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Conference Paper

Sifter: Scalable Sampling for Distributed Traces, without Feature Engineering

MPS-Authors
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Las-Casas,  Pedro Henrique B.
Group J. Mace, Max Planck Institute for Software Systems, Max Planck Society;

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Papakerashvili,  Giorgi
Group J. Mace, Max Planck Institute for Software Systems, Max Planck Society;

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Anand,  Vaastav
Group J. Mace, Max Planck Institute for Software Systems, Max Planck Society;

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Mace,  Jonathan
Group J. Mace, Max Planck Institute for Software Systems, Max Planck Society;

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Citation

Las-Casas, P. H. B., Papakerashvili, G., Anand, V., & Mace, J. (2019). Sifter: Scalable Sampling for Distributed Traces, without Feature Engineering. In SoCC'19 (pp. 312-324). New York, NY: ACM. doi:10.1145/3357223.3362736.


Cite as: https://hdl.handle.net/21.11116/0000-0005-F062-D
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