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Machine learning

LAFC-Evict: Learning-Augmented Cache Eviction Dataset

LAFC-Evict is a derived, tabular research dataset of counterfactual supervision labels for learning-augmented cache-eviction research. Each row describes one candidate object considered for eviction at one full-cache-miss decision point, together with engineered state/candidate features and labels describing what would happen to the cache miss rate over a short future horizon if that specific candidate were evicted. The current AWS release, v1.0, contains five trace families: cloudphysics, metacdn, metakv, twemcache, and wiki2018. It includes 277,995,072 candidate rows, 2,363,286 decision-view rows, and a 1,000,000-row pairwise...

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Data coverage

LAFC-Evict is a derived, tabular research dataset of counterfactual supervision labels for learning-augmented cache-eviction research. Each row describes one candidate object considered for eviction at one full-cache-miss decision point, together with engineered state/candidate features and labels describing what would happen to the cache miss rate over a short future horizon if that specific candidate were evicted. The current AWS release, v1.0, contains five trace families: cloudphysics, metacdn, metakv, twemcache, and wiki2018. It includes 277,995,072 candidate rows, 2,363,286 decision-view rows, and a 1,000,000-row pairwise sample. LAFC-Evict is a generated/derived artifact and does not redistribute raw upstream trace logs, raw Wikimedia pageview rows, raw page titles, or other third-party raw data. The historical v0.3 wiki2018-only AWS publication remains preserved at the bucket root for reproducibility; v1.0 is available under the versioned prefix s3://lafc-evict-open-data/v1.0/.

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