---
pretty_name: BGL
dataset_name: logfit-project/BGL
task_categories:
- text-classification
language:
- en
size_categories:
- 1M<n<10M
annotations_creators:
- logfit-project
license: other
---

# Dataset Card for logfit-project/BGL

## Dataset Summary
The BlueGene/L (BGL) dataset contains console logs emitted by a 131,072-processor BlueGene/L supercomputer
operated at Lawrence Livermore National Laboratory. Each line records hardware or software events tagged
with an alert category, enabling downstream research on alert detection, prediction, and log analytics.

## Supported Tasks and Leaderboards
- anomaly-detection: binary or multi-class classification of alert categories.
- log-parsing: template discovery and sequence modeling for high-performance computing (HPC) systems.

## Dataset Structure
- `label`: Alert category tag (`-` indicates a non-alert informational message).
- `timestamp`: Unix epoch timestamp associated with the log event.
- `date`: Calendar date formatted as `YYYY.MM.DD`.
- `node`: Hardware node identifier that emitted the log line.
- `time`: Precise timestamp including microseconds (`YYYY-MM-DD-HH.MM.SS.xxxxxx`).
- `node_repeat`: Repeated node identifier found in the structured dataset.
- `type`: High-level event type (e.g., `RAS`).
- `component`: Subsystem reporting the log (e.g., `KERNEL`).
- `level`: Severity level accompanying the event.
- `content`: Verbose description of the underlying event.
- `anomaly`: Binary indicator (`1` for alert labels, `0` for non-alert `-`).

## Source Data
- **Homepage:** https://github.com/logpai/loghub/tree/master/BGL
- **Original Maintainers:** The LogPAI team (https://logpai.com/).
- **Additional Context:** https://www.usenix.org/cfdr-data#hpc4

## Dataset Creation
The raw BlueGene/L logs are parsed with a deterministic regular expression to reproduce the schema
published in `BGL_2k.log_structured.csv`. The transformation streams lines sequentially so the full corpus
can be processed without loading the entire file into memory.

## Uses
Suitable for supervised alert detection, failure prediction, anomaly detection, sequence modeling of HPC
logs, and benchmarking log parsing techniques.

## Citation
- Adam J. Oliner, Jon Stearley. "What Supercomputers Say: A Study of Five System Logs", DSN 2007.
- Jieming Zhu, Shilin He, Pinjia He, Jinyang Liu, Michael R. Lyu. "Loghub: A Large Collection of System Log
  Datasets for AI-driven Log Analytics", ISSRE 2023.

## Dataset Statistics
- Number of log lines: 4747963