Source: https://acc.digital/robust-query-processing-in-database-systems/9/
Timestamp: 2019-04-18 12:16:39+00:00

Document:
M. Abhirama, S. Bhaumik, A. Dey, H. Shrimal and J. Haritsa, “On the Stability of Plan Costs and the Costs of Plan Stability”, PVLDB Journal, 3(1), 2010.
 A. Aboulnaga and S. Chaudhuri, “Self-tuning Histograms: Building Histograms Without Looking at Data”, Prod. of ACM SIGMOD Intl. Conf. of Management of Data, 1999.
 M. Akdere, U. Cetintemel, M. Riondato, E. Upfal and S. Zdonik, “Learning-based query performance modeling and prediction”, Proc. of IEEE Intl. Conf. on Data Engineering (ICDE), 2012.
 R. Avnur and J. Hellerstein, “Eddies: Continuously Adaptive Query Processing”, Proc. of ACM SIGMOD Intl. Conf. on Management of Data, 2000.
 B. Babcock and S. Chaudhuri, “Towards a Robust Query Optimizer: A Principled and Practical Approach”, Proc. of ACM SIGMOD Intl. Conf. on Management of Data, 2005.
 S. Babu, P. Bizarro, and D. DeWitt, “Proactive re-optimization”, ACM SIGMOD Intl. Conf. on Management of Data, 2005.
 R. Borovica-Gajic, S. Idreos, A. Ailamaki, M. Zukowski and C. Fraser, “Smooth Scan: Statistics-oblivious access paths”, Proc. of IEEE Intl. Conf. on Data Engineering (ICDE), 2015.
 S. Chaudhuri, “An Overview of Query Optimization in Relational Systems”, Proc. of ACM Symp. on Principles of Database Systems (PODS), 1998.
 S. Chaudhuri, “Query Optimizers: Time to rethink the contract?”, Proc. of ACM SIGMOD Intl. Conf. on Management of Data, 2009.
 S. Chaudhuri, Interview in ACM XRDS, 19(1), 2012.
 S. Chen, P. Gibbons, and S. Nath, “Rethinking Database Algorithms for Phase Change Memory”, Proc. of 5th Biennial Conf. on Innovative Data Systems Research (CIDR), 2011.
 F. Chu, J. Halpern and P. Seshadri, “Least Expected Cost Query Optimization: An Exercise in Utility”, Proc. of ACM Symp. on Principles of Database Systems (PODS), 1999.
 F. Chu, J. Halpern and J. Gehrke, “Least Expected Cost Query Optimization: What can we expect?”, Proc. of ACM Symp. on Principles of Database Systems (PODS), 2002.
 E. Codd, “A Relational Model of Data for Large Shared Data Banks”, Comm. of the ACM , 13 (6), 1970.
 A. Deshpande, Z. Ives and V. Raman, “Adaptive Query Processing”, Foundations and Trends in Databases, Now Publishers, 1 (1), 2007.
 D. DeWitt, Interview in ACM Sigmod Record, 31(2), 2002.  A. Dutt and J. Haritsa, “Plan Bouquets: A Fragrant Approach to Robust Query Processing”, ACM Trans. on Database Systems (TODS), 41(2), 2016.
 A. Dutt and J. Haritsa, “Plan Bouquets: A Fragrant Approach to Robust Query Processing”, ACM Trans. on Database Systems (TODS), 41(2), 2016.
 A. Dutt, V. Narasayya and S. Chaudhuri, “Leveraging re-costing for online optimization of parameterized queries with guarantees”, Proc. of ACM SIGMOD Intl. Conf. on Management of Data, 2016.
 G. Graefe, “Query evaluation techniques for large databases”, ACM Computing Surveys, 25(2), 1993.
 J. Gray, “The Transaction Concept: Virtues and Limitations”, Proc. of 7th Intl. Conf. on Very Large Data Bases (VLDB), 1981.
 G. Graefe, “New algorithms for join and grouping operations”, Computer Science – R&D, 27(1), 2012.
 J. Haritsa, “The Picasso Database Query Optimizer Visualizer”, PVLDB Journal, 3(2), 2010.
 J. Haritsa, “Plan Diagrams: Visualizing Database Query Optimizers”, Annals of Indian National Academy of Engineering (INAE), Volume VIII, 2011.
 D. Harish, P. Darera and J. Haritsa, “On the Production of Anorexic Plan Diagrams”, Proc. of 31st Intl. Conf. on Very Large Data Bases (VLDB), 2007.
 D. Harish, P. Darera and J. Haritsa, “Identifying Robust Plans through Plan Diagram Reduction”, PVLDB Journal, 1(1), 2008.
 A. Hulgeri and S. Sudarshan, “Parametric Query Optimization for Linear and Piecewise Linear Cost Functions”, Proc. of 28th Intl. Conf. on Very Large Data Bases (VLDB), 2002.
 A. Hulgeri and S. Sudarshan, “AniPQO: Almost Non-intrusive Parametric Query Optimization for Nonlinear Cost Functions”, Proc. of 29th Intl. Conf. on Very Large Data Bases (VLDB), 2003.
 Y. Ioannidis and S. Christodoulakis, “On the propagation of errors in the size of join results”, Proc. of ACM SIGMOD Intl. Conf. on Management of Data, 1991.
 N. Kabra and D. DeWitt, “Efficient Mid-query Re-optimization of Sub-optimal Query Execution Plans”, Proc. of ACM SIGMOD Intl. Conf. on Management of Data, 1998.
 S. Karthik, J. Haritsa, S. Kenkre, V. Pandit and L. Krishnan, “Platform-independent Robust Query Processing”, IEEE Trans. on Knowledge and Data Engineering (TKDE), 2017.
 V. Leis, A. Gubichev, A. Mirchev, P. Boncz, A. Kempers and T. Neumann, “How Good are Query Optimizers, Really?”, PVLDB Journal, 9(3), 2015.
 V. Leis, B. Radke, A. Gubichev, A. Kempers and T. Neumann, “Cardinality Estimation DoneRight: Index-based Join Sampling”, Proc. of Conf. on Innovative Data Systems Research (CIDR), 2017.
 G. Lohman, “Is Query Optimization a â˘AIJSolvedâ˘A˙I Problem?”, wp.sigmod.org/?p=1075.
 L. Mackert and G. Lohman, “R Optimizer Validation and Performance Evaluation for Local Queries”, Proc. of ACM SIGMOD Intl. Conf. on Management of Data, 1986.
 T. Malik, R. Burns and N. Chawla, “A Black-Box Approach to Query Cardinality Estimation”, Proc. of Conf. on Innovative Data Systems Research (CIDR), 2007.
 V. Markl, V. Raman, D. Simmen, G. Lohman, H. Pirahesh, and M. Cilimdzic, “Robust query processing through progressive optimization”, Proc. of ACM SIGMOD Intl. Conf. on Management of Data, 2004.
 G. Moerkotte, T. Neumann and G. Steidl, “Preventing Bad Plans by Bounding the Impact of Cardinality Estimation Errors”, PVLDB Journal, 2(1), 2009.
 T. Neumann and C. Galindo-Legaria, “Taking the Edge off Cardinality Estimation Errors using Incremental Execution”, Proc. of BTW Conf., 2013.
 N. Reddy and J. Haritsa, “Analyzing Plan Diagrams of Database Query Optimizers”, Proc. of 31st Intl. Conf. on Very Large Data Bases (VLDB)., 2005.
 W. Rodiger, S. Idicula, A. Kemper and T. Neumann, “Flow-join: Adaptive skew handling for distributed joins over high-speed networks”, Proc. of IEEE Intl. Conf. on Data Engineering (ICDE), 2016.
 P. Selinger, P. Griffiths, M. Astrahan, D. Chamberlin, R. Lorie, and T. Price. “Access Path Selection in a Relational Database Management System”, Proc. of ACM SIGMOD Intl. Conf. on Management of Data, 1979.
 M. Stillger, G. Lohman, V. Markl and M. Kandil, “LEO – DB2’s LEarning Optimizer”, Proc. of 27th Intl. Conf. on Very Large Data Bases (VLDB), 2001.
 K. Tzoumas, A. Deshpande and C. Jensen, “Lightweight graphical models for selectivity estimation without independence assumptions”, PVLDB Journal, 4(11), 2011.
 K. Tzoumas, A. Deshpande and C. Jensen, “Efficiently adapting graphical models for selectivity estimation”, VLDB Journal, 22(1), 2013.
 W. Wu, Y. Chi, H. Hacigumus and J. Naughton, “Towards predicting query execution time for concurrent and dynamic databae workloads”, PVLDB Journal, 6(10), 2013.
 W. Wu, Y. Chi, S. Zhu, J. Tatemura, H. Hacigumus and J. Naughton, “Predicting query execution time: Are optimizer cost models really unusable?”, Proc. of IEEE Intl. Conf. on Data Engineering (ICDE), 2012.
 W. Wu, X. Wu, H. Hacigumus and J. Naughton, “Uncertainty Aware Query Execution Time Prediction”, PVLDB Journal, 7(14), 2014.
 Dagstuhl Seminar on Robust Query Processing, 2010.
 Dagstuhl Seminar on Robust Query Processing, 2012.
 Dagstuhl Seminar on Robust Query Processing, 2017.

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