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Datasets:
VGalaxies666
/
boomlet

Tasks:
Time Series Forecasting
Sub-tasks:
univariate-time-series-forecasting
multivariate-time-series-forecasting
Size:
100K<n<1M
ArXiv:
Tags:
time-series
forecasting
benchmark
fev
tsfile
apache-tsfile
License:
Dataset card Files
xet
 Community
Dataset Viewer
The dataset viewer is not available for this subset.
Cannot get the split names for the config 'default' of the dataset.
Exception:    SplitsNotFoundError
Message:      The split names could not be parsed from the dataset config.
Traceback:    Traceback (most recent call last):
                File "tsfile/tsfile_py_cpp.pyx", line 567, in tsfile.tsfile_py_cpp.tsfile_reader_new_c
              tsfile.exceptions.FileOpenError: 28: 
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
                  for split_generator in builder._split_generators(
                                         ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      StreamingDownloadManager(base_path=builder.base_path, download_config=download_config)
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/tsfile/tsfile.py", line 271, in _split_generators
                  scan = self._scan_metadata(all_files)
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/tsfile/tsfile.py", line 318, in _scan_metadata
                  with self._open_reader(file) as reader:
                       ~~~~~~~~~~~~~~~~~^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/tsfile/tsfile.py", line 742, in _open_reader
                  return TsFileReader(file)
                File "tsfile/tsfile_reader.pyx", line 323, in tsfile.tsfile_reader.TsFileReaderPy.__init__
              SystemError: <class '_weakrefset.WeakSet'> returned a result with an exception set
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 66, in compute_split_names_from_streaming_response
                  for split in get_dataset_split_names(
                               ~~~~~~~~~~~~~~~~~~~~~~~^
                      path=dataset,
                      ^^^^^^^^^^^^^
                      config_name=config,
                      ^^^^^^^^^^^^^^^^^^^
                      token=hf_token,
                      ^^^^^^^^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
                  info = get_dataset_config_info(
                      path,
                  ...<6 lines>...
                      **config_kwargs,
                  )
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
                  raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
              datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

boomlet (TsFile format)

This repository contains time-series forecasting data stored in Apache TsFile format.

Summary

  • FEV subset: boomlet
  • Unified source collection: autogluon/fev_datasets
  • Original source: https://huggingface.co/datasets/Datadog/BOOM
  • Paper / citation: [5]
  • Series: 1
  • Modalities: Time-series
  • TsFile rows (flattened observations): 10,139,745
  • Frequencies: 1062, 1209, 1225, 1230, 1282, 1487, 1631, 1676, 1855, 1975, 2187, 285, 619, 772, 963
  • TsFile files: 15
  • Time precision: milliseconds (INT64).

Licensing and citation requirements follow the original source. This repository does not claim ownership of the original data.

Dataset Statistics

Frequency Series Median series length TsFile rows (observations) Dynamic columns Static columns Data files
1062 1 16,384 344,064 21 6 1062/1062.tsfile
1209 1 16,384 868,352 53 6 1209/1209.tsfile
1225 1 16,384 802,816 49 6 1225/1225.tsfile
1230 1 16,384 376,832 23 6 1230/1230.tsfile
1282 1 16,384 573,440 35 6 1282/1282.tsfile
1487 1 16,384 884,736 54 6 1487/1487.tsfile
1631 1 10,463 418,520 40 6 1631/1631.tsfile
1676 1 10,463 1,046,300 100 6 1676/1676.tsfile
1855 1 5,231 272,012 52 6 1855/1855.tsfile
1975 1 5,231 392,325 75 6 1975/1975.tsfile
2187 1 5,231 523,100 100 6 2187/2187.tsfile
285 1 16,384 1,228,800 75 6 285/285.tsfile
619 1 16,384 851,968 52 6 619/619.tsfile
772 1 16,384 1,097,728 67 6 772/772.tsfile
963 1 16,384 458,752 28 6 963/963.tsfile

Files

The Hugging Face dataset card YAML points configs.data_files to all *.tsfile files in this repository.

  • 1062/1062.tsfile
  • 1209/1209.tsfile
  • 1225/1225.tsfile
  • 1230/1230.tsfile
  • 1282/1282.tsfile
  • 1487/1487.tsfile
  • 1631/1631.tsfile
  • 1676/1676.tsfile
  • 1855/1855.tsfile
  • 1975/1975.tsfile
  • 2187/2187.tsfile
  • 285/285.tsfile
  • 619/619.tsfile
  • 772/772.tsfile
  • 963/963.tsfile

TsFile Storage Model

  • Each original series (id) is stored as one TsFile device.
  • Static covariate columns are stored as TAG columns: type, Application_Usage, Infrastructure, Database, Networking, Security.
  • Time-varying targets and dynamic covariates are stored as FIELD measurements.
  • Source timestamp values are mapped to the TsFile Time column as millisecond timestamps.
  • Table name(s): boomlet_1062, boomlet_1209, boomlet_1225, boomlet_1230, boomlet_1282, boomlet_1487, boomlet_1631, boomlet_1676, boomlet_1855, boomlet_1975, boomlet_2187, boomlet_285, boomlet_619, boomlet_772, boomlet_963.

Column Schema

Column Role TsFile type
Time Time column INT64
id TAG (device dimension) STRING
type TAG (device dimension) STRING
Application_Usage TAG (device dimension) DOUBLE
Infrastructure TAG (device dimension) DOUBLE
Database TAG (device dimension) DOUBLE
Networking TAG (device dimension) DOUBLE
Security TAG (device dimension) DOUBLE
target_0 FIELD (measurement) FLOAT
target_1 FIELD (measurement) FLOAT
target_2 FIELD (measurement) FLOAT
target_3 FIELD (measurement) FLOAT
target_4 FIELD (measurement) FLOAT
target_5 FIELD (measurement) FLOAT
target_6 FIELD (measurement) FLOAT
target_7 FIELD (measurement) FLOAT
target_8 FIELD (measurement) FLOAT
target_9 FIELD (measurement) FLOAT
target_10 FIELD (measurement) FLOAT
target_11 FIELD (measurement) FLOAT
target_12 FIELD (measurement) FLOAT
target_13 FIELD (measurement) FLOAT
target_14 FIELD (measurement) FLOAT
target_15 FIELD (measurement) FLOAT
target_16 FIELD (measurement) FLOAT
target_17 FIELD (measurement) FLOAT
target_18 FIELD (measurement) FLOAT
target_19 FIELD (measurement) FLOAT
target_20 FIELD (measurement) FLOAT

Note: 15 original id values contained invalid identifier characters and were normalized to valid device names, for example 1062→_1062, 1209→_1209, 1225→_1225.

Conversion Notes

  • The source FEV format stores each time series as one nested row containing id, timestamp[], and target or covariate arrays.
  • The TsFile conversion flattens those nested arrays into long rows. Therefore, the TsFile rows values above correspond to the number of timestamped observations after flattening.
  • TAG columns identify the device and static metadata. FIELD columns contain values that change over time.
  • Large logical tables may be split into multiple .tsfile shards such as <name>_1.tsfile, <name>_2.tsfile, and so on. Shards listed for the same frequency belong to the same logical table.

Reading Example 

from tsfile import TsFileReader

reader = TsFileReader("1062/1062.tsfile")
schemas = reader.get_all_table_schemas()
# Table name(s): boomlet_1062, boomlet_1209, boomlet_1225, boomlet_1230, boomlet_1282, boomlet_1487, boomlet_1631, boomlet_1676, boomlet_1855, boomlet_1975, boomlet_2187, boomlet_285, boomlet_619, boomlet_772, boomlet_963
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Paper for VGalaxies666/boomlet