Flight Data — On-Time Rate by Carrier

Flight Data benchmark · all Flight Data queries

On-time arrival percentage by airline carrier

Representative SQL

Rendered in the benchmark’s native SQL with default parameters (no dialect translation available).

SELECT
  f.reporting_airline,
  a.name AS airline_name,
  COUNT(*) AS total_flights,
  SUM(CASE WHEN f.arr_delay <= 15 THEN 1 ELSE 0 END) AS ontime_flights,
  ROUND(100.0 * SUM(CASE WHEN f.arr_delay <= 15 THEN 1 ELSE 0 END) / COUNT(*), 2) AS ontime_pct,
  ROUND(AVG(CASE WHEN f.arr_delay > 0 THEN f.arr_delay END), 2) AS avg_delay_when_late
FROM flights AS f
LEFT JOIN airlines AS a
  ON f.reporting_airline = a.code
WHERE
  f.cancelled = 0 AND f.flight_date >= '2021-08-01' AND f.flight_date < '2025-01-01'
GROUP BY
  f.reporting_airline,
  a.name
ORDER BY
  ontime_pct DESC,
  f.reporting_airline

Representative DataFrame

Expression family (Polars, PySpark, DataFusion), default parameters.

def ontime_by_carrier_expression_impl(ctx: DataFrameContext) -> Any:
    flights = ctx.get_table("flights")
    col, lit = ctx.col, ctx.lit

    return (
        flights.join(_airline_names(ctx), left_on="reporting_airline", right_on="a_code", how="left")
        .filter(_date_condition(col, lit, lambda col, lit: col("cancelled") == lit(0)))
        .with_columns(
            (col("arr_delay") <= lit(15)).cast(int).alias("_ontime"),
            ctx.when(col("arr_delay") > lit(0)).then(col("arr_delay")).otherwise(lit(None)).alias("_late_delay"),
        )
        .group_by("reporting_airline", "airline_name")
        .agg(
            col("flight_id").count().alias("total_flights"),
            col("_ontime").sum().alias("ontime_flights"),
            col("_late_delay").mean().alias("_avg_late"),
        )
        .with_columns(
            _round_half_away(ctx, lit(100.0) * col("ontime_flights") / col("total_flights"), 2).alias("ontime_pct"),
            _round_half_away(ctx, col("_avg_late"), 2).alias("avg_delay_when_late"),
        )
        .select(
            "reporting_airline",
            "airline_name",
            "total_flights",
            "ontime_flights",
            "ontime_pct",
            "avg_delay_when_late",
        )
        .sort(["ontime_pct", "reporting_airline"], descending=[True, False], nulls_last=True)
    )

Get the exact query for your run

The blocks above are representative. To get the precise statement a specific platform runs at a specific scale, substitute your own values:

from benchbox import FlightData

bench = FlightData(scale_factor=1.0)            # your scale factor
print(bench.get_queries()['ontime-by-carrier'])

For the DataFrame form:

from benchbox.core.query_catalog import get_dataframe_render

print(get_dataframe_render('flightdata', 'ontime-by-carrier', family="expression").source)  # or family="pandas"

Source

Query text: benchbox/core/flightdata/queries.py