TPC-H Skew Q12 — Shipping Modes and Order Priority

TPC-H Skew benchmark · all TPC-H Skew queries

Effect of shipping modes on order priority

Representative SQL

Rendered for DataFusion with default parameters.

SELECT
  l_shipmode,
  SUM(
    CASE
      WHEN o_orderpriority = '1-URGENT' OR o_orderpriority = '2-HIGH'
      THEN 1
      ELSE 0
    END
  ) AS high_line_count,
  SUM(
    CASE
      WHEN o_orderpriority <> '1-URGENT' AND o_orderpriority <> '2-HIGH'
      THEN 1
      ELSE 0
    END
  ) AS low_line_count
FROM orders, lineitem
WHERE
  o_orderkey = l_orderkey
  AND l_shipmode IN ('MAIL', 'SHIP')
  AND l_commitdate < l_receiptdate
  AND l_shipdate < l_commitdate
  AND l_receiptdate >= CAST('1994-01-01' AS DATE)
  AND l_receiptdate < CAST('1994-01-01' AS DATE) + INTERVAL '1 YEAR'
GROUP BY
  l_shipmode
ORDER BY
  l_shipmode

Representative DataFrame

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

def q12_expression_impl(ctx: DataFrameContext) -> Any:
    orders = ctx.get_table("orders")
    lineitem = ctx.get_table("lineitem")
    col = ctx.col
    lit = ctx.lit

    params = get_tpch_parameters(12)
    shipmode1 = params["shipmode1"]
    shipmode2 = params["shipmode2"]
    start_date = params["start_date"]
    end_date = params["end_date"]

    return (
        lineitem.filter(
            (col("l_shipmode").is_in([shipmode1, shipmode2]))
            & (col("l_commitdate") < col("l_receiptdate"))
            & (col("l_shipdate") < col("l_commitdate"))
            & (col("l_receiptdate") >= lit(start_date))
            & (col("l_receiptdate") < lit(end_date))
        )
        .join(orders, left_on="l_orderkey", right_on="o_orderkey")
        .group_by("l_shipmode")
        .agg(
            col("o_orderpriority")
            .filter(col("o_orderpriority").is_in(["1-URGENT", "2-HIGH"]))
            .count()
            .alias("high_line_count"),
            col("o_orderpriority")
            .filter(~col("o_orderpriority").is_in(["1-URGENT", "2-HIGH"]))
            .count()
            .alias("low_line_count"),
        )
        .sort("l_shipmode")
    )

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 TPCHSkew

bench = TPCHSkew(scale_factor=0.01)            # your scale factor
queries = bench.get_queries(dialect="datafusion")   # your platform's dialect; drop dialect= for native SQL
print(queries['12'])

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

print(bench.get_query(12, 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_skew', '12', family="expression").source)  # or family="pandas"

Source

Query text: benchbox/_binaries/tpc-h/templates/queries/12.sql