TPC-DS-OBT Q16 — obt_store_summary

TPC-DS-OBT benchmark · all TPC-DS-OBT queries

Store-channel sales, revenue, and profit

Representative SQL

Rendered for DataFusion with default parameters.

SELECT
  COUNT(DISTINCT sale_id) AS "order count",
  SUM(ext_ship_cost) AS "total shipping cost",
  SUM(net_profit) AS "total net profit"
FROM tpcds_sales_returns_obt AS obt
WHERE
  (
    ship_date_d_date BETWEEN '1999-2-01' AND (
      CAST('1999-2-01' AS DATE) + INTERVAL '60 DAY'
    )
    AND obt.ship_date_sk = ship_date_d_date_sk
    AND obt.ship_addr_sk = ship_addr_ca_address_sk
    AND ship_addr_ca_state = '0'
    AND obt.call_center_sk = call_center_cc_call_center_sk
    AND call_center_cc_county IN ('0', '0', '0', '0', '0')
    AND EXISTS(
      SELECT
        *
      FROM tpcds_sales_returns_obt AS obt
      WHERE
        (
          obt.sale_id = obt.sale_id AND obt.warehouse_sk <> obt.warehouse_sk
        )
        AND channel = 'catalog'
    )
    AND NOT EXISTS(
      SELECT
        *
      FROM tpcds_sales_returns_obt AS obt
      WHERE
        obt.sale_id = obt.sale_id AND obt.has_return = 'Y' AND obt.channel = 'catalog'
    )
  )
  AND channel = 'catalog'
ORDER BY
  COUNT(DISTINCT sale_id)
LIMIT 100

Representative DataFrame

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

def impl(ctx: DataFrameContext) -> Any:
        table = ctx.get_table(OBT_TABLE)
        for column, op, value in spec.filters:
            table = table.filter(_FILTER_OPS[op](ctx.col(column), ctx.lit(value)))
        aggregates = [getattr(ctx.col(column), func)().alias(alias) for alias, column, func in spec.aggregations]
        if spec.group_keys:
            result = table.group_by(*spec.group_keys).agg(*aggregates)
        else:
            result = table.select(*aggregates)
        if spec.sort_keys:
            descending = list(spec.descending) if spec.descending else [False] * len(spec.sort_keys)
            result = result.sort(list(spec.sort_keys), descending=descending)
        if spec.limit:
            result = result.limit(spec.limit)
        return result

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 TPCDSOBT

bench = TPCDSOBT(scale_factor=1.0)            # your scale factor
queries = bench.get_queries(dialect="datafusion")   # your platform's dialect; drop dialect= for native SQL
print(queries['16'])

For the DataFrame form:

from benchbox.core.query_catalog import get_dataframe_render

print(get_dataframe_render('tpcds_obt', '16', family="expression").source)  # or family="pandas"

Source

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