Read Primitives — Map Access

Read Primitives benchmark · all Read Primitives queries

Access map values by key

Representative SQL

Rendered for DataFusion with default parameters.

WITH supplier_costs AS (
  SELECT
    ps_suppkey,
    MAP(ARRAY_AGG(CAST(ps_partkey AS VARCHAR)), ARRAY_AGG(ps_supplycost)) AS part_costs
  FROM partsupp
  WHERE
    ps_suppkey <= 10
  GROUP BY
    ps_suppkey
)
SELECT
  ps_suppkey,
  MAP_EXTRACT(part_costs, '1')[1] AS cost_for_part_1,
  MAP_EXTRACT(part_costs, '5')[1] AS cost_for_part_5
FROM supplier_costs
ORDER BY
  ps_suppkey
LIMIT 10

Representative DataFrame

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

def map_access_expression_impl(ctx: DataFrameContext) -> Any:
    col = ctx.col
    lit = ctx.lit

    return (
        _partsupp_map_expression(ctx, 10)
        .select(
            "ps_suppkey",
            col("part_costs").map.get(lit("1")).alias("cost_for_part_1"),
            col("part_costs").map.get(lit("5")).alias("cost_for_part_5"),
        )
        .limit(10)
    )

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['map_access'])

For the DataFrame form:

from benchbox.core.query_catalog import get_dataframe_render

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

Source

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