQL and RDF, RDF Tax and many others.
Artículo de José Luis Ares, Profesor Adjunto de Derecho Procesal Penal en la carrera de Abogacía de la Univ. Nacional del Sur, docente Tutor de la Especialización en Derecho Penal de la UNS, y Juez Correccional del Depto. Judicial de Bahía Blanca
Apache Jackrabbit Oak is a new JCR implementation with a completely new architecture. Based on concepts like eventual consistency and multi-version concurrency control, and borrowing ideas from distributed version control systems and cloud-scale databases, the Oak architecture is a major leap ahead for Jackrabbit. This presentation describes the Oak architecture and shows what it means for the scalability and performance of modern content applications. Changes to existing Jackrabbit functionality are described and the migration process is explained.
LOD2 plenary meeting in Paris: presentation of WP5: State of Play: Linked Data Visualization, Browsing and Authoring, by Renaud Delbru (National University of Ireland, Galway).
(http://lod2.eu/BlogPost/webinar-series) In this Webinar Michael Martin presents CubeViz - a facetted browser for statistical data utilizing the RDF Data Cube vocabulary which is the state-of-the-art in representing statistical data in RDF. This vocabulary is compatible with SDMX and increasingly being adopted. Based on the vocabulary and the encoded Data Cube, CubeViz is generating a facetted browsing widget that can be used to filter interactively observations to be visualized in charts. Based on the selected structure, CubeViz offer beneficiary chart types and options which can be selected by users.
If you are interested in Linked (Open) Data principles and mechanisms, LOD tools & services and concrete use cases that can be realised using LOD then join us in the free LOD2 webinar series!
http://lod2.eu/BlogPost/webinar-series
This webinar in the course of the LOD2 webinar series will present the release 3.0 of the LOD2 stack, which contains updates to
*) Virtuoso 7 [Openlink]: the original row store of the Virtuoso 6 universal server has now been replaced by a column store, increasing the performance of SPARQL queries significantly, the store is now up to three times as fast as the previous major version.
Linked Open Data Manager Suite [SWC]: the 'lodms' application allows the user to quickly set up pipelines for transforming linked data through the use of its many extensions. It also allows operations for extracting rdf from other types of data.
*) dbpedia-spotlight-ui [ULEI]: a graphical user interface component that allows the user to use a remote DBpedia spotlight instance to annotate a text with DBpedia concepts.
*) sparqlify [ULEI]: a scalable SPARQL-SQL rewriter, allowing you to query an SQL database as if it were a triple store.
*) SIREn [DERI]: a Lucene plugin that allows you to efficiently index and query RDF, as well as any textual document with an arbitrary amount of metadata fields.
*) CubeViz [ULEI]: CubeViz allows visualization of the Data Cube linked data representation of statistical data. It has support for the more advanced DataCube features, such as slices. It also allows the selection of a remote SPARQL endpoint and export of a modified cube.
*) R2R [UMA]: the R2R mapping API is now included directly into the lod2 demonstrator application, allowing users to experience the full effect of the R2R semantic mapping language through a graphical user interface.
*) ontowiki-csvimport [ULEI]: an OntoWiki extension that transforms CSV files to RDF. The extension can create Data Cubes that can be visualized by CubeViz.
If you are interested in Linked (Open) Data principles and mechanisms, LOD tools & services and concrete use cases that can be realised using LOD then join us in the free LOD2 webinar series!
Solr 4.0 dramatically improves scalability, performance, and flexibility. An overhauled Lucene underneath sports near real-time (NRT) capabilities allowing indexed documents to be rapidly visible and searchable. Lucene’s improvements also include pluggable scoring, much faster fuzzy and wildcard querying, and vastly improved memory usage. These Lucene improvements automatically make Solr much better, and Solr magnifies these advances with “SolrCloud.” SolrCloud enables highly available and fault tolerant clusters for large scale distributed indexing and searching. There are many other changes that will be surveyed as well. This talk will cover these improvements in detail, comparing and contrasting to previous versions of Solr.
This presentation presents OpenLink Virtuoso -- The Prometheus of RDF -- including Linked Data Verticals and Patterns, involving Web and Big Data, SPARQL and RDF, RDF Tax and many others.
LOD2 plenary meeting in Paris: presentation of WP2: State of Play (Storing and Querying Very Large Knowledge Bases) by Peter Boncz (CWI) and Orri Erling (OpenLink Software)
Linked Data Publishing with Drupal (SWIB13 workshop)Joachim Neubert
Publishing Linked Open Data in a user-appealing way is still a challenge: Generic solutions to convert arbitrary RDF structures to HTML out-of-the-box are available, but leave users perplexed. Custom-built web applications to enrich web pages with semantic tags "under the hood" require high efforts in programming. Given this dilemma, content management systems (CMS) could be a natural enhancement point for data on the web. In the case of Drupal, one of the most popular CMS nowadays, Semantic Web enrichment is provided as part of the CMS core. In a simple declarative approach, classes and properties from arbitrary vocabularies can be added to Drupal content types and fields, and are turned into Linked Data on the web pages automagically. The embedded RDFa marked-up data can be easily extracted by other applications. This makes the pages part of the emerging Web of Data, and in the same course helps discoverability with the major search engines.
In the workshop, you will learn how to make use of the built-in Drupal 7 features to produce RDFa enriched pages. You will build new content types, add custom fields and enhance them with RDF markup from mixed vocabularies. The gory details of providing LOD-compatible "cool" URIs will not be skipped, and current limitations of RDF support in Drupal will be explained. Exposing the data in a REST-ful application programming interface or as a SPARQL endpoint are additional options provided by Drupal modules. The workshop will also introduce modules such as Web Taxonomy, which allows linking to thesauri or authority files on the web via simple JSON-based autocomplete lookup. Finally, we will touch the upcoming Drupal 8 version. (Workshop announcement)
Latest (storage IO) patterns for cloud-native applications OpenEBS
Applying micro service patterns to storage giving each workload its own Container Attached Storage (CAS) system. This puts the DevOps persona within full control of the storage requirements and brings data agility to k8s persistent workloads. We will go over the concept and the implementation of CAS, as well as its orchestration.
Building Hopsworks, a cloud-native managed feature store for machine learning Jim Dowling
Cloud Native London talk about the control layer of Hopsworks.ai and our choice of cloud native services. We built our own multi-tenant services as cloud native services, for the most part.
Database as a Service on the Oracle Database Appliance PlatformMaris Elsins
Speaker: Marc Fielding, Co-speaker: Maris Elsins.
Oracle Database Appliance provides a robust, highly-available, cost-effective, and surprisingly scalable platform for database as a service environment. By leveraging Oracle Enterprise Manager's self-service features, databases can be provisioned on a self-service basis to a cluster of Oracle Database Appliance machines. Discover how multiple ODA devices can be managed together to provide both high availability and incremental, cost-effective scalability. Hear real-world lessons learned from successful database consolidation implementations.
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UnifiedViews is a joint project currently maintained by Semantic Web Company (SWC) and Semantica.cz (Semantica.cz). It has been mainly developed by Charles University in Prague as a student project called ODCleanStore (version 2). It is based on the experience SWC obtained with the LOD Management Suite (LODMS) used in WP7 and ODCleansStore (version 1) developed by Charles University in Prague for the WP9a use case of the LOD2 FP7 project. In the next stack release of the LOD2 stack, UnifiedViews will replace LODMS as an ETL tool in the stack and the tool has already been adopted in other projects.
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In this Webinar Lorenz Bühmann presents the ontology repair and enrichment tool ORE and also the DL-Learner , a machine learning tool to solve supervised learnings tasks and support knowledge engineers in constructing knowledge. Those two beneighbored tools in the LOD2 Stack are for classification and the following quality analysis of Linked Data.
This webinar in the course of the LOD2 webinar series will present Virtuoso 7. Virtuoso Column Store, Adaptive Techniques for RDF Graph Databases. In this webinar we shall discuss the application of column store techniques to both graph (RDF) and relational data for mixed work-loads ranging from lookup to analytics.
Virtuoso is an innovative enterprise grade multi-model data server for agile enterprises & individuals. It delivers an unrivaled platform agnostic solution for data management, access, and integration. The unique hybrid server architecture of Virtuoso enables it to offer traditionally distinct server functionality within a single product
If you are interested in Linked (Open) Data principles and mechanisms, LOD tools & services and concrete use cases that can be realised using LOD then join us in the free LOD2 webinar series!
http://lod2.eu/BlogPost/webinar-series
DBpedia Spotlight is a tool employed in the Extraction stage of the LOD Lyfe Cycle, performing Entity Recognition and Linking. Although the tool currently specializes in English language, the support for other languages is currently being tested, and demos for German, Dutch and others are available or underway. The tool can be used to enable faceted browsing, semantic search, among other applications. In this webinar we will describe what is DBpedia Spotlight, how it works and how can you benefit from it in your application.
If you are interested in Linked (Open) Data principles and mechanisms, LOD tools & services and concrete use cases that can be realised using LOD then join us in the free LOD2 webinar series!
http://lod2.eu/BlogPost/webinar-series
PublicData.eu is striving to become the Pan European one-stop-shop, providing access to open, freely reusable datasets from numerous local, regional and national public bodies across Europe.
After the first release of the PublicData.eu website (Alpha release was Jan 2011 & Beta release was June 2011) and it's subsequent upgrades (a significant upgrade was efected March 2012), OKFN worked towards the deployment of various personalization features, meant to improve the user experience on Publicdata.eu and spur more interest and interaction around the official data-sets.
This webinar in the course of the LOD2 webinar series will present Zemanta and its LODRefine - a LOD-enabled version of OpenRefine (previously Google Refine), which is a part of the LOD2 stack. LODRefine extends cleansing and linking functionalities of OpenRefine by providing means to reconcile and augment your data with DBpedia or any other SPARQL endpoint, extract named entities using Zemanta API, export data in one of the RDF formats, and recently also to exploit available crowdsourcing services. In webinar we will demonstrate several task which demonstrate the ease of use and versatility of LODRefine.
If you are interested in Linked (Open) Data principles and mechanisms, LOD tools & services and concrete use cases that can be realised using LOD then join us in the free LOD2 webinar series: http://lod2.eu/BlogPost/webinar-series
This webinar in the course of the LOD2 webinar series will present the implications of Linked Open Data and Semantic Web Technologies in the information and publishing industry.
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This series will provide a monthly webinar about Linked (Open) Data tools and services around the LOD2 project, the LOD2 Stack and the Linked Open Data Life Cycle, also in the form of 3rd party tools. Please find continuously updated information here: http://lod2.eu/BlogPost/webinar-series
This webinar in the course of the LOD2 webinar series will present use cases and live demos of PoolParty (by Semantic Web Company).
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If you are interested in Linked (Open) Data principles and mechanisms, LOD tools & services and concrete use cases that can be realised using LOD then join us in the LOD2 webinar series!
http://lod2.eu/BlogPost/webinar-series
This webinar in the course of the LOD2 webinar series will present use cases and live demos of D2R (Free University Berlin) and Sparqlify (University of Leipzig).
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Sparqlify is a tool enabling one to define expressive RDF views on relational databases and query them with a subset of the SPARQL query language. By featuring a novel RDF view definition syntax, it aims at simplifying the RDB-RDF mapping process.
more to be found at:
Born from the wish to make linking tractable, the Link Discovery Framework for Metric Spaces (LIMES) is tailored towards the time-efficient and lossless discovery of links across knowledge bases. LIMES is an extensible declarative framework that encapsulates manifold algorithms dedicated to the processing of structured data of any sort. Built with extensibility and easy integration in mind, LIMES allows implementing applications that integrate, consume and/or generate Linked Data. Within LOD2, it will be used for discovering links between knowledge bases.
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Under Augustus, the empire experienced the Pax Romana, a 200-year period of relative peace and stability. Augustus reformed the military, established efficient administrative systems, and initiated grand construction projects. The empire's borders expanded, encompassing territories from Britain to Egypt and from Spain to the Euphrates. Roman legions, renowned for their discipline and engineering prowess, secured and maintained these vast territories, building roads, fortifications, and cities that facilitated control and integration.
The Roman Empire’s society was hierarchical, with a rigid class system. At the top were the patricians, wealthy elites who held significant political power. Below them were the plebeians, free citizens with limited political influence, and the vast numbers of slaves who formed the backbone of the economy. The family unit was central, governed by the paterfamilias, the male head who held absolute authority.
Culturally, the Romans were eclectic, absorbing and adapting elements from the civilizations they encountered, particularly the Greeks. Roman art, literature, and philosophy reflected this synthesis, creating a rich cultural tapestry. Latin, the Roman language, became the lingua franca of the Western world, influencing numerous modern languages.
Roman architecture and engineering achievements were monumental. They perfected the arch, vault, and dome, constructing enduring structures like the Colosseum, Pantheon, and aqueducts. These engineering marvels not only showcased Roman ingenuity but also served practical purposes, from public entertainment to water supply.
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This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
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• The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act.
• The Committee on Oversight and Accountability is investigating the sources of funding and other support flowing to groups espousing pro-Hamas propaganda and engaged in antisemitic harassment and intimidation of students. The Committee on Oversight and Accountability is the principal oversight committee of the US House of Representatives and has broad authority to investigate “any matter” at “any time” under House Rule X.
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Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
LOD2 Plenary Vienna 2012: WP2 - Storing and Querying Very Large Knowledge Bases
1. SIB . 23.03.2011 . Page 1 http://lod2.eu
WP2
Storing and Querying
Very Large Knowledge Bases
Vienna Update
March 2012 – M18
Peter Boncz
http://lod2.eu
2. SIB . 23.03.2011 . Page 2 http://lod2.eu
Table of Contents
• WP2 Refresher
• LOD Cloud Hosted on the Knowledge Store Cluster
* 50B mark reached, column-store Virtuoso deployed
• State of the Art LOD Laboratory (“Benchmarking”)
* LDBC – RDF Store Industry council
* BSBM at large scale
* RDF-H + Social Intelligence Benchmark (SIB)
• Technical work
* column-store Virtuoso cluster version
* recycling query results
• Next up
* LOD cloud @250B triples
* Virtuoso: adaptive query optimizer (and more)
* first MonetDB/SPARQL version (RDF clustering, graph indexing)
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WP2 Organization
CWI (MonetDB):
• Peter Boncz (also in VUA group of Frank v Harmelen)
• Duc Pham Minh (Phd student)
• Irini Fundulaki (1-year sabbatical from FORTH)
OpenLink (Virtuoso):
• Orri Erling
• Hugh Williams
• Ivan Mikhailov
+ FU Berlin (BSBM)
+ DERI (BSBM text+ LOD cloud + text retrieval/sindice)
+ ULEI (DBpedia benchmark)
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WP2
Storing and Querying Very Large Knowledge Bases
Goal: enabling large-scale, feature-rich & enterprise-ready Linked
Data management solutions
Database Partners in LOD2:
CWI: Leading open source analytics RDBMS
OpenLink: Leading Linked data deployment platform
Technological Excellence:
Creating and publishing metrics for choosing RDF solutions
Bringing Column Store Technology for Business Intelligence on RDF
Ground-breaking database innovations for RDF stores
(Dynamic Query optimization, Adaptive Caching of Joins,
Optimized Graph Processing, Cluster/Cloud scalability)
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Task 2.1: State of the Art, Evaluation & Benchmarking
LOD cloud cache scalability
• M0: 20B triples
• M12: 50B triples
• M24: 250B triples
• M36: 1T triples
D2.4 completed: 50B triples in LOD cache @ DERI
First deployment of Virtuoso7 Cluster
• Currently hosting about 55 billion triples
• 8 node Virtuoso v7 (column store) Cluster
• 384GB RAM
• 2TB Disk Storage
• 14B/quads, excl literals
Next up:
• hardware provisioning for 250B and 1T triples
(need 512GB RAM resp. 2TB RAM somewhere)
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Task 2.1: State of the Art, Evaluation & Benchmarking
Benchmarking
• creating new benchmarks
• BSBM-BI (FU Berlin)
• DBpedia Benchmark (ULEI) – best paper award
• RDF-H (OGL,CWI)
• Social Intelligence Benchmark (OGL,CWI)
• running benchmark evaluations
• BSBM on a large cluster cluster (Lisa @ SARA)
• BSBM on large single-server (40cores, 1TB RAM)
• creating industry consensus
• Benchmark Auditing Service
• LOD Benchmark Council
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BSBM Large Scale Experiments (still ongoing..)
New Aspects:
• The Business Intelligence Use Case (BI)
• Benchmark Rules
• BSBM V3 Results
• trying cluster versions
SARA LISA cluster
• experiments with up to 64 nodes
VectorWise high-end server
• 40-core machine with 1TB RAM
Benchmarked at SARA and Vectorwise
4store 1.1.2 Garlik http://4store.org/
BigData r4169 SYSTAP LLC http://www.systap.com/bigdata.htm
BigOwlim 3.4.3129 OntoText http://www.ontotext.com/owlim/
Jena TDB 0.8.9 openjena.org http://www.openjena.org/TDB/
Fuseki 0.1.0 openjena.org http://openjena.org/wiki/Fuseki
Virtuoso 7.0 OpenLink http://virtuoso.openlinksw.com/
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Social Intelligence Benchmark
14 dictionaries
of real data
Facebook schema style
Realistic scenario
simulation
Synthetic Generated Data Linked Open Data
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Technical Work: Recycling (D2.4)
Dynamic caching of intermediate query results
• SPARQL problem: hard to index workload / expensive backward chaining
Idea: compute once, re-use many times
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Technical Work: Virtuoso 7
Major now upcoming release V7, due for release in 2012
• column store technology:
• aggressive compression more data fits in RAM
• vectored execution things run faster
• elastic cluster implementation
• partitions can migrate across nodes
• bringing computation to the data
• arbitrary recursive functions in the cluster
• geospatial support
• full openGIS support, R-tree backed, EWKT format
• future enhancements
• adaptive query optimization (CWI ROX)
•re-use of intermediates (CWI recycling)
• using SSDs as cache
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Next 6 months
Virtuoso: sampled query optimizer
• query optimization in SPARQL is difficult (no stats)
• use adaptive, run-time, query optimization with sampling
MonetDB and SPARQL
• First version in sight (cooperation with FORTH)
• research tracks
• RDF clustering on Characteristic Sets
• correlated join path indexing
LOD cache at 250B triples
• what triples to use?
• what hardware to use? (need 512GB RAM)
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Contact
Address
Centrum Wiskunde Informatica (CWI)
Science Park 123
1098 XG Amsterdam
The Netherlands
monetdb.cwi.nl
Thanks for your attention!
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LOD2 Benchmark Auditing Service
Benchmarking needs of SPARQL engine vendors:
• vendors want to publish in their own timescale
• using new or upcoming releases (not yet public)
• using properly tuned settings and hardware to their solution
• yet need credibility (is it fair)
Tournaments organized by one institution have
• bad timing, wrong version, one more bug to fix, etc
• not the right hardware or settings
• may become a legal liability once matters become more serious
LOD2 should reach out to the SPARQL technical community and
provide independent benchmark auditing services
• start with BSBM working on Auditing Rules Document
• maybe other benchmarks later
Editor's Notes
From the aforementioned reasons, we proposed an RDF and graph database benchmark, called Social Intelligence benchmark, that can exploit the advantages of RDF in graph representation. We are aiming at testing the graph database performance on a highly connected graph. As social network is a high profile for graph data management, we design our benchmark over the scenarios of a social network. We try to generate data as realistic as possible with correlations and offer challenging queries over the data correlations.Besides, since a very large amount of useful information is available in many linked-open datasets, we exploit these resources by linking to them.
Now, I will describe the data specification of SIB. As Facebook is the most popular social network with more than 800 millions active users, we take the schema style of Facebook as the baseline for designing SIB. For generating realistic data, we use 14 dictionaries that we build from real data. These dictionaries cover various domains, for example, geographical information, personal names,..SIB data is designed so that it can simulate realistic scenario including the real behaviors of the users and the characteristics of data distributions in social networks.As we mention before, our synthetic data is linked with well-known linked open data. And here, SIB is linked with DBPedia, one of the largest linked open dataset.
I think most of us know FB and even have a Facebook account. The logical schema of our benchmark simulates the Facebook schema in which a user can have many friends, and there are friendships between them. A user can provide many profile information such as his name, where he is studying at, where he is living at. He can also specify his current status, for example, in Relation ship with another user. The user can upload many photo, start a discussion by writing posts, and get a lot of comments from his friends.