EMF-IncQuery presentation at TOOLS 2012
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The document presents an overview of integrating efficient model queries in state-of-the-art Eclipse Modeling Framework (EMF) tools, focusing on EMF-IncQuery, a model query engine optimized for incremental queries. It addresses scalability issues in model-driven engineering (MDE), highlights the performance benefits of EMF-IncQuery, and introduces new features such as an expressive query language and on-the-fly validations. The document concludes with performance benchmarks showcasing the speed advantages of EMF-IncQuery over traditional OCL methods, emphasizing its potential for large instance models.
EMF-IncQuery presentation at TOOLS 2012
- 1. Integrating Efficient Model Queries in State-of-the-art EMF Tools Gábor Bergmann, Ábel Hegedüs, Ákos Horváth, István Ráth, Zoltán Ujhelyi and Dániel Varró Budapest University of Technology and Economics TOOLS Europe 2012 Fault Tolerant Systems Research Group Prague, Czech Republic, 2012. 05. 30.
- 2. Overview Introduction EMF-INCQUERY overview Transparent query integration Performance considerations Conclusion
- 3. MDE today Modeling techniques Integrated model-driven tools REQ Model- SD based early analysis Architecture IMP modeling, DSMLs TST Code generation, IDE model-assisted Model-based development test generation
- 4. MDE today Modeling techniques Eclipse Modeling Framework REQ SD IMP TST IDE - Eclipse
- 5. A key problem of MDE Scalability vs. modeling tools o Issues encountered by several industrial partners using tools based on the Eclipse Modeling Framework (EMF) o Modeling scenarios can get really complex really quickly • Instance models of size 1-2M and beyond • Performance issues with model transformations and code generators have an adverse effect on everyday development tasks Scalability? Recognized e.g. by AUTOSAR tool vendors o Complex http://wiki.eclipse.org/Auto_IWG_WP2 (meta)models o Large instance models o Complex query and manipulation scenarios
- 6. Focus: model queries Model queries: “a piece of code that retrieves a given set of the model” Queries are at the heart of MDE o Every model access/read is a (simple) query o More complex: Views, content providers o Most complex: Model transformations, code generators, … Query performance (= the speed of content retrieval) is crucial o First vs. consecutive vs. throughput o Query result vs. query contents Core problems 1. Slow query engines 2. Considerable programming effort necessary to get complex queries right
- 7. EMF-INCQUERY
- 8. Overview EMF-INCQUERY: a model query engine o Supports batch queries o Optimized for incremental queries! Incremental evaluation o Based on the RETE algorithm o Compute once, update afterwards o Gain: Instant re-evaluation o Price: Uses some more memory • Manageable with proper life cycles
- 9. EMF instance model Input = Model contents + changes (EMF notifications) Input RETE network nodes Query definition Intermediate nodes Output Delta nodes monitor Generated query components Query engine Output = Query results + (subsequent) Query result deltas
- 10. Benefits of EMF-INCQUERY Makes on-the-fly well-formedness validation, view maintenance, … feasible over really large instance models Simplifies writing really complex queries o Graph pattern language o Highly reusable query libraries Easy-to-integrate into existing apps o Works with any EMF domain metamodel o Integrates through Eclipse standards works with many EMF-based apps out-of-the-box
- 11. DEMO INCQUERY Pattern Language School metamodel in EMF
- 12. INCQUERY Pattern Language Expressive declarative query language by graph patterns Capture local + global queries Compositionality + Reusabilility „Arbitrary” Recursion, Negation
- 13. New features with version 0.6 Tools o Xtext2-based language • Content assist (code completion), validation, outline, … o Unique query language features • Unlimited recursion and transitive closure • Aggregate functions • Match/exceed the expressive power of OCL, while providing more flexible re-use Runtime o Build and execute queries on-the-fly o Strong generative bindings to Java o Efficient incremental transitive closure
- 14. INCQUERY Development Tools • Works with most EMF- based editors out-of- the-box • Reveals matches as selection Pattern Editor Queries are applied & updates on-the- fly Query Explorer
- 15. INCQUERY Model Validation • Works with most EMF- based tools out-of-the- box • Manages error-warning markers on-the-fly as the Standard Eclipse BPMN Editor user is editing the model = Instantaneous feedback Markers in the Problems View
- 16. TRANSPARENT QUERY INTEGRATION … beyond the development tools
- 17. Derived features in EMF Derived features: Derived attributes: • Supported by auxiliary • Typed scalar values mechanisms (e.g. Java, OCL) • Supported by • Supported by EMF-based INCQUERY derivatives <<derived>> tools out-of-the-box <<derived>> <<derived>> Derived edges: • Binary relationships • Supported by binary INCQUERY patterns
- 18. INCQUERY derivatives You can combine IQPL with (side-effect free, deterministic) Xbase Key benefits: • Automatic dependency-aware change notifications Derived attribute for derived features “hasPrimeWeight”: • Instantaneous result True iff pattern retrieval “coursePrimeWeight” matches to host C
- 19. PERFORMANCE BENCHMARK Instantaneous result retrieval?
- 20. Benchmarking scenario In-memory models o Embedded railways control software system design domain o Instance models up to 2.7M elements Scenario: well-formedness validation o 5 rules, from simple to very complex o Batch validation: loading models + executing queries o On-the-fly revalidation: modifying models + re-executing queries instantaneously Tools o Eclipse tools (OCL, INCQUERY, EMF-Java) o RDF/SPARQL engines (for comparison) http://viatra.inf.mit.bme.hu/publications/trainbenchmark
- 21. Revalidation on-the-fly SPARQL tools are • Incremental EMF engines generally 1-2 Orders-of- typically 5-10x faster Magnitude (OM) slower • sub-100ms response times than top EMF tools for up to 1.5M elements
- 22. A closer look at the top Performance advantage of OCL-IA over OCL is not significant with complex queries INCQUERY is 1-1.5 orders- of-magnitude faster than OCL-IA
- 23. Memory usage • Incremental engines impose a linear memory consumption overhead • INCQUERY overhead is larger than OCL-IA • Even the largest models fit into 1GB of RAM
- 24. Final points EMF-INCQUERY has been proposed as an Eclipse.org project under EMFT http://www.eclipse.org/proposals/modeling.emf.incquery/ EMF-INCQUERY 0.6 preview release is available immediately o Pointers: http://viatra.inf.mit.bme.hu/incquery http://viatra.inf.mit.bme.hu/incquery/getting_started http://viatra.inf.mit.bme.hu/performance Release 0.6 is scheduled shortly after the Eclipse Juno Launch (beginning of July)
- 25. Acknowledgements Additional development team members o Márk Czotter, Tamás Szabó Performance benchmarking o Benedek Izsó, Zoltán Szatmári Testing, examples o Attila Csicsely, Tamás Csurgó, Dániel Kávássy, Gábor Szárnyas, Tamás Tóth Thank you very much!