TPC-H Q5 — Local Supplier Volume

TPC-H benchmark · all TPC-H queries

Revenue from orders in same nation within region

Representative SQL

Rendered for DataFusion with default parameters.

SELECT
  n_name,
  SUM(l_extendedprice * (
    1 - l_discount
  )) AS revenue
FROM customer, orders, lineitem, supplier, nation, region
WHERE
  c_custkey = o_custkey
  AND l_orderkey = o_orderkey
  AND l_suppkey = s_suppkey
  AND c_nationkey = s_nationkey
  AND s_nationkey = n_nationkey
  AND n_regionkey = r_regionkey
  AND r_name = 'ASIA'
  AND o_orderdate >= CAST('1994-01-01' AS DATE)
  AND o_orderdate < CAST('1994-01-01' AS DATE) + INTERVAL '1 YEAR'
GROUP BY
  n_name
ORDER BY
  revenue DESC

Representative DataFrame

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

def q5_expression_impl(ctx: DataFrameContext) -> Any:
    customer = ctx.get_table("customer")
    orders = ctx.get_table("orders")
    lineitem = ctx.get_table("lineitem")
    supplier = ctx.get_table("supplier")
    nation = ctx.get_table("nation")
    region = ctx.get_table("region")
    col = ctx.col
    lit = ctx.lit

    params = get_tpch_parameters(5)
    region_name = params["region_name"]
    start_date = params["start_date"]
    end_date = params["end_date"]

    return (
        region.filter(col("r_name") == lit(region_name))
        .join(nation, left_on="r_regionkey", right_on="n_regionkey")
        .join(customer, left_on="n_nationkey", right_on="c_nationkey")
        .join(orders, left_on="c_custkey", right_on="o_custkey")
        .filter((col("o_orderdate") >= lit(start_date)) & (col("o_orderdate") < lit(end_date)))
        .join(lineitem, left_on="o_orderkey", right_on="l_orderkey")
        .join(
            supplier,
            left_on=["l_suppkey", "n_nationkey"],
            right_on=["s_suppkey", "s_nationkey"],
        )
        .group_by("n_name")
        .agg((col("l_extendedprice") * (lit(1) - col("l_discount"))).sum().alias("revenue"))
        .sort("revenue", descending=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 TPCH

bench = TPCH(scale_factor=0.01)            # your scale factor
queries = bench.get_queries(dialect="datafusion")   # your platform's dialect; drop dialect= for native SQL
print(queries['5'])

Parameter substitution for this benchmark is seed-driven; pass a seed for a specific stream’s parameters:

print(bench.get_query(5, scale_factor=0.01, seed=42, dialect="datafusion"))

For the DataFrame form:

from benchbox.core.query_catalog import get_dataframe_render

print(get_dataframe_render('tpch', '5', family="expression").source)  # or family="pandas"

Source

Query text: benchbox/_binaries/tpc-h/templates/queries/5.sql