---
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](https://huggingface.co/datasets/Salesforce/GiftEval).

## 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`](https://huggingface.co/datasets/Salesforce/GiftEval) — subset `bitbrains_fast_storage`
- Paper: [GIFT-Eval (arXiv:2410.10393)](https://arxiv.org/abs/2410.10393)
- Code: https://github.com/SalesforceAIResearch/gift-eval
- License: apache-2.0

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

```bibtex
@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}
}
```