README.md

metadata

license: apache-2.0
tags:
  - forecasting
  - benchmark
  - gifteval
  - tsfile
  - modality:timeseries
task_categories:
  - time-series-forecasting
pretty_name: bitbrains_fast_storage (GIFT-Eval, TsFile)
modality:
  - timeseries
size_categories:
  - 1K<n<10K

bitbrains_fast_storage (TsFile)

Apache TsFile version of the bitbrains_fast_storage subset of GIFT-Eval.

Overview

GIFT-Eval is a benchmark for general time-series forecasting, covering 23 datasets (≈144,000 series and 177M data points) across seven domains, ten frequencies, and a range of forecast horizons. This repository contains a single subset of that benchmark.

bitbrains_fast_storage — VM resource-usage traces from the Bitbrains fast-storage data center.

The .tsfile files are organized by the original GIFT-Eval frequency under data/:

• data/5T/: 11 .tsfile files
• data/H/: 1 .tsfile files

Schema (TsFile structure)

• Time (INT64, milliseconds) — the timestamp of each observation.
• Each series is stored as a TsFile device; per-series identifiers from GIFT-Eval are carried as TAG columns, and the observed values are FIELD columns.

Usage

Read the .tsfile files with the Apache TsFile Java or Python SDK.

Source & license

• Original dataset: Salesforce/GiftEval — subset bitbrains_fast_storage
• Paper: GIFT-Eval (arXiv:2410.10393)
• Code: https://github.com/SalesforceAIResearch/gift-eval
• License: apache-2.0

If you use this data, please cite GIFT-Eval:

@article{aksu2024giftevalbenchmarkgeneraltime,
  title={GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluation},
  author={Taha Aksu and Gerald Woo and Juncheng Liu and Xu Liu and Chenghao Liu and Silvio Savarese and Caiming Xiong and Doyen Sahoo},
  journal={arXiv preprint arXiv:2410.10393},
  year={2024}
}