Read Primitives — Large Cardinality Group By

Read Primitives benchmark · all Read Primitives queries

Aggregates within high cardinality grouping

Representative SQL

Rendered for DataFusion with default parameters.

SELECT
  l_orderkey,
  l_partkey,
  l_suppkey,
  SUM(l_quantity) AS total_qty,
  AVG(l_extendedprice) AS avg_price
FROM lineitem
GROUP BY
  l_orderkey,
  l_partkey,
  l_suppkey

Representative DataFrame

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

def impl(ctx: DataFrameContext) -> Any:
        return aggregation_groupby_impl(
            ctx,
            table_name=table_name,
            group_cols=group_cols,
            agg_specs=agg_specs,
            conditions=conditions,
            sort_cols=sort_cols,
            sort_desc=sort_desc,
            limit=limit,
        )

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_groupby_large'])

For the DataFrame form:

from benchbox.core.query_catalog import get_dataframe_render

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

Source

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