Cost-Effective Resource Configurations for Executing Data-Intensive Workloads in Public Clouds

........................................................................................................................................... ii Co-Authorship ................................................................................................................................ iv Dedications ..................................................................................................................................... vi Acknowledgements ........................................................................................................................ vii Statement of Originality ................................................................................................................ viii Chapter 1 : Introduction ................................................................................................................... 1 1.1 Cloud Computing and its Offerings to Large-Scale Data Processing .................................... 1 1.2 Examples of Data Growth in Scientific and Commercial Domains ...................................... 5 1.3 The Need for Workload Management and Resource Provisioning ....................................... 6 1.4 Thesis Contributions .............................................................................................................. 8 1.5 Thesis Statement .................................................................................................................... 9 1.6 Thesis Organization ............................................................................................................. 10 Chapter 2 : Background and State-of-the-Art ................................................................................ 11 2.1 Workload Management Taxonomy ..................................................................................... 11 2.2 Data Processing: Taxonomy and Survey ............................................................................. 14 2.2.1 MapReduce ................................................................................................................... 16 2.2.2 Dataflow-processing ..................................................................................................... 20 2.2.3 Shared-nothing Relational Processing .......................................................................... 24 2.2.4 Stream-processing ......................................................................................................... 28 2.2.5 MR&DB Hybrid ........................................................................................................... 31 2.2.6 Discussion ..................................................................................................................... 35 2.3 Provisioning: Taxonomy & Survey ..................................................................................... 39 2.3.1 Scaling........................................................................................................................... 41 2.3.2 Migration....................................................................................................................... 45 2.3.3 Surge Computing .......................................................................................................... 51 2.3.4 Discussion ..................................................................................................................... 54 2.4 Conclusions .......................................................................................................................... 57 2.4.1 Open Problems .............................................................................................................. 60 Chapter 3 : Overview of Our Approach ......................................................................................... 62 3.1 Problem Statement ............................................................................................................... 62 3.2 Framework ........................................................................................................................... 65 3.3 Evaluation Setup .................................................................................................................. 67 x 3.3.1 Tenant Databases and Request Types for Creating Workloads .................................... 67 3.3.2 Selection of VM Types ................................................................................................. 71 3.4 Outline of the Remaining Thesis ......................................................................................... 72 Chapter 4 : Experiment-Based Performance Models ..................................................................... 74 4.1 Motivation ............................................................................................................................ 74 4.2 Background .......................................................................................................................... 75 4.3 Variables in building a Performance Model ........................................................................ 78 4.4 Building the Performance Model ......................................................................................... 80 4.4.1 Sampling the Space of Request Mixes .......................................................................... 80 4.4.2 Experiment-driven Data Collection .............................................................................. 81 4.4.3 Constructing the Request Mix Model ........................................................................... 82 4.4.4 Determining a suitable number of samples ................................................................... 82 4.4.5 Comparison of Prediction Techniques .......................................................................... 86 4.5 Evaluation ............................................................................................................................ 89 4.5.1 Experiment Setup and Validation Method .................................................................... 89 4.5.2 Data Patterns: Identification and Treatment ................................................................. 91 4.5.2.1 Data Classes ........................................................................................................... 92 4.5.3 Validation Results ......................................................................................................... 94 4.5.3.1 Large VM Type (Optimal MPL=75) ..................................................................... 94 4.5.3.2 Small VM type (Optimal MPL=14) ..................................................................... 100 4.5.3.3 Xlarge VM type (Optimal MPL=115) ................................................................. 101 4.6 Modeling Non-linear Behaviour ........................................................................................ 103 4.7 Conclusions ........................................................................................................................ 107 Chapter 5 : Analytical Cost Model .............................................................................................. 110 5.1 Motivation .......................................................................................................................... 110 5.2 Background ........................................................................................................................ 111 5.3 Different Resource Types and Pricing Schemes in IaaS Clouds ....................................... 112 5.3.1 Resource Types and Sub Types .................................................................................. 113 5.3.2 Pricing Schemes .......................................................................................................... 115 5.4 Cost Model ......................................................................................................................... 116 5.5 Evaluation .......................................................................................................................... 119 5.5.1 Tenants and Workloads ............................................................................................... 120 5.5.2 Cost Model for the Amazon cloud .............................................................................. 121 5.5.3 Experiments ................................................................................................................ 123 xi 5.5.3.1 VM Type .............................................................................................................. 125 5.5.3.2 Workload Mix ...................................................................................................... 126 5.5.3.3 SLA Penalties ....................................................................................................... 127 5.6 Conclusions ........................................................................................................................ 130 Chapter 6 : Heuristic-based Configuration Selection .................................................................. 133 6.1 Motivation .......................................................................................................................... 133 6.2 Background ........................................................................................................................ 134 6.3 Determining a Cost-Effective Configuration ..................................................................... 136 6.3.1 Modifications .............................................................................................................. 137 6.3.2 Search Algorithms ...................................................................................................... 139 6.4 Evaluation ...........................................................................................

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