Read Primitives — Long Predicate

Read Primitives benchmark · all Read Primitives queries

Query with many conjunctive predicates across multiple tables

Representative SQL

Rendered for DataFusion with default parameters.

SELECT
  COUNT(*)
FROM lineitem AS l
JOIN orders AS o
  ON l.l_orderkey = o.o_orderkey
JOIN customer AS c
  ON o.o_custkey = c.c_custkey
WHERE
  l.l_shipdate >= CAST('1994-01-01' AS DATE)
  AND l.l_shipdate < CAST('1995-01-01' AS DATE)
  AND l.l_discount BETWEEN 0.05 AND 0.07
  AND l.l_quantity < 24
  AND o.o_orderpriority = '1-URGENT'
  AND c.c_mktsegment = 'BUILDING'
  AND l.l_returnflag = 'R'
  AND l.l_linestatus = 'F'
  AND o.o_totalprice > 100000
  AND c.c_nationkey IN (1, 2, 3, 4, 5)

Representative DataFrame

Expression family (Polars, PySpark, DataFusion), default parameters.

def long_predicate_expression_impl(ctx: DataFrameContext) -> Any:
    col, lit = ctx.col, ctx.lit
    return (
        ctx.get_table("lineitem")
        .join(ctx.get_table("orders"), left_on="l_orderkey", right_on="o_orderkey")
        .join(ctx.get_table("customer"), left_on="o_custkey", right_on="c_custkey")
        .filter(
            (col("l_shipdate") >= lit(date(1994, 1, 1)))
            & (col("l_shipdate") < lit(date(1995, 1, 1)))
            & (col("l_discount") >= lit(0.05))
            & (col("l_discount") <= lit(0.07))
            & (col("l_quantity") < lit(24))
            & (col("o_orderpriority") == lit("1-URGENT"))
            & (col("c_mktsegment") == lit("BUILDING"))
            & (col("l_returnflag") == lit("R"))
            & (col("l_linestatus") == lit("F"))
            & (col("o_totalprice") > lit(100000))
            & col("c_nationkey").is_in([1, 2, 3, 4, 5])
        )
        .select(col("l_orderkey").count().alias("count"))
    )

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 ReadPrimitives

bench = ReadPrimitives(scale_factor=0.01)            # your scale factor
queries = bench.get_queries(dialect="datafusion")   # your platform's dialect; drop dialect= for native SQL
print(queries['long_predicate'])

For the DataFrame form:

from benchbox.core.query_catalog import get_dataframe_render

print(get_dataframe_render('read_primitives', 'long_predicate', family="expression").source)  # or family="pandas"

Source

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