TPC-DS Q92 — Web Sales Discount

TPC-DS benchmark · all TPC-DS queries

Finds web items sold with excess discount

Representative SQL

Rendered for DataFusion with default parameters.

SELECT
  SUM(ws_ext_discount_amt) AS "Excess Discount Amount"
FROM web_sales, item, date_dim
WHERE
  i_manufact_id = 269
  AND i_item_sk = ws_item_sk
  AND d_date BETWEEN '1998-03-18' AND (
    CAST('1998-03-18' AS DATE) + INTERVAL '90 DAY'
  )
  AND d_date_sk = ws_sold_date_sk
  AND ws_ext_discount_amt > (
    SELECT
      1.3 * AVG(ws_ext_discount_amt)
    FROM web_sales, date_dim
    WHERE
      ws_item_sk = i_item_sk
      AND d_date BETWEEN '1998-03-18' AND (
        CAST('1998-03-18' AS DATE) + INTERVAL '90 DAY'
      )
      AND d_date_sk = ws_sold_date_sk
  )
ORDER BY
  SUM(ws_ext_discount_amt)
LIMIT 100

Representative DataFrame

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

def impl(ctx: DataFrameContext) -> Any:
        return helper(ctx, query_id, *helper_args)

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 TPCDS

bench = TPCDS(scale_factor=1.0)            # your scale factor
queries = bench.get_queries(dialect="datafusion")   # your platform's dialect; drop dialect= for native SQL
print(queries['92'])

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

print(bench.get_query(92, scale_factor=1.0, seed=42, dialect="datafusion"))

For the DataFrame form:

from benchbox.core.query_catalog import get_dataframe_render

print(get_dataframe_render('tpcds', '92', family="expression").source)  # or family="pandas"

Source

Query text: _sources/tpc-ds/query_templates/query92.tpl