Read Primitives — Nested Aggregation

Read Primitives benchmark · all Read Primitives queries

Nested aggregation requiring CTE materialization

Representative SQL

Rendered for DataFusion with default parameters.

WITH order_totals AS (
  SELECT
    o_custkey,
    SUM(o_totalprice) AS customer_total
  FROM orders
  GROUP BY
    o_custkey
)
SELECT
  AVG(customer_total) AS avg_customer_spending
FROM order_totals

Representative DataFrame

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

def aggregation_materialize_expression_impl(ctx: DataFrameContext) -> Any:
    totals = ctx.get_table("orders").group_by("o_custkey").agg(ctx.col("o_totalprice").sum().alias("customer_total"))
    return totals.select(ctx.col("customer_total").mean().alias("avg_customer_spending"))

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['aggregation_materialize'])

For the DataFrame form:

from benchbox.core.query_catalog import get_dataframe_render

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

Source

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