TPC-DS Q11 — Store/Web Year-over-Year Customer Comparison

TPC-DS benchmark · all TPC-DS queries

Compares customer totals between store and web channels year-over-year

Representative SQL

Rendered for DataFusion with default parameters.

WITH year_total AS (
  SELECT
    c_customer_id AS customer_id,
    c_first_name AS customer_first_name,
    c_last_name AS customer_last_name,
    c_preferred_cust_flag AS customer_preferred_cust_flag,
    c_birth_country AS customer_birth_country,
    c_login AS customer_login,
    c_email_address AS customer_email_address,
    d_year AS dyear,
    SUM(ss_ext_list_price - ss_ext_discount_amt) AS year_total,
    's' AS sale_type
  FROM customer, store_sales, date_dim
  WHERE
    c_customer_sk = ss_customer_sk AND ss_sold_date_sk = d_date_sk
  GROUP BY
    c_customer_id,
    c_first_name,
    c_last_name,
    c_preferred_cust_flag,
    c_birth_country,
    c_login,
    c_email_address,
    d_year
  UNION ALL
  SELECT
    c_customer_id AS customer_id,
    c_first_name AS customer_first_name,
    c_last_name AS customer_last_name,
    c_preferred_cust_flag AS customer_preferred_cust_flag,
    c_birth_country AS customer_birth_country,
    c_login AS customer_login,
    c_email_address AS customer_email_address,
    d_year AS dyear,
    SUM(ws_ext_list_price - ws_ext_discount_amt) AS year_total,
    'w' AS sale_type
  FROM customer, web_sales, date_dim
  WHERE
    c_customer_sk = ws_bill_customer_sk AND ws_sold_date_sk = d_date_sk
  GROUP BY
    c_customer_id,
    c_first_name,
    c_last_name,
    c_preferred_cust_flag,
    c_birth_country,
    c_login,
    c_email_address,
    d_year
)
SELECT
  t_s_secyear.customer_id,
  t_s_secyear.customer_first_name,
  t_s_secyear.customer_last_name,
  t_s_secyear.customer_email_address
FROM year_total AS t_s_firstyear, year_total AS t_s_secyear, year_total AS t_w_firstyear, year_total AS t_w_secyear
WHERE
  t_s_secyear.customer_id = t_s_firstyear.customer_id
  AND t_s_firstyear.customer_id = t_w_secyear.customer_id
  AND t_s_firstyear.customer_id = t_w_firstyear.customer_id
  AND t_s_firstyear.sale_type = 's'
  AND t_w_firstyear.sale_type = 'w'
  AND t_s_secyear.sale_type = 's'
  AND t_w_secyear.sale_type = 'w'
  AND t_s_firstyear.dyear = 2001
  AND t_s_secyear.dyear = 2001 + 1
  AND t_w_firstyear.dyear = 2001
  AND t_w_secyear.dyear = 2001 + 1
  AND t_s_firstyear.year_total > 0
  AND t_w_firstyear.year_total > 0
  AND CASE
    WHEN t_w_firstyear.year_total > 0
    THEN t_w_secyear.year_total / t_w_firstyear.year_total
    ELSE 0.0
  END > CASE
    WHEN t_s_firstyear.year_total > 0
    THEN t_s_secyear.year_total / t_s_firstyear.year_total
    ELSE 0.0
  END
ORDER BY
  t_s_secyear.customer_id,
  t_s_secyear.customer_first_name,
  t_s_secyear.customer_last_name,
  t_s_secyear.customer_email_address
LIMIT 100

Representative DataFrame

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

def q11_expression_impl(ctx: DataFrameContext) -> Any:
    return _year_growth_expression(ctx, *_year_growth_args(11))

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['11'])

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

print(bench.get_query(11, 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', '11', family="expression").source)  # or family="pandas"

Source

Query text: _sources/tpc-ds/query_templates/query11.tpl