Datasets:

THULab
/

africa-synth-telecom-edge-computing-load-data-nigeria

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 68, 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.

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Nigeria Telecom Edge Computing Load Data (TsFile)

This dataset is an Apache TsFile conversion of electricsheepafrica/africa-synth-telecom-edge-computing-load-data-nigeria, a synthetic Nigerian telecom dataset describing processing demand and resource utilization across edge nodes.

Source Dataset

Original dataset: electricsheepafrica/africa-synth-telecom-edge-computing-load-data-nigeria
Author: electricsheepafrica
Category: Emerging and Advanced
Original formats: CSV and Parquet
Rows: 250,000
Columns: 14
Date generated: 2025-10-05
Modalities: Time-series / tabular edge-computing load metrics
License metadata: gpl as listed in the original Hugging Face dataset card metadata. The original README body also contains a "MIT License" note.

The source dataset card describes Nigerian telecom context including major Nigerian cities, operators such as MTN, Airtel, Glo, and 9mobile, West Africa Time (WAT, UTC+1), and 2G/3G/4G/5G network types.

Converted TsFile Data

TsFile path: africa_telecom_edge_computing_load_data_nigeria.tsfile
Table name: edge_computing_load_data
Conversion mode: custom Python staging + Java TsFile Parquet import tool, schema mode
Time precision: milliseconds (ms)
Rows converted: 250,000
Dropped rows: none
Source file used: edge_computing_load_data.parquet

Time, TAG, and FIELD Mapping

Source column	TsFile role	Type	Notes
`timestamp`	Time	INT64 timestamp	Original datetime column converted to TsFile `Time` in milliseconds.
`edge_node_id`	TAG	STRING	Edge node identifier.
`city`	TAG	STRING	Nigerian city.
`application`	TAG	STRING	Edge application/workload category.
`operator`	TAG	STRING	Telecom operator.
`load_status`	TAG	STRING	Source load status category.
`event_rank`	TAG	INT64	Generated duplicate-order tag for concurrent same-device same-minute rows.
`cpu_utilization_percent`	FIELD	DOUBLE	CPU utilization percentage.
`memory_utilization_percent`	FIELD	DOUBLE	Memory utilization percentage.
`storage_utilization_percent`	FIELD	DOUBLE	Storage utilization percentage.
`network_throughput_gbps`	FIELD	DOUBLE	Network throughput in Gbps.
`active_sessions`	FIELD	INT64	Active session count.
`requests_per_second`	FIELD	INT64	Request rate.
`avg_response_time_ms`	FIELD	DOUBLE	Average response time in milliseconds.
`cache_hit_ratio_percent`	FIELD	DOUBLE	Cache hit ratio percentage; null values are preserved.

edge_node_id, city, application, operator, and load_status describe an edge-node workload/device dimension. The generated event_rank TAG distinguishes 154 concurrent records that share the same base TAG values and minute timestamp, preserving all source rows without shifting the original time. The source timestamp column is represented as TsFile Time and is not duplicated as a FIELD.

Minimal Read Example

from tsfile import TsFileReader

path = "africa_telecom_edge_computing_load_data_nigeria.tsfile"
with TsFileReader(path) as reader:
    schemas = reader.get_all_table_schemas()
    print(schemas.keys())  # includes: edge_computing_load_data

Citation

Nigerian Telecom Datasets - Edge Computing Load Data
Generated: 2025-10-05
Category: Emerging and Advanced
Rows: 250,000
Converted to Apache TsFile from the Hugging Face dataset:
electricsheepafrica/africa-synth-telecom-edge-computing-load-data-nigeria

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Total file size:

22.4 MB