Read Primitives — Array Distinct

Read Primitives benchmark · all Read Primitives queries

Get distinct elements from array

Representative SQL

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

WITH ship_modes AS (
  SELECT
    l_orderkey,
    ARRAY_AGG(l_shipmode) AS modes
  FROM lineitem
  GROUP BY
    l_orderkey
)
SELECT
  l_orderkey,
  ARRAY_SORT(ARRAY_DISTINCT(modes)) AS unique_modes
FROM ship_modes
ORDER BY
  l_orderkey
LIMIT 100

Representative DataFrame

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

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

    return (
        _expr_grouped_list(ctx, "lineitem", "l_orderkey", "l_shipmode", "modes")
        .with_columns(col("modes").list.unique().list.sort().alias("unique_modes"))
        .select("l_orderkey", "unique_modes")
        .sort("l_orderkey")
        .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['array_distinct'])

For the DataFrame form:

from benchbox.core.query_catalog import get_dataframe_render

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

Source

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