Read Primitives — Window RANK

Read Primitives benchmark · all Read Primitives queries

Window function RANK() OVER (PARTITION BY … ORDER BY …)

Representative SQL

Rendered for DataFusion with default parameters.

SELECT
  l_orderkey,
  l_returnflag,
  l_quantity,
  qty_rank
FROM (
  SELECT
    l_orderkey,
    l_returnflag,
    l_quantity,
    RANK() OVER (PARTITION BY l_returnflag ORDER BY l_quantity DESC) AS qty_rank
  FROM lineitem
) AS ranked
WHERE
  qty_rank <= 5
ORDER BY
  l_returnflag,
  qty_rank,
  l_orderkey

Representative DataFrame

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

def window_rank_expression_impl(ctx: DataFrameContext) -> Any:
    result = ctx.get_table("lineitem").with_columns(
        ctx.window_rank(order_by=[("l_quantity", False)], partition_by=["l_returnflag"]).alias("qty_rank")
    )
    return (
        result.filter(ctx.col("qty_rank") <= 5)
        .select("l_orderkey", "l_returnflag", "l_quantity", "qty_rank")
        .sort(["l_returnflag", "qty_rank", "l_orderkey"])
    )

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['window_rank'])

For the DataFrame form:

from benchbox.core.query_catalog import get_dataframe_render

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

Source

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