Read Primitives — List Filter

Read Primitives benchmark · all Read Primitives queries

Filter array elements by condition

Representative SQL

Rendered in the benchmark’s native SQL with default parameters (no dialect translation available).

WITH order_prices AS (
  SELECT
    o_custkey,
    ARRAY_AGG(o_totalprice) AS prices
  FROM orders
  GROUP BY
    o_custkey
)
SELECT
  o_custkey,
  FILTER(prices, x -> x > 100000) AS large_orders
FROM order_prices
ORDER BY
  o_custkey
LIMIT 100

Representative DataFrame

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

def list_filter_expression_impl(ctx: DataFrameContext) -> Any:
    col = ctx.col
    lit = ctx.lit
    elem = ctx.element()

    return (
        _expr_grouped_list(ctx, "orders", "o_custkey", "o_totalprice", "prices")
        .with_columns(col("prices").list.eval(elem.filter(elem > lit(100000))).alias("large_orders"))
        .select("o_custkey", "large_orders")
        .sort("o_custkey")
        .limit(100)
    )

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['list_filter'])

For the DataFrame form:

from benchbox.core.query_catalog import get_dataframe_render

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

Source

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