JoinOrder Q13d — Canonical JoinOrder 13d

JoinOrder benchmark · all JoinOrder queries

Canonical JoinOrder SQL query 13d; generated DataFrame translation

Representative SQL

Rendered for DataFusion with default parameters.

SELECT
  MIN(cn.name) AS producing_company,
  MIN(miidx.info) AS rating,
  MIN(t.title) AS movie
FROM company_name AS cn, company_type AS ct, info_type AS it, info_type AS it2, kind_type AS kt, movie_companies AS mc, movie_info AS mi, movie_info_idx AS miidx, title AS t
WHERE
  cn.country_code = '[us]'
  AND ct.kind = 'production companies'
  AND it.info = 'rating'
  AND it2.info = 'release dates'
  AND kt.kind = 'movie'
  AND mi.movie_id = t.id
  AND it2.id = mi.info_type_id
  AND kt.id = t.kind_id
  AND mc.movie_id = t.id
  AND cn.id = mc.company_id
  AND ct.id = mc.company_type_id
  AND miidx.movie_id = t.id
  AND it.id = miidx.info_type_id
  AND mi.movie_id = miidx.movie_id
  AND mi.movie_id = mc.movie_id
  AND miidx.movie_id = mc.movie_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['13d'])

For the DataFrame form:

from benchbox.core.query_catalog import get_dataframe_render

print(get_dataframe_render('joinorder', '13d', family="expression").source)  # or family="pandas"

Source

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