Read Primitives — Window Lead/Lag
Read Primitives benchmark · all Read Primitives queries
Offset window functions over the same frame
Representative SQL
Rendered for DataFusion with default parameters.
SELECT o_orderkey, o_orderdate, o_totalprice, LAG(o_totalprice, 1) OVER (PARTITION BY o_custkey ORDER BY o_orderdate, o_orderkey) AS prev_order_price, LEAD(o_totalprice, 1) OVER (PARTITION BY o_custkey ORDER BY o_orderdate, o_orderkey) AS next_order_priceFROM ordersWHERE o_orderdate >= CAST('1995-01-01' AS DATE) AND o_orderdate < CAST('1996-01-01' AS DATE)Representative DataFrame
Expression family (Polars, PySpark, DataFusion), default parameters.
def window_lead_lag_expression_impl(ctx: DataFrameContext) -> Any: order_by = [("o_orderdate", True), ("o_orderkey", True)] return ( ctx.get_table("orders") .filter( (ctx.col("o_orderdate") >= ctx.lit(date(1995, 1, 1))) & (ctx.col("o_orderdate") < ctx.lit(date(1996, 1, 1))) ) .with_columns( ctx.window_lag("o_totalprice", 1, partition_by=["o_custkey"], order_by=order_by).alias("prev_order_price"), ctx.window_lead("o_totalprice", 1, partition_by=["o_custkey"], order_by=order_by).alias("next_order_price"), ) .sort(["o_custkey", "o_orderdate", "o_orderkey"]) .select("o_orderkey", "o_orderdate", "o_totalprice", "prev_order_price", "next_order_price") )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 factorqueries = bench.get_queries(dialect="datafusion") # your platform's dialect; drop dialect= for native SQLprint(queries['window_lead_lag_same_frame'])For the DataFrame form:
from benchbox.core.query_catalog import get_dataframe_render
print(get_dataframe_render('read_primitives', 'window_lead_lag_same_frame', family="expression").source) # or family="pandas"Source
Query text: benchbox/core/read_primitives/queries.py