JoinOrder Q30c — Canonical JoinOrder 30c

JoinOrder benchmark · all JoinOrder queries

Canonical JoinOrder SQL query 30c; generated DataFrame translation

Representative SQL

Rendered for DataFusion with default parameters.

SELECT
  MIN(mi.info) AS movie_budget,
  MIN(mi_idx.info) AS movie_votes,
  MIN(n.name) AS writer,
  MIN(t.title) AS complete_violent_movie
FROM complete_cast AS cc, comp_cast_type AS cct1, comp_cast_type AS cct2, cast_info AS ci, info_type AS it1, info_type AS it2, keyword AS k, movie_info AS mi, movie_info_idx AS mi_idx, movie_keyword AS mk, name AS n, title AS t
WHERE
  cct1.kind = 'cast'
  AND cct2.kind = 'complete+verified'
  AND ci.note IN ('(writer)', '(head writer)', '(written by)', '(story)', '(story editor)')
  AND it1.info = 'genres'
  AND it2.info = 'votes'
  AND k.keyword IN ('murder', 'violence', 'blood', 'gore', 'death', 'female-nudity', 'hospital')
  AND mi.info IN ('Horror', 'Action', 'Sci-Fi', 'Thriller', 'Crime', 'War')
  AND n.gender = 'm'
  AND t.id = mi.movie_id
  AND t.id = mi_idx.movie_id
  AND t.id = ci.movie_id
  AND t.id = mk.movie_id
  AND t.id = cc.movie_id
  AND ci.movie_id = mi.movie_id
  AND ci.movie_id = mi_idx.movie_id
  AND ci.movie_id = mk.movie_id
  AND ci.movie_id = cc.movie_id
  AND mi.movie_id = mi_idx.movie_id
  AND mi.movie_id = mk.movie_id
  AND mi.movie_id = cc.movie_id
  AND mi_idx.movie_id = mk.movie_id
  AND mi_idx.movie_id = cc.movie_id
  AND mk.movie_id = cc.movie_id
  AND n.id = ci.person_id
  AND it1.id = mi.info_type_id
  AND it2.id = mi_idx.info_type_id
  AND k.id = mk.keyword_id
  AND cct1.id = cc.subject_id
  AND cct2.id = cc.status_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['30c'])

For the DataFrame form:

from benchbox.core.query_catalog import get_dataframe_render

print(get_dataframe_render('joinorder', '30c', family="expression").source)  # or family="pandas"

Source

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