TPC-H Q6 — Forecasting Revenue Change
TPC-H benchmark · all TPC-H queries
Revenue increase from eliminating discounts
Representative SQL
Rendered for DataFusion with default parameters.
SELECT SUM(l_extendedprice * l_discount) AS revenueFROM lineitemWHERE l_shipdate >= CAST('1994-01-01' AS DATE) AND l_shipdate < CAST('1994-01-01' AS DATE) + INTERVAL '1 YEAR' AND l_discount BETWEEN 0.06 - 0.01 AND 0.06 + 0.01 AND l_quantity < 24Representative DataFrame
Expression family (Polars, PySpark, DataFusion), default parameters.
def q6_expression_impl(ctx: DataFrameContext) -> Any: lineitem = ctx.get_table("lineitem") col = ctx.col lit = ctx.lit
params = get_tpch_parameters(6) start_date = params["start_date"] end_date = params["end_date"] discount_low = params["discount_low"] discount_high = params["discount_high"] quantity_limit = params["quantity_limit"]
return ( lineitem.filter( (col("l_shipdate") >= lit(start_date)) & (col("l_shipdate") < lit(end_date)) & (col("l_discount") >= lit(discount_low)) & (col("l_discount") <= lit(discount_high)) & (col("l_quantity") < lit(quantity_limit)) ) .select((col("l_extendedprice") * col("l_discount")).alias("revenue")) .sum() )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 factorqueries = bench.get_queries(dialect="datafusion") # your platform's dialect; drop dialect= for native SQLprint(queries['6'])Parameter substitution for this benchmark is seed-driven; pass a seed for a specific stream’s parameters:
print(bench.get_query(6, 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', '6', family="expression").source) # or family="pandas"Source
Query text: benchbox/_binaries/tpc-h/templates/queries/6.sql