TPC-DI AQ1

TPC-DI benchmark · all TPC-DI queries

Representative SQL

Rendered for DataFusion with default parameters.

SELECT
  'Customer Profitability Analysis' AS analysis_name,
  c.Tier,
  c.Country,
  c.Gender,
  COUNT(DISTINCT c.SK_CustomerID) AS customer_count,
  COUNT(t.TradeID) AS total_trades,
  SUM(t.Quantity * t.TradePrice) AS total_trade_value,
  SUM(t.Fee + t.Commission + t.Tax) AS total_fees_generated,
  AVG(t.TradePrice) AS avg_trade_price,
  AVG(c.NetWorth) AS avg_net_worth,
  AVG(c.CreditRating) AS avg_credit_rating,
  SUM(t.Quantity * t.TradePrice) / COUNT(DISTINCT c.SK_CustomerID) AS revenue_per_customer,
  SUM(t.Fee + t.Commission + t.Tax) / COUNT(DISTINCT c.SK_CustomerID) AS fees_per_customer,
  COUNT(t.TradeID) / COUNT(DISTINCT c.SK_CustomerID) AS trades_per_customer
FROM DimCustomer AS c
LEFT JOIN FactTrade AS t
  ON c.SK_CustomerID = t.SK_CustomerID
LEFT JOIN DimDate AS d
  ON t.SK_CreateDateID = d.SK_DateID
WHERE
  c.IsCurrent IS TRUE
  AND (
    d.CalendarYearID >= 2015 AND d.CalendarYearID <= 2019
  )
  AND t.Status = 'Completed'
GROUP BY
  c.Tier,
  c.Country,
  c.Gender
HAVING
  COUNT(t.TradeID) > 10
ORDER BY
  total_fees_generated DESC,
  total_trade_value DESC
LIMIT 50

Representative DataFrame

No DataFrame implementation is registered for this query.

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 TPCDI

bench = TPCDI(scale_factor=0.01)            # your scale factor
queries = bench.get_queries(dialect="datafusion")   # your platform's dialect; drop dialect= for native SQL
print(queries['AQ1'])

Source

Query text: benchbox/core/tpcdi/query_analytics.py