Exathlon: A Benchmark for Explainable Anomaly Detection over Time Series

Understand

Access to high-quality data repositories and benchmarks have been instrumental in advancing the state of the art in many experimental research domains.

• While advanced analytics tasks over time series data have been gaining lots of attention, lack of such community resources severely limits scientific progress.
• In this paper, we present Exathlon, the first comprehensive public benchmark for explainable anomaly detection over high-dimensional time series data.
• Exathlon has been systematically constructed based on real data traces from repeated executions of large-scale stream processing jobs on an Apache Spark cluster.