JoinOrder Q1a — Production Companies Top 250

JoinOrder benchmark · all JoinOrder queries

Production companies with top 250 ranked movies (5 tables)

Representative SQL

Rendered for DataFusion with default parameters.

SELECT
  MIN(mc.note) AS production_note,
  MIN(t.title) AS movie_title,
  MIN(t.production_year) AS movie_year
FROM company_type AS ct, info_type AS it, movie_companies AS mc, movie_info_idx AS mi_idx, title AS t
WHERE
  ct.kind = 'production companies'
  AND it.info = 'top 250 rank'
  AND mc.note NOT LIKE '%(as Metro-Goldwyn-Mayer Pictures)%'
  AND (
    mc.note LIKE '%(co-production)%' OR mc.note LIKE '%(presents)%'
  )
  AND ct.id = mc.company_type_id
  AND t.id = mc.movie_id
  AND t.id = mi_idx.movie_id
  AND mc.movie_id = mi_idx.movie_id
  AND it.id = mi_idx.info_type_id

Representative DataFrame

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

def _impl(ctx: DataFrameContext) -> Any:
        return _execute_joinorder_expression_query(ctx, query_id)

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 JoinOrder

bench = JoinOrder(scale_factor=1.0)            # your scale factor
queries = bench.get_queries(dialect="datafusion")   # your platform's dialect; drop dialect= for native SQL
print(queries['1a'])

For the DataFrame form:

from benchbox.core.query_catalog import get_dataframe_render

print(get_dataframe_render('joinorder', '1a', family="expression").source)  # or family="pandas"

Source

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