JoinOrder Q15b — Canonical JoinOrder 15b

JoinOrder benchmark · all JoinOrder queries

Canonical JoinOrder SQL query 15b; generated DataFrame translation

Representative SQL

Rendered for DataFusion with default parameters.

SELECT
  MIN(mi.info) AS release_date,
  MIN(t.title) AS youtube_movie
FROM aka_title AS at1, company_name AS cn, company_type AS ct, info_type AS it1, keyword AS k, movie_companies AS mc, movie_info AS mi, movie_keyword AS mk, title AS t
WHERE
  cn.country_code = '[us]'
  AND cn.name = 'YouTube'
  AND it1.info = 'release dates'
  AND mc.note LIKE '%(200%)%'
  AND mc.note LIKE '%(worldwide)%'
  AND mi.note LIKE '%internet%'
  AND mi.info LIKE 'USA:% 200%'
  AND t.production_year BETWEEN 2005 AND 2010
  AND t.id = at1.movie_id
  AND t.id = mi.movie_id
  AND t.id = mk.movie_id
  AND t.id = mc.movie_id
  AND mk.movie_id = mi.movie_id
  AND mk.movie_id = mc.movie_id
  AND mk.movie_id = at1.movie_id
  AND mi.movie_id = mc.movie_id
  AND mi.movie_id = at1.movie_id
  AND mc.movie_id = at1.movie_id
  AND k.id = mk.keyword_id
  AND it1.id = mi.info_type_id
  AND cn.id = mc.company_id
  AND ct.id = mc.company_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['15b'])

For the DataFrame form:

from benchbox.core.query_catalog import get_dataframe_render

print(get_dataframe_render('joinorder', '15b', family="expression").source)  # or family="pandas"

Source

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