Read Primitives — Predicate Ordering with Aggregation

Read Primitives benchmark · all Read Primitives queries

Order filter predicates by selectivity for aggregation

Representative SQL

Rendered for DataFusion with default parameters.

SELECT
  SUM(l_extendedprice) AS total_price
FROM lineitem
WHERE
  l_shipdate >= CAST('1994-01-01' AS DATE)
  AND l_shipdate < CAST('1995-01-01' AS DATE)
  AND l_discount BETWEEN 0.05 AND 0.07
  AND l_quantity < 24

Representative DataFrame

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

def predicate_ordering_aggregation_expression_impl(ctx: DataFrameContext) -> Any:
    col, lit = ctx.col, ctx.lit
    return (
        ctx.get_table("lineitem")
        .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))
        )
        .select(col("l_extendedprice").sum().alias("total_price"))
    )

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['predicate_ordering_aggregation'])

For the DataFrame form:

from benchbox.core.query_catalog import get_dataframe_render

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

Source

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