THULab/rescast_100k_sharded_small_sample

RESCAST-100k-sharded-small-sample (TsFile)

Apache TsFile version of Jainam03/RESCAST-100k-sharded-small-sample, one of the processed real residential building-energy corpora used with RESCAST-100k.

Overview

A small subset of the processed sharded RESCAST-100k residential building time-series dataset. Each building is stored as one row group of a shard parquet file and identified by building_id.

• Buildings: 1,024
• Rows: 35,880,960
• Resolution: 15 minutes
• Time span: Calendar year 2007 (2007-01-01 00:15 to 2008-01-01 00:00) for every building in this subset.
• TsFile layout: The converted corpus is stored as 57 TsFile shard(s) (rescast_100k_sharded_small_sample_000.tsfile ... rescast_100k_sharded_small_sample_056.tsfile), all under the TsFile table rescast_100k_sharded_small_sample.

Each row is one timestamped reading for one building. The TsFile table name is rescast_100k_sharded_small_sample and the building_id TAG identifies the building.

Schema (TsFile structure)

• Time (INT64, milliseconds) — timestamp parsed from the source Time column (UTC for timezone-aware sources).

• building_id (TAG) — building identifier. For the per-building repositories it is the numeric N from the source file name <prefix>_home_N.parquet; for the sharded sample it is the source building_id column.

• Measurements (FIELD):

• fuel_use_electricity_total (DOUBLE) — total electricity load, kWh

• end_use_electricity_heating (DOUBLE) — electricity end use for heating, kWh

• end_use_electricity_cooling (DOUBLE) — electricity end use for cooling, kWh

• temperature_conditioned_space (DOUBLE) — indoor conditioned-space temperature, degrees F

• temperature_heating_setpoint (DOUBLE) — heating setpoint, degrees F

• temperature_cooling_setpoint (DOUBLE) — cooling setpoint, degrees F

• weather_drybulb_temperature (DOUBLE) — outdoor dry-bulb temperature, degrees F

• weather_wetbulb_temperature (DOUBLE) — outdoor wet-bulb temperature, degrees F

• weather_relative_humidity (DOUBLE) — outdoor relative humidity, percent

• weather_wind_speed (DOUBLE) — outdoor wind speed, m/s

• weather_diffuse_solar_radiation (DOUBLE) — diffuse solar radiation

• weather_direct_solar_radiation (DOUBLE) — direct solar radiation

Query one building with a predicate such as WHERE building_id = 1. The source column names contain spaces (and : for the sharded sample); they are written as TsFile-safe identifiers by replacing runs of non-alphanumeric characters with _ and lower-casing, e.g. Indoor Temp -> indoor_temp and Fuel Use: Electricity: Total -> fuel_use_electricity_total.

Static building features

The source repositories also contain house_features_*.parquet (static per-building metadata such as weather location, geometry, HVAC type and insulation). That table is not a time series and is not included in this TsFile repository; it remains in the original dataset. For the sharded sample, the static manifest.parquet, house_features_rescast-100k.parquet and results-Baseline-100k.csv files are likewise not included, and the redundant building_id_str column (a string copy of building_id) is not carried into the TsFile.

Usage

Install the Apache TsFile Python SDK (pip install tsfile) and read a converted file:

from pathlib import Path
from tsfile import TsFileReader

path = Path("rescast_100k_sharded_small_sample_000.tsfile")
with TsFileReader(str(path)) as reader:
    schemas = reader.get_all_table_schemas()
    print("tables:", list(schemas))
    table_name = next(iter(schemas))
    table = schemas[table_name]
    columns = [column.get_column_name() for column in table.get_columns()]
    print("columns:", columns)
    field_names = [
        column.get_column_name()
        for column in table.get_columns()
        if column.get_column_name() not in {"Time", "time"}
    ]
    if field_names:
        with reader.query_table(table_name, field_names[:3], batch_size=1024) as result:
            batch = result.read_arrow_batch()
            if batch is not None:
                print(batch.to_pandas().head())

Source & license

• Original dataset: Jainam03/RESCAST-100k-sharded-small-sample
• Author / publisher: Jainam03 (processed RESCAST-100k release)
• Paper: This subset is a small sample of Jainam03/RESCAST-100k.
• License: cc-by-4.0 (processed release; check the original source terms before redistribution)