TPC-DI AQ2

TPC-DI benchmark · all TPC-DI queries

Representative SQL

Rendered for DataFusion with default parameters.

SELECT
  'Security Performance Analysis' AS analysis_name,
  s.Symbol,
  s.Name AS security_name,
  comp.Name AS company_name,
  comp.Industry,
  comp.SPrating,
  COUNT(t.TradeID) AS total_trades,
  SUM(t.Quantity) AS total_volume,
  AVG(t.TradePrice) AS avg_trade_price,
  MIN(t.TradePrice) AS min_trade_price,
  MAX(t.TradePrice) AS max_trade_price,
  (
    MAX(t.TradePrice) - MIN(t.TradePrice)
  ) / MIN(t.TradePrice) * 100 AS price_volatility_pct,
  SUM(t.Quantity * t.TradePrice) AS total_market_value,
  AVG(mh.ClosePrice) AS avg_market_close,
  AVG(mh.Volume) AS avg_daily_volume,
  AVG(mh.PERatio) AS avg_pe_ratio,
  AVG(mh.Yield) AS avg_dividend_yield,
  MAX(mh.FiftyTwoWeekHigh) AS week52_high,
  MIN(mh.FiftyTwoWeekLow) AS week52_low
FROM DimSecurity AS s
JOIN DimCompany AS comp
  ON s.SK_CompanyID = comp.SK_CompanyID
LEFT JOIN FactTrade AS t
  ON s.SK_SecurityID = t.SK_SecurityID
LEFT JOIN FactMarketHistory AS mh
  ON s.SK_SecurityID = mh.SK_SecurityID
LEFT JOIN DimDate AS d
  ON t.SK_CreateDateID = d.SK_DateID
WHERE
  s.IsCurrent IS TRUE
  AND comp.IsCurrent IS TRUE
  AND (
    d.CalendarYearID >= 2015 AND d.CalendarYearID <= 2019
  )
  AND t.Status = 'Completed'
GROUP BY
  s.Symbol,
  s.Name,
  comp.Name,
  comp.Industry,
  comp.SPrating
HAVING
  COUNT(t.TradeID) > 10
ORDER BY
  total_market_value DESC,
  price_volatility_pct 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['AQ2'])

Source

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