1 / 24

GeoLoc : Robust Resource Allocation Method for Query Optimization in Data Grid Systems

GeoLoc : Robust Resource Allocation Method for Query Optimization in Data Grid Systems. Igor EPIMAKHOV Abdelkader HAMEURLAIN Franck MORVAN. Baltic DB&IS'2012. Table of contents. Introduction Existing methods classification Contributions Allocation Space Allocation Algorithm

clucinda
Download Presentation

GeoLoc : Robust Resource Allocation Method for Query Optimization in Data Grid Systems

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. GeoLoc:Robust Resource Allocation Method for Query Optimization in Data Grid Systems Igor EPIMAKHOV Abdelkader HAMEURLAIN Franck MORVAN Baltic DB&IS'2012

  2. Table of contents • Introduction • Existing methods classification • Contributions • Allocation Space • Allocation Algorithm • Performance Evaluation • Conclusion

  3. Introduction Data Grid • Heterogeneity • Dynamicity • Large Scale

  4. Introduction Query processing Query execution Parsing Query rewrite Resource allocation Resource discovery

  5. Introduction Problem Input: • Set of query operations (dependent) • Set of nodes • Distribution of Relations • Dynamic and Static characteristics of Data Grid Objectives: • Select optimal subset of nodes to allocate resources for query operations

  6. Existing Methods Classification Control structure: Centralized Hierarchical Decentralized

  7. Existing Methods Classification Algorithms: Heuristic Exact

  8. Existing Methods Classification Static Strategies: Resource Allocation Execution Dynamic Resource Allocation Execution Hybrid Execution with Dynamic Reallocation Resource Allocation

  9. Existing Methods Classification • Cooperation type: • Classic • Incentive-based • Economic / Reputation

  10. Contributions • Allocation Space Restriction • Algorithm of Resource Allocation Parallelism: pipeline, intra-operation, inter-operation Distributed and duplicated relations

  11. Allocation Space Source nodes Nearest nodes

  12. Allocation Algorithm Assumptions • Each relation is distributed by N equal parts • Hybrid Hash Join algorithm • Results are being retransferred from the nodes • Memory is using for reducing I/O operations

  13. Allocation Algorithm • Input: • All nodes with fragments of queried relations (1) • All nodes nearest to (1) Stage 1. Definition of Allocation Space CPU NET I/O Overall Node Bandwidth • Algorithm: • Selection of source nodes on the base of their performance • Placement of Scan operations • Generation of Allocation Space (source nodes + nearest nodes)

  14. Allocation Algorithm • Input: • Query logic plan • Generated Allocation Space • Idea: • Parity in bandwidth between Scan and Join operations Stage 2. Generation of execution plan • Algorithm: • BEGIN • FOR each join DO • Count the time of source relations read and transferring, Tscan_exec • DO • Choose the most efficient node Neff from a set of AS for placing join operation • Add Neff to the join allocation plan, Pjoin • Estimate the execution time of join, Tjoin_exec • WHILE (Tjoin_exec > Tscan_exec) • Add Pjoin to the query allocation plan, Pquery • ENDFOR • END

  15. Allocation Algorithm Query: R S R = R1U R2 S = S1U S2 R1: n1, n2 R2: n3, n4 S1: n5, n6 S2: n7, n8 Example n5 n2 n8 n6 n1 n3 n7 n4

  16. Allocation Algorithm Query: R S R = R1U R2 S = S1U S2 R1:n1, n2 R2: n3, n4 S1: n5, n6 S2:n7, n8 Example n5 n2 n8 n6 n1 n3 n7 n4

  17. Allocation Algorithm n25 n26 n14 n11 n12 n10 n19 n16 n13 n17 n15 n20 n18 n22 n24 n23 n21 Query: R S R = R1U R2 S = S1U S2 Allocation space n1, n4, n6, n7, n10 n11, n12, n13, n14 n15, n16, n17, n18 n19, n20, n21, n22 n23, n24, n25, n26 Example n5 n2 n8 n6 n1 n3 n7 n4

  18. Allocation Algorithm n25 n26 n14 n11 n12 n10 n19 n16 n13 n17 n15 n20 n18 n22 n24 n23 n21 Query: R S R = R1U R2 S = S1U S2 Allocation space n1, n4, n6, n7, n10 n11, n12, n13, n14 n15, n16, n17, n18 n19, n20, n21, n22 n23, n24, n25, n26 Example n5 n2 n8 n6 n1 n3 n7 n4

  19. Allocation Algorithm Source Nodes n25 n26 n18 n19 n12 n13 n10 Allocation space n1, n4, n6, n7, n10 n11, n12, n13, n14 n15, n16, n17, n18 n19, n20, n21, n22 n23, n24, n25, n26 Resulted Execution Plan Scans: n1, n4, n7, n6 Joins: n18, n25, n10, n26, n13, n12, n19 n1 n4 n7 n6 Example Nodes’ Bandwidth: 2000 lines/sec Nodes allocated for Join Nodes’ Bandwidth: 1790 lines/sec 2000 lines/sec 1300 lines/sec 1500 lines/sec 1650 lines/sec 1920 lines/sec 900 lines/sec

  20. Performance Evaluation Experimental conditions • Data Grid simulator • 6000 heterogeneous nodes • Simple, Average and Complex queries • Distributed and duplicated relations Comparison • Method GeoLoc • Method Gounaris2004

  21. Performance Evaluation Optimization Time

  22. Performance Evaluation Response Time

  23. Conclusion Proposed method is: • Efficient • Scalable • Adapted to heterogeneous decentralized Data Grid Perspective: • Adaptation to the Dynamicity of Data Grid

  24. Thank you for your attention!

More Related