Flight Data — Hub Airport Connectivity

Flight Data benchmark · all Flight Data queries

Number of unique destinations served from each origin airport

Representative SQL

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

SELECT
  f.origin,
  ap.name AS airport_name,
  ap.city,
  ap.state,
  COUNT(DISTINCT f.dest) AS unique_destinations,
  COUNT(DISTINCT f.reporting_airline) AS serving_carriers,
  COUNT(*) AS total_departures,
  ROUND(AVG(f.dep_delay), 2) AS avg_dep_delay
FROM flights AS f
LEFT JOIN airports AS ap
  ON f.origin = ap.code
WHERE
  f.cancelled = 0 AND f.flight_date >= '2021-08-01' AND f.flight_date < '2025-01-01'
GROUP BY
  f.origin,
  ap.name,
  ap.city,
  ap.state
ORDER BY
  total_departures DESC,
  f.origin
LIMIT 30

Representative DataFrame

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

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

    ap = airports.select(
        col("code").alias("ap_code"),
        col("name").alias("airport_name"),
        col("city"),
        col("state"),
    )

    return (
        flights.join(ap, left_on="origin", right_on="ap_code", how="left")
        .filter(_date_condition(col, lit, lambda col, lit: col("cancelled") == lit(0)))
        .group_by("origin", "airport_name", "city", "state")
        .agg(
            col("dest").n_unique().alias("unique_destinations"),
            col("reporting_airline").n_unique().alias("serving_carriers"),
            col("flight_id").count().alias("total_departures"),
            col("dep_delay").mean().alias("_avg_dep"),
        )
        .with_columns(_round_half_away(ctx, col("_avg_dep"), 2).alias("avg_dep_delay"))
        .select(
            "origin",
            "airport_name",
            "city",
            "state",
            "unique_destinations",
            "serving_carriers",
            "total_departures",
            "avg_dep_delay",
        )
        .sort(["total_departures", "origin"], descending=[True, False])
        .limit(30)
    )

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()['hub-connectivity'])

For the DataFrame form:

from benchbox.core.query_catalog import get_dataframe_render

print(get_dataframe_render('flightdata', 'hub-connectivity', family="expression").source)  # or family="pandas"

Source

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