Datasets:
The dataset viewer is not available for this subset.
Exception: SplitsNotFoundError
Message: The split names could not be parsed from the dataset config.
Traceback: 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 364, in tsfile.tsfile_reader.TsFileReaderPy.__init__
File "tsfile/tsfile_reader.pyx", line 367, in tsfile.tsfile_reader.TsFileReaderPy.init_reader
File "tsfile/tsfile_py_cpp.pyx", line 789, in tsfile.tsfile_py_cpp.tsfile_reader_new_c
File "tsfile/tsfile_py_cpp.pyx", line 55, in tsfile.tsfile_py_cpp.check_error
tsfile.exceptions.FileOpenError: 28: Failed to open file
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.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.
- Overview
- Schema (TsFile structure)
alarm_events.tsfilecompressor_failures.tsfiledowntime_events.tsfileenvironmental_conditions.tsfileequipment_failure_labels.tsfileequipment_master.tsfilefacility_master.tsfilelubrication_analysis.tsfilemaintenance_work_orders.tsfilepump_failures.tsfilereliability_metrics.tsfileroot_cause_analysis.tsfilesensor_drift.tsfilethermal_profiles.tsfilevalve_failures.tsfilevibration_signals.tsfile
- Conversion notes
- Usage
- Source & license
OIL-038 — Synthetic Equipment Failure Dataset (Sample) (TsFile)
Apache TsFile version of xpertsystems/oil038-sample.
Overview
A schema-identical preview of OIL-038, the XpertSystems.ai synthetic equipment-failure and predictive-maintenance dataset for oil & gas rotating and stationary assets (pumps, valves, compressors). The full product covers ~6,500 facilities across a 3-year horizon with ~6 million telemetry rows. This sample is the generator's demo mode (20 facilities × ~18 assets × 90 days) covering all 16 product tables.
- Tables: 16 TsFile table(s), 115,031 rows in total.
alarm_events: 15,460 rows, 2023-01-01 00:00:00 → 2023-03-31 00:00:00.259000 (UTC)compressor_failures: 92 rows, 2023-01-01 05:00:00 → 2023-03-31 09:00:00 (UTC)downtime_events: 396 rows, 2023-01-01 05:00:00 → 2023-03-31 19:00:00.001000 (UTC)environmental_conditions: 30,510 rows, 2023-01-01 00:00:00 → 2023-03-31 00:00:00.338000 (UTC)equipment_failure_labels: 339 rows, 1970-01-01 00:00:00 → 2023-03-31 19:00:00.001000 (UTC)equipment_master: 339 rows, 2002-09-08 00:00:00 → 2024-12-15 00:00:00 (UTC)facility_master: 20 rows, 1970-01-01 00:00:00 → 1970-01-01 00:00:00.019000 (UTC)lubrication_analysis: 4,407 rows, 2023-01-01 00:00:00 → 2023-03-26 00:00:00.338000 (UTC)maintenance_work_orders: 396 rows, 2023-01-01 10:02:32.650000 → 2023-04-01 01:16:32.170000 (UTC)pump_failures: 129 rows, 2023-01-01 05:00:00 → 2023-03-31 19:00:00.001000 (UTC)reliability_metrics: 339 rows, 1970-01-01 00:00:00 → 1970-01-01 00:00:00.338000 (UTC)root_cause_analysis: 396 rows, 1970-01-01 00:00:00 → 1970-01-01 00:00:00.395000 (UTC)sensor_drift: 1,013 rows, 2024-01-03 00:00:00 → 2025-12-27 00:00:00.002000 (UTC)thermal_profiles: 30,510 rows, 2023-01-01 00:00:00 → 2023-03-31 00:00:00.338000 (UTC)valve_failures: 175 rows, 2023-01-01 12:00:00 → 2023-03-31 00:00:00 (UTC)vibration_signals: 30,510 rows, 2023-01-01 00:00:00 → 2023-03-31 00:00:00.338000 (UTC)
Schema (TsFile structure)
alarm_events.tsfile
- Time (INT64, milliseconds) — the source
timestampcolumn. - TAG: none — the table is stored as a single device.
- FIELD (9):
alarm_id(string),equipment_id(string),facility_id(string),alarm_code(string),severity(string),alarm_value(double),response_delay_minutes(double),acknowledged_flag(int64),alarm_flood_flag(int64)
compressor_failures.tsfile
- Time (INT64, milliseconds) — the source
failure_timestampcolumn. - TAG: none — the table is stored as a single device.
- FIELD (15):
failure_id(string),equipment_id(string),facility_id(string),failure_mode(string),severity_score(double),root_cause(string),detected_by(string),prior_mtbf_hours(double),estimated_mttr_hours(double),unplanned_shutdown_flag(int64),surge_index(double),vibration_mm_s(double),bearing_temp_f(double),discharge_temp_f(double),compression_efficiency_pct(double)
downtime_events.tsfile
- Time (INT64, milliseconds) — the source
downtime_startcolumn. - TAG: none — the table is stored as a single device.
- FIELD (10):
downtime_event_id(string),failure_id(string),equipment_id(string),facility_id(string),shutdown_type(string),downtime_hours(double),production_loss_bbl(double),repair_cost_usd(double),safety_impact_flag(int64),environmental_impact_flag(int64)
environmental_conditions.tsfile
- Time (INT64, milliseconds) — the source
timestampcolumn. - TAG: none — the table is stored as a single device.
- FIELD (7):
equipment_id(string),facility_id(string),ambient_temp_f(double),humidity_pct(double),corrosive_index(double),salt_fog_exposure(int64),h2s_exposure_flag(int64)
equipment_failure_labels.tsfile
- Time (INT64, milliseconds) — the source
last_failure_timestampcolumn. - TAG: none — the table is stored as a single device.
- FIELD (9):
equipment_id(string),facility_id(string),equipment_type(string),failure_probability_30d(double),failure_probability_90d(double),criticality_score(double),risk_rank_score(double),predictive_maintenance_priority(string),recommended_action(string)
equipment_master.tsfile
- Time (INT64, milliseconds) — the source
installed_datecolumn. - TAG: none — the table is stored as a single device.
- FIELD (13):
equipment_id(string),facility_id(string),equipment_type(string),manufacturer_family(string),equipment_age_years(int64),criticality(string),rated_capacity(double),design_margin(double),normal_operating_pressure_psi(double),normal_operating_temp_f(double),maintenance_strategy(string),sensor_coverage_score(double),baseline_mtbf_hours(double)
facility_master.tsfile
- Time (INT64, milliseconds) — synthetic row index over the stable source order; this table has no clock column.
- TAG: none — the table is stored as a single device.
- FIELD (9):
facility_id(string),facility_type(string),region(string),operating_environment(string),facility_age_years(int64),process_complexity_score(double),maintenance_maturity_score(double),corrosive_index(double),safety_criticality(string)
lubrication_analysis.tsfile
- Time (INT64, milliseconds) — the source
sample_timestampcolumn. - TAG: none — the table is stored as a single device.
- FIELD (8):
sample_id(string),equipment_id(string),facility_id(string),oil_quality_score(double),contamination_index(double),water_ppm(double),particle_count_iso_code(string),viscosity_change_pct(double)
maintenance_work_orders.tsfile
- Time (INT64, milliseconds) — the source
created_timestampcolumn. - TAG: none — the table is stored as a single device.
- FIELD (11):
work_order_id(string),failure_id(string),equipment_id(string),facility_id(string),repair_type(string),priority(string),completion_status(string),planned_labor_hours(double),actual_labor_hours(double),spare_parts_delay_hours(double),maintenance_quality_score(double)
pump_failures.tsfile
- Time (INT64, milliseconds) — the source
failure_timestampcolumn. - TAG: none — the table is stored as a single device.
- FIELD (16):
failure_id(string),equipment_id(string),facility_id(string),failure_mode(string),severity_score(double),root_cause(string),detected_by(string),prior_mtbf_hours(double),estimated_mttr_hours(double),unplanned_shutdown_flag(int64),cavitation_score(double),seal_leak_rate_lpm(double),bearing_temp_f(double),pump_efficiency_pct(double),suction_pressure_psi(double),discharge_pressure_psi(double)
reliability_metrics.tsfile
- Time (INT64, milliseconds) — synthetic row index over the stable source order; this table has no clock column.
- TAG: none — the table is stored as a single device.
- FIELD (15):
equipment_id(string),facility_id(string),equipment_type(string),criticality(string),baseline_mtbf_hours(double),equipment_age_years(int64),maintenance_strategy(string),failure_count(int64),downtime_hours(double),observed_mtbf_hours(double),mttr_hours(double),availability(double),reliability_score(double),criticality_weight(double),risk_rank_score(double)
root_cause_analysis.tsfile
- Time (INT64, milliseconds) — synthetic row index over the stable source order; this table has no clock column.
- TAG: none — the table is stored as a single device.
- FIELD (12):
rca_id(string),failure_id(string),equipment_id(string),root_cause(string),contributing_factor_1(string),contributing_factor_2(string),rca_method(string),human_factor_flag(int64),design_factor_flag(int64),process_factor_flag(int64),corrective_action_required(string),rca_confidence_score(double)
sensor_drift.tsfile
- Time (INT64, milliseconds) — the source
last_calibration_datecolumn. - TAG: none — the table is stored as a single device.
- FIELD (7):
sensor_id(string),equipment_id(string),facility_id(string),sensor_type(string),drift_percentage(double),calibration_status(string),signal_quality_score(double)
thermal_profiles.tsfile
- Time (INT64, milliseconds) — the source
timestampcolumn. - TAG: none — the table is stored as a single device.
- FIELD (6):
equipment_id(string),facility_id(string),temperature_f(double),thermal_stress_index(double),cooling_efficiency_pct(double),thermal_cycle_count_30d(int64)
valve_failures.tsfile
- Time (INT64, milliseconds) — the source
failure_timestampcolumn. - TAG: none — the table is stored as a single device.
- FIELD (15):
failure_id(string),equipment_id(string),facility_id(string),failure_mode(string),severity_score(double),root_cause(string),detected_by(string),prior_mtbf_hours(double),estimated_mttr_hours(double),unplanned_shutdown_flag(int64),leakage_rate_scfh(double),actuator_response_ms(double),stiction_score(double),position_error_pct(double),packing_leak_flag(int64)
vibration_signals.tsfile
- Time (INT64, milliseconds) — the source
timestampcolumn. - TAG: none — the table is stored as a single device.
- FIELD (8):
equipment_id(string),facility_id(string),rms_velocity_mm_s(double),fft_peak_hz(double),kurtosis(double),crest_factor(double),health_index(double),load_factor(double)
Conversion notes
- One TsFile per source CSV (16 tables); each table is stored as a single device, so the rig / well / tank / equipment / sensor identifiers stay ordinary FIELDs.
- Time = the table's own clock column as INT64 milliseconds (event timestamps, sample or inspection dates, and daily record dates). The clock columns used here are
created_timestamp,downtime_start,failure_timestamp,installed_date,last_calibration_date,last_failure_timestamp,sample_timestamp,timestamp. - Tables with no clock column (
facility_master,reliability_metrics,root_cause_analysis) use a synthetic row index over their stable source order as Time. - No column is dropped. Rows that share a timestamp are ordered by a 1 ms step in stable source order, so daily tables keep their exact calendar day.
Usage
Read this dataset with the Java SDK. It is written with the
zstdcompressor. The Apache TsFile Java SDK reads every compressor, but the Python SDK (pip install tsfile) implements onlyUNCOMPRESSED,SNAPPY,GZIPandLZ4; opening this file with it yields no rows.
Read a converted file with the Apache TsFile Java SDK (org.apache.tsfile:tsfile):
import org.apache.tsfile.file.metadata.IDeviceID;
import org.apache.tsfile.read.TsFileReader;
import org.apache.tsfile.read.TsFileSequenceReader;
import org.apache.tsfile.read.common.Path;
import org.apache.tsfile.read.expression.QueryExpression;
import org.apache.tsfile.read.query.dataset.QueryDataSet;
import org.apache.tsfile.write.schema.MeasurementSchema;
import java.util.ArrayList;
import java.util.List;
String path = "alarm_events.tsfile";
try (TsFileSequenceReader sequenceReader = new TsFileSequenceReader(path);
TsFileReader reader = new TsFileReader(sequenceReader)) {
// Devices are enumerated as IDeviceID objects. Tables with TAG columns
// have multi-segment device ids that cannot be rebuilt from their string
// form, so always use getAllDevices() rather than getAllDeviceIds().
for (IDeviceID device : sequenceReader.getAllDevices()) {
List<Path> paths = new ArrayList<>();
for (MeasurementSchema schema : reader.getMeasurement(device)) {
String name = schema.getMeasurementName();
if (name != null && !name.isEmpty() && !name.equalsIgnoreCase("Time")) {
paths.add(new Path(device, name, true));
}
}
QueryDataSet dataSet = reader.query(QueryExpression.create(paths, null));
while (dataSet.hasNext()) {
System.out.println(dataSet.next());
}
}
}
Source & license
- Original dataset:
xpertsystems/oil038-sample - Source card title: OIL-038 — Synthetic Equipment Failure Dataset (Sample)
- License: cc-by-nc-4.0 (as declared by the original dataset).
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