stardog 1.1: easier, smarter, faster rdf database
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stardog.com
Stardog 1.1An Easier, Smarter,
Faster RDF DatabaseMichael Grove, Clark & Parsia LLC
mike@clarkparsia.com@mikegrovesoft, @stardog_db, @candp
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About C&P
•We build semantic technology tools for enterprise solutions
•Proud bootstrappers since 2005
•Offices in DC and Cambridge, MA
•Government & enterprise customers
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What is Stardog?
•a pure Java RDF database
• full-service, feature rich
• focus on query performance
•standards compliant
•scalable (up first, out next)
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History•Development started summer 2010
•Stardog 0.5 alpha - 2 May 2011
•Stardog 1.0 final - 19 June 2012
•Total of 32 releases, ~500 tickets, 100s of email on the mailing list
•Stardog 1.0.7 presently
•Stardog 1.1 real soon now...
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What is easy?
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•What’s “easy” in an RDF database?
•Configuration
•Maintenance
•User Experience
• i.e., rationally predictable
•Easier for whom? Not a simple question.
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Configuration• Convention, not configuration
• “Quick Start” is shortest page in the docs
• 4 steps to querying
• Predictable, sane defaults throughout
• Adapted to Java, Unix, Semtech cultures
• Culture is key to convention
• Very good (!) documentation
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Maintenance•Nothing is easier than doing nothing
•RDF & OWL are ideally schema flexible
• Job scheduler: search, indexes, etc.
•Data migration tools since < 1.0
•Multi-tenancy, online & offline DBs
• Just add data...Automatic data quality*
•NoSQL == Anti-jobs program for DBAs
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Except that...•Every DB has to be admin’d &
maintained
•Matter of degree, not kind
•Stardog Enterprise Server Management
• audit logging
• JMX monitoring
•web console
•online backups (coming soon!)
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User Experience•Client-server & Embeddable
• Jena, Sesame, SNARL, HTTP
•SPARQL query simplifications
•ACID transactions
• Idiomatic Java & Unix interfaces
•Great CLI & shell…
•Windows has gotten much better! :>
•Rich security model10
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Okay...that’s BS.
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•“Smarter” is market speak
•But Stardog 1.1 has rich feature set
•Reasoning, including UDR
•Integrity Constraint Validation (ICV)
•Semantic Search
•Security
•Spring
•Linked Data Platform
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Reasoning•OWL 2 DL, QL, EL, and RL
•Query-time, no materialization
•Only pay for what you eat
•Embarrassingly parallel in part
•Pellet 3 embedded for OWL 2 DL schema reasoning only
•Very flexible re: NGs & schemas
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User-defined Rules• New in 1.1!
• Using SWRL syntax
• Including all SWRL builtins
• Which are also available to SPARQL
• Recently added new individual builtin
• Create new individuals in your rules
• Beware of non-termination!
• Executed at query time like everything else
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ICV?• Integrity Constraint Validation
•Automated data quality
•Closed world semantics
•Transactional
•High-level & declarative
• ICs can be OWL, SWRL, or SPARQL
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Example...Only employees who are US citizens can work on projects that receive funding from a US government agency.
Class: Project and (receivesFundsFrom some USGovAgency)SubClassOf: inverse(worksOn) only (Employee and nationality value "US")
More examples: http://stardog.com/docs/
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Semantic Search•Uses Waldo, our deep adaptation of
Lucene
•Text index from RDF literals
•Search for resources or literals
• Integrated with SPARQL query evaluation
•Auto-managed search indexes
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Security
•Rich security model
•Based on standard RBAC model
•Applies at database-level
•Will extend to Named Graphs in 1.x
•Easy CLI admin tools (& Java API)
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Spring•Love it or not, Spring isn’t going away
•Support Batch, Data Import, etc.
•Open Source: http://github.com/clark-parsia/spring-stardog
•Developed by an early adopter who needed it; supported/maintained by C&P
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Linked Data•Stardog fills a hole in our Linked
Data Platform
•HTML5, pure JS, client side web framework (based on backbone.js)
•Linked Data publishing suite
•Stardog Linked Data Catalog...Enterprise Linked Data management app
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Finally...
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•Now we can talk about something that’s objective, context-free, and measurable
•Yes!
•But no…#include <std_disclaim.h>
•Your data & your queries are the only things that really matter
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That said...•Two de facto benchmarks for
SPARQL:
•BSBM, OLTP-style, query mixes per hour (QMpH · 25)
•SP2B, OLAP-style (torture test), set of queries within a timeout, T, at a data size D
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SP2B•Stardog completes SP2B at 5M,
10M, and 25M (except q5a)
•No other RDF database completes > 5M. (As of the most recent report. Things change.)
•Considerable performance differential
•Pushing this out to 100M+ in 1.x
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BSBM• A throughput test, primarily. Not
necessarily simple queries
• On modest machine, 255 clients, 10M triples, we sustain 7m queries per hour (277k QMpH)
• At 100M, 255 clients, sustain 3m queries per hour (125k QMpH)
• Among the top 2 or 3 RDF DBs for BSBM performance
• We will tackle BSBM BI next...
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Data Loading• Two indexing modes
• Triples only indexing
• Faster loading, slower NG query
• Up to 250,000 triples per second
• Quads indexing
• Slower loading, faster NG query
• Up to 150,000 triples per second
• More improvements coming in the future
• Customized RDF parser
• Will look at user-defined index subsets26
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What’s new in 1.1
•Aforementioned user defined rules
•But most notably, SPARQL 1.1
•Our most requested feature in a survey
•Oh, we also made it faster
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SPARQL 1.1• Latest revision of the SPARQL query
language
• Put off implementing until spec finalized
• It’s still in flux, but we decided to go for it
• Adds useful new features to SPARQL
• Aggregates, grouping, sub-query, negation
• Oh, and the entailment regimes
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SPARQL 1.1• Rewrite of query planner & engine for 1.0.5
• Changes needed to support SPARQL 1.1
• Tested by users for the past 3 releases
• With great power comes great responsibility...
• New features are not without cost
• Query planning & optimization more crucial than ever
• Majority of development time
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Roadmap
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1. Transitivity & equality
2. GeoSPARQL
3. Web Console
4. Statement identifiers
5. Stored procedures & database triggers
6. “Stardocs”: doc/blob storage & NLP analytics
7. Graph Traversals, Algorithms & query langs
8. Statistical inference & machine learning
9. Stardog 2.0: Distributed Cluster Super Cloud Thingie!
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Summary
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Pick all three!
Easier. Smarter. Faster.
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Feature Rich• Support for RDFS, OWL2 profiles (EL, RL, QL) & OWL2 DL
via schema only queries
• Semantic Search
• ICV
• Transactions
• Rich security model
• Support for major APIs
• Jena & Sesame, and our own SNARL
• SPARQL HTTP protocol, Graph Store protocol
• Also includes a CLI & Shell environment
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