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![07/10/2016 PrefetchML: a Framework for Prefetching and Caching Models - G. Daniel 10
PrefetchML DSL
import ''http://www.example.com/Java''
plan samplePlan {
use cache LRU[size=100, chunk=10]
rule r1: on starting
fetch Package.allInstances()
rule r2: on access type ClassDeclaration
fetch self.bodyDeclarations.modifier
}
Package
+ name : String
ClassDeclaration
+ name : String
BodyDeclaration
+ name : String
Modifier
+ kind : VisibilityKind
*
1
ownedElements
*
bodyDeclarations
modifier](https://image.slidesharecdn.com/slideprefetch-161108040304/85/PrefetchML-a-Framework-for-Prefetching-and-Caching-models-10-320.jpg)
![07/10/2016 PrefetchML: a Framework for Prefetching and Caching Models - G. Daniel 11
PrefetchML DSL
import ''http://www.example.com/Java''
plan samplePlan {
use cache LRU[size=100, chunk=10]
rule r1: on starting
fetch Package.allInstances()
rule r2: on access type ClassDeclaration (self.name = 'MyClass')
fetch self.bodyDeclarations.modifier
}
Package
+ name : String
ClassDeclaration
+ name : String
BodyDeclaration
+ name : String
Modifier
+ kind : VisibilityKind
*
1
ownedElements
*
bodyDeclarations
modifier](https://image.slidesharecdn.com/slideprefetch-161108040304/85/PrefetchML-a-Framework-for-Prefetching-and-Caching-models-11-320.jpg)
![07/10/2016 PrefetchML: a Framework for Prefetching and Caching Models - G. Daniel 12
PrefetchML DSL
import ''http://www.example.com/Java''
plan samplePlan {
use cache LRU[size=100, chunk=10]
rule r1: on starting
fetch Package.allInstances()
rule r2: on access type ClassDeclaration (self.name = 'MyClass')
fetch self.bodyDeclarations.modifier
remove type Package
}
Package
+ name : String
ClassDeclaration
+ name : String
BodyDeclaration
+ name : String
Modifier
+ kind : VisibilityKind
*
1
ownedElements
*
bodyDeclarations
modifier](https://image.slidesharecdn.com/slideprefetch-161108040304/85/PrefetchML-a-Framework-for-Prefetching-and-Caching-models-12-320.jpg)
Uploaded byJordi Cabot
PrefetchML: a Framework for Prefetching and Caching models
PrefetchML is a framework designed for prefetching and caching models, improving the performance of I/O intensive applications by loading necessary data into memory beforehand. It features a domain-specific language (DSL) for defining high-level prefetching and caching rules, and its engine operates transparently with various databases. Future work includes automatic generation of plans and dynamic adaptation of cache rules based on access patterns.
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PrefetchML: a Framework for Prefetching and Caching models
- 1. PrefetchML: a Frameworkfor Prefetching and Caching Models Jordi Cabot ICREA-UOC jordi.cabot@icrea.cat Gwendal Daniel Inria - Mines Nantes & Lina gwendal.daniel@inria.fr Gerson Sunyé Inria - Mines Nantes & Lina gerson.sunye@inria.fr
- 2. 07/10/2016 PrefetchML: aFramework for Prefetching and Caching Models - G. Daniel 2 Introduction ● Prefetching – Bring objects into memory before they are requested ● Caching – Retain objects in memory to speed-up their access ● Integrated in databases and file systems – Speeds-up I/O intensive applications
- 3. 07/10/2016 PrefetchML: aFramework for Prefetching and Caching Models - G. Daniel 3 Introduction ● Database prefetchers & caches – Lack of fine-grained configuration ● Elements to load ● Usage scenario – Tightly coupled to data representation ● Low level of abstraction ● Not reusable – Not a common in NoSQL stores
- 4. 07/10/2016 PrefetchML: aFramework for Prefetching and Caching Models - G. Daniel 4 Introduction ● We need to prefetch and cache models – Scalable Persistence Frameworks ● Databases to store large models (relational, NoSQL, ...) ● Latencies to bring elements from the database ● I/O intensive
- 5. 07/10/2016 PrefetchML: aFramework for Prefetching and Caching Models - G. Daniel 5 Introduction ● We need to prefetch and cache models – Metamodel informations ● High-level prefetching rules ● Decoupled from data representation
- 6. 07/10/2016 PrefetchML: aFramework for Prefetching and Caching Models - G. Daniel 6 PrefetchML ● A prefetching and caching framework at the model level PrefetchML DSL PrefetchML Engine – Metamodel and model level – Use case dependent – Readable – Datastore-independent – Transparent for the persistence solution rule definition rule execution
- 7. 07/10/2016 PrefetchML: aFramework for Prefetching and Caching Models - G. Daniel 7 PrefetchML DSL ● Define prefetching and caching rules grouped in plans ● Event-based language – Model loading – Element access, update, deletion – OCL guards ● OCL loading instructions ● Cache management – Define cache policy – Remove cached elements
- 8. 07/10/2016 PrefetchML: aFramework for Prefetching and Caching Models - G. Daniel 8 PrefetchML DSL import ''http://www.example.com/Java'' plan samplePlan { rule r1: on starting fetch Package.allInstances() } Package + name : String ClassDeclaration + name : String BodyDeclaration + name : String Modifier + kind : VisibilityKind * 1 ownedElements * bodyDeclarations modifier
- 9. 07/10/2016 PrefetchML: aFramework for Prefetching and Caching Models - G. Daniel 9 PrefetchML DSL import ''http://www.example.com/Java'' plan samplePlan { rule r1: on starting fetch Package.allInstances() rule r2: on access type ClassDeclaration fetch self.bodyDeclarations.modifier } Package + name : String ClassDeclaration + name : String BodyDeclaration + name : String Modifier + kind : VisibilityKind * 1 ownedElements * bodyDeclarations modifier
- 10. 07/10/2016 PrefetchML: aFramework for Prefetching and Caching Models - G. Daniel 10 PrefetchML DSL import ''http://www.example.com/Java'' plan samplePlan { use cache LRU[size=100, chunk=10] rule r1: on starting fetch Package.allInstances() rule r2: on access type ClassDeclaration fetch self.bodyDeclarations.modifier } Package + name : String ClassDeclaration + name : String BodyDeclaration + name : String Modifier + kind : VisibilityKind * 1 ownedElements * bodyDeclarations modifier
- 11. 07/10/2016 PrefetchML: aFramework for Prefetching and Caching Models - G. Daniel 11 PrefetchML DSL import ''http://www.example.com/Java'' plan samplePlan { use cache LRU[size=100, chunk=10] rule r1: on starting fetch Package.allInstances() rule r2: on access type ClassDeclaration (self.name = 'MyClass') fetch self.bodyDeclarations.modifier } Package + name : String ClassDeclaration + name : String BodyDeclaration + name : String Modifier + kind : VisibilityKind * 1 ownedElements * bodyDeclarations modifier
- 12. 07/10/2016 PrefetchML: aFramework for Prefetching and Caching Models - G. Daniel 12 PrefetchML DSL import ''http://www.example.com/Java'' plan samplePlan { use cache LRU[size=100, chunk=10] rule r1: on starting fetch Package.allInstances() rule r2: on access type ClassDeclaration (self.name = 'MyClass') fetch self.bodyDeclarations.modifier remove type Package } Package + name : String ClassDeclaration + name : String BodyDeclaration + name : String Modifier + kind : VisibilityKind * 1 ownedElements * bodyDeclarations modifier
- 13. 07/10/2016 PrefetchML: aFramework for Prefetching and Caching Models - G. Daniel 13 PrefetchML Engine ● Rule execution engine ● Executes loading instructions ● Captures events ● Transparent to the modeling framework ● Database independent – Specialized connectors
- 14. 07/10/2016 PrefetchML: aFramework for Prefetching and Caching Models - G. Daniel 14 PrefetchML Engine
- 15. 07/10/2016 PrefetchML: aFramework for Prefetching and Caching Models - G. Daniel 15 PrefetchML Engine
- 16. 07/10/2016 PrefetchML: aFramework for Prefetching and Caching Models - G. Daniel 16 PrefetchML Engine
- 17. 07/10/2016 PrefetchML: aFramework for Prefetching and Caching Models - G. Daniel 17 PrefetchML Engine
- 18. 07/10/2016 PrefetchML: aFramework for Prefetching and Caching Models - G. Daniel 18 Tooling ● PrefetchML Editor – XText editor – Navigation hints – Rule validation
- 19. 07/10/2016 PrefetchML: aFramework for Prefetching and Caching Models - G. Daniel 19 Tooling
- 20. 07/10/2016 PrefetchML: aFramework for Prefetching and Caching Models - G. Daniel 20 Evaluation Q1 Q2 Q3 0 2 4 6 8 10 12 14 16 18 No Pref. EMF Pref. NeoEMF Pref. ExecutionTime(s) Q1 Q2 Q3 0 1 2 3 4 5 6 7 8 9 ExecutionTime(s) ● Model containing 2 million elements ● MDT OCL over NeoEMF/Graph Cold Execution (empty cache) Warmed Execution
- 21. 07/10/2016 PrefetchML: aFramework for Prefetching and Caching Models - G. Daniel 21 Conclusion ● Model-level prefetching & caching framework ● PrefetchML DSL: defines prefetching and caching rules at a high level of abstraction ● PrefetchML Engine: captures events, trigger rules, cache model elements
- 22. 07/10/2016 PrefetchML: aFramework for Prefetching and Caching Models - G. Daniel 22 Conclusion ● Future work – Automatic generation of PrefetchML plans ● ATL transformations ● Code analysis – Dynamic discovery of frequent access patterns ● Log mining ● Switch on/off plans when needed ● Add/remove rules at runtime
- 23. 07/10/2016 PrefetchML: aFramework for Prefetching and Caching Models - G. Daniel 23 Questions? Websites / Repositories PrefetchML: https://github.com/atlanmod/Prefetching_Caching_DSL NeoEMF: neoemf.com https://github.com/atlanmod Thank you for your attention! https://github.com/SOM-Research
- 24. 07/10/2016 PrefetchML: aFramework for Prefetching and Caching Models - G. Daniel 24 PrefetchML Engine