Read Primitives — QUALIFY PERCENT_RANK

Read Primitives benchmark · all Read Primitives queries

Find orders in top 10% per priority using PERCENT_RANK

Representative SQL

Rendered for DataFusion with default parameters.

SELECT
  o_orderpriority,
  o_orderkey,
  o_totalprice,
  price_percentile
FROM (
  SELECT
    o_orderpriority,
    o_orderkey,
    o_totalprice,
    PERCENT_RANK() OVER (PARTITION BY o_orderpriority ORDER BY o_totalprice) AS price_percentile,
    PERCENT_RANK() OVER (PARTITION BY o_orderpriority ORDER BY o_totalprice) AS _w
  FROM orders
  WHERE
    o_orderdate >= CAST('1995-01-01' AS DATE)
  ORDER BY
    o_orderpriority,
    o_totalprice DESC
) AS _t
WHERE
  _w >= 0.9

Representative DataFrame

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

def qualify_percentile_expression_impl(ctx: DataFrameContext) -> Any:
    result = (
        ctx.get_table("orders")
        .filter(ctx.col("o_orderdate") >= ctx.lit(date(1995, 1, 1)))
        .with_columns(
            ctx.window_percent_rank(order_by=[("o_totalprice", True)], partition_by=["o_orderpriority"]).alias(
                "price_percentile"
            )
        )
    )
    return (
        result.filter(ctx.col("price_percentile") >= ctx.lit(0.9))
        .select("o_orderpriority", "o_orderkey", "o_totalprice", "price_percentile")
        .sort(["o_orderpriority", "o_totalprice"], descending=[False, True])
    )

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['qualify_percentile'])

For the DataFrame form:

from benchbox.core.query_catalog import get_dataframe_render

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

Source

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