JoinOrder Q14a — Canonical JoinOrder 14a

JoinOrder benchmark · all JoinOrder queries

Canonical JoinOrder SQL query 14a; generated DataFrame translation

Representative SQL

Rendered for DataFusion with default parameters.

SELECT
  MIN(mi_idx.info) AS rating,
  MIN(t.title) AS northern_dark_movie
FROM info_type AS it1, info_type AS it2, keyword AS k, kind_type AS kt, movie_info AS mi, movie_info_idx AS mi_idx, movie_keyword AS mk, title AS t
WHERE
  it1.info = 'countries'
  AND it2.info = 'rating'
  AND k.keyword IN ('murder', 'murder-in-title', 'blood', 'violence')
  AND kt.kind = 'movie'
  AND mi.info IN (
    'Sweden',
    'Norway',
    'Germany',
    'Denmark',
    'Swedish',
    'Denish',
    'Norwegian',
    'German',
    'USA',
    'American'
  )
  AND mi_idx.info < '8.5'
  AND t.production_year > 2010
  AND kt.id = t.kind_id
  AND t.id = mi.movie_id
  AND t.id = mk.movie_id
  AND t.id = mi_idx.movie_id
  AND mk.movie_id = mi.movie_id
  AND mk.movie_id = mi_idx.movie_id
  AND mi.movie_id = mi_idx.movie_id
  AND k.id = mk.keyword_id
  AND it1.id = mi.info_type_id
  AND it2.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['14a'])

For the DataFrame form:

from benchbox.core.query_catalog import get_dataframe_render

print(get_dataframe_render('joinorder', '14a', family="expression").source)  # or family="pandas"

Source

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