Nothing Special   »   [go: up one dir, main page]

Ma et al., 2018 - Google Patents

Query-based workload forecasting for self-driving database management systems

Ma et al., 2018

View PDF
Document ID
6942087600558224518
Author
Ma L
Van Aken D
Hefny A
Mezerhane G
Pavlo A
Gordon G
Publication year
Publication venue
Proceedings of the 2018 International Conference on Management of Data

External Links

Snippet

The first step towards an autonomous database management system (DBMS) is the ability to model the target application's workload. This is necessary to allow the system to anticipate future workload needs and select the proper optimizations in a timely manner. Previous …
Continue reading at www.cs.cmu.edu (PDF) (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30286Information retrieval; Database structures therefor; File system structures therefor in structured data stores
    • G06F17/30386Retrieval requests
    • G06F17/30424Query processing
    • G06F17/30533Other types of queries
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30286Information retrieval; Database structures therefor; File system structures therefor in structured data stores
    • G06F17/30587Details of specialised database models
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F11/00Error detection; Error correction; Monitoring
    • G06F11/30Monitoring
    • G06F11/34Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation; Recording or statistical evaluation of user activity, e.g. usability assessment
    • G06F11/3409Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation; Recording or statistical evaluation of user activity, e.g. usability assessment for performance assessment
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30286Information retrieval; Database structures therefor; File system structures therefor in structured data stores
    • G06F17/30289Database design, administration or maintenance
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F11/00Error detection; Error correction; Monitoring
    • G06F11/30Monitoring
    • G06F11/34Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation; Recording or statistical evaluation of user activity, e.g. usability assessment
    • G06F11/3466Performance evaluation by tracing or monitoring
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/50Computer-aided design
    • G06F17/5009Computer-aided design using simulation
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00Subject matter not provided for in other groups of this subclass
    • G06N99/005Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • G06Q10/06Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
    • G06Q10/063Operations research or analysis
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F2201/00Indexing scheme relating to error detection, to error correction, and to monitoring
    • G06F2201/86Event-based monitoring
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00Computer systems utilising knowledge based models
    • G06N5/04Inference methods or devices
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00Computer systems utilising knowledge based models
    • G06N5/02Knowledge representation
    • G06N5/022Knowledge engineering, knowledge acquisition

Similar Documents

Publication Publication Date Title
Ma et al. Query-based workload forecasting for self-driving database management systems
Zhou et al. Database meets artificial intelligence: A survey
Van Aken et al. An inquiry into machine learning-based automatic configuration tuning services on real-world database management systems
Zhang et al. Restune: Resource oriented tuning boosted by meta-learning for cloud databases
Ma et al. MB2: decomposed behavior modeling for self-driving database management systems
Pavlo et al. Self-Driving Database Management Systems.
Herodotou et al. Profiling, what-if analysis, and cost-based optimization of mapreduce programs
Ortiz et al. An empirical analysis of deep learning for cardinality estimation
Khoshkbarforoushha et al. Distribution based workload modelling of continuous queries in clouds
Popescu et al. Same queries, different data: Can we predict runtime performance?
Ipek et al. Efficient architectural design space exploration via predictive modeling
Dai et al. Provenance-based object storage prediction scheme for scientific big data applications
Wu et al. Invalid bug reports complicate the software aging situation
Ganapathi Predicting and optimizing system utilization and performance via statistical machine learning
Khoshkbarforoushha et al. Resource usage estimation of data stream processing workloads in datacenter clouds
Liang et al. Fast and reliable missing data contingency analysis with predicate-constraints
Zou et al. Survey on learnable databases: A machine learning perspective
Li et al. A resource-aware deep cost model for big data query processing
Vaidya et al. Leveraging query logs and machine learning for parametric query optimization
Kamali et al. Roq: Robust Query Optimization Based on a Risk-aware Learned Cost Model
Sinanaj et al. Granulation of large temporal databases: An allan variance approach
Khoshkbarforoushha et al. Resource and performance distribution prediction for large scale analytics queries
He et al. Query execution time estimation in graph databases based on graph neural networks
Nagwani et al. A data mining model to predict software bug complexity using bug estimation and clustering
Ma Self-Driving Database Management Systems: Forecasting, Modeling, and Planning