JoinOrder Q30b — Canonical JoinOrder 30b
JoinOrder benchmark · all JoinOrder queries
Canonical JoinOrder SQL query 30b; 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_gore_movieFROM 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 tWHERE cct1.kind IN ('cast', 'crew') 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', 'Thriller') AND n.gender = 'm' AND t.production_year > 2000 AND ( t.title LIKE '%Freddy%' OR t.title LIKE '%Jason%' OR t.title LIKE 'Saw%' ) 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_idRepresentative 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 factorqueries = bench.get_queries(dialect="datafusion") # your platform's dialect; drop dialect= for native SQLprint(queries['30b'])For the DataFrame form:
from benchbox.core.query_catalog import get_dataframe_render
print(get_dataframe_render('joinorder', '30b', family="expression").source) # or family="pandas"Source
Query text: benchbox/core/joinorder/queries.py