Read Primitives — QUALIFY LAG/LEAD

Read Primitives benchmark · all Read Primitives queries

Find orders with increasing price using LAG

Representative SQL

Rendered for DataFusion with default parameters.

SELECT
  c_custkey,
  c_name,
  o_orderkey,
  o_orderdate,
  o_totalprice,
  prev_order_price
FROM (
  SELECT
    c_custkey,
    c_name,
    o_orderkey,
    o_orderdate,
    o_totalprice,
    LAG(o_totalprice) OVER (PARTITION BY c_custkey ORDER BY o_orderdate, o_orderkey) AS prev_order_price,
    LAG(o_totalprice) OVER (PARTITION BY c_custkey ORDER BY o_orderdate, o_orderkey) AS _w
  FROM customer AS c
  JOIN orders AS o
    ON c.c_custkey = o.o_custkey
  WHERE
    o_orderdate >= CAST('1995-01-01' AS DATE)
  ORDER BY
    c_custkey,
    o_orderdate,
    o_orderkey
) AS _t
WHERE
  o_totalprice > _w

Representative DataFrame

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

def qualify_lag_lead_expression_impl(ctx: DataFrameContext) -> Any:
    return (
        _orders_customer_since_1995_expr(ctx)
        .with_columns(
            ctx.window_lag(
                "o_totalprice",
                1,
                partition_by=["c_custkey"],
                order_by=[("o_orderdate", True), ("o_orderkey", True)],
            ).alias("prev_order_price")
        )
        .filter(ctx.col("o_totalprice") > ctx.col("prev_order_price"))
        .select("c_custkey", "c_name", "o_orderkey", "o_orderdate", "o_totalprice", "prev_order_price")
        .sort(["c_custkey", "o_orderdate", "o_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['qualify_lag_lead'])

For the DataFrame form:

from benchbox.core.query_catalog import get_dataframe_render

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

Source

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