TPC-H Skew Q13 — Customer Distribution

TPC-H Skew benchmark · all TPC-H Skew queries

Distribution of customers by order count

Representative SQL

Rendered for DataFusion with default parameters.

SELECT
  c_count,
  COUNT(*) AS custdist
FROM (
  SELECT
    c_custkey,
    COUNT(o_orderkey)
  FROM customer
  LEFT OUTER JOIN orders
    ON c_custkey = o_custkey AND o_comment NOT LIKE '%special%requests%'
  GROUP BY
    c_custkey
) AS c_orders(c_custkey, c_count)
GROUP BY
  c_count
ORDER BY
  custdist DESC,
  c_count DESC

Representative DataFrame

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

def q13_expression_impl(ctx: DataFrameContext) -> Any:
    customer = ctx.get_table("customer")
    orders = ctx.get_table("orders")
    col = ctx.col

    params = get_tpch_parameters(13)
    word1 = params["word1"]
    word2 = params["word2"]

    customer_orders = (
        customer.join(
            orders.filter(~col("o_comment").str.contains(f"{word1}.*{word2}")),
            left_on="c_custkey",
            right_on="o_custkey",
            how="left",
        )
        .group_by("c_custkey")
        .agg(col("o_orderkey").count().alias("c_count"))
    )

    return (
        customer_orders.group_by("c_count")
        .agg(col("c_custkey").count().alias("custdist"))
        .sort(["custdist", "c_count"], descending=[True, True])
    )

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 TPCHSkew

bench = TPCHSkew(scale_factor=0.01)            # your scale factor
queries = bench.get_queries(dialect="datafusion")   # your platform's dialect; drop dialect= for native SQL
print(queries['13'])

Parameter substitution for this benchmark is seed-driven; pass a seed for a specific stream’s parameters:

print(bench.get_query(13, scale_factor=0.01, seed=42, dialect="datafusion"))

For the DataFrame form:

from benchbox.core.query_catalog import get_dataframe_render

print(get_dataframe_render('tpch_skew', '13', family="expression").source)  # or family="pandas"

Source

Query text: benchbox/_binaries/tpc-h/templates/queries/13.sql