STEAM: Observability-Preserving Trace Sampling

Author:

He Shilin1,Feng Botao1,Li Liqun1,Zhang Xu1,Kang Yu1,Lin Qingwei1,Rajmohan Saravan2,Zhang Dongmei1

Affiliation:

1. Microsoft, Beijing, China

2. Microsoft, Redmond, USA

Publisher

ACM

Reference52 articles.

1. Paul Barham , Rebecca Isaacs , Richard Mortier , and Dushyanth Narayanan . 2003 . Magpie: Online modelling and performance-aware systems . In 9th Workshop on Hot Topics in Operating Systems (HotOS IX). Paul Barham, Rebecca Isaacs, Richard Mortier, and Dushyanth Narayanan. 2003. Magpie: Online modelling and performance-aware systems. In 9th Workshop on Hot Topics in Operating Systems (HotOS IX).

2. Elisa Celis , Vijay Keswani , Damian Straszak , Amit Deshpande , Tarun Kathuria , and Nisheeth Vishnoi . 2018 . Fair and diverse DPP-based data summarization . In International Conference on Machine Learning. 716–725 . Elisa Celis, Vijay Keswani, Damian Straszak, Amit Deshpande, Tarun Kathuria, and Nisheeth Vishnoi. 2018. Fair and diverse DPP-based data summarization. In International Conference on Machine Learning. 716–725.

3. Large Scale Online Learning of Image Similarity Through Ranking;Chechik Gal;Journal of Machine Learning Research,2010

4. Laming Chen , Guoxin Zhang , and Eric Zhou . 2018. Fast greedy map inference for determinantal point process to improve recommendation diversity. Advances in Neural Information Processing Systems, 31 ( 2018 ). Laming Chen, Guoxin Zhang, and Eric Zhou. 2018. Fast greedy map inference for determinantal point process to improve recommendation diversity. Advances in Neural Information Processing Systems, 31 (2018).

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1. Tracemesh: Scalable and Streaming Sampling for Distributed Traces;2024 IEEE 17th International Conference on Cloud Computing (CLOUD);2024-07-07

2. The Diagnosis-Effective Sampling of Application Traces;Applied Sciences;2024-07-02

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