q18_large_volume_customer.py

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"""
TPC-H Problem Statement Query 18:

The Large Volume Customer Query finds a list of the top 100 customers who have ever placed large
quantity orders. The query lists the customer name, customer key, the order key, date and total
price and the quantity for the order.

The above problem statement text is copyrighted by the Transaction Processing Performance Council
as part of their TPC Benchmark H Specification revision 2.18.0.

Reference SQL (from TPC-H specification, used by the benchmark suite)::

    select
        c_name,
        c_custkey,
        o_orderkey,
        o_orderdate,
        o_totalprice,
        sum(l_quantity)
    from
        customer,
        orders,
        lineitem
    where
        o_orderkey in (
                select
                        l_orderkey
                from
                        lineitem
                group by
                        l_orderkey having
                                sum(l_quantity) > 300
        )
        and c_custkey = o_custkey
        and o_orderkey = l_orderkey
    group by
        c_name,
        c_custkey,
        o_orderkey,
        o_orderdate,
        o_totalprice
    order by
        o_totalprice desc,
        o_orderdate limit 100;
"""

from datafusion import SessionContext, col
from datafusion import functions as F
from util import get_data_path

QUANTITY = 300

# Load the dataframes we need

ctx = SessionContext()

df_customer = ctx.read_parquet(get_data_path("customer.parquet")).select(
    "c_custkey", "c_name"
)
df_orders = ctx.read_parquet(get_data_path("orders.parquet")).select(
    "o_orderkey", "o_custkey", "o_orderdate", "o_totalprice"
)
df_lineitem = ctx.read_parquet(get_data_path("lineitem.parquet")).select(
    "l_orderkey", "l_quantity", "l_extendedprice"
)

# Find orders whose total quantity exceeds the threshold, then join in the
# order + customer details the problem statement requires and sort.
df = (
    df_lineitem.aggregate(
        ["l_orderkey"], [F.sum(col("l_quantity")).alias("total_quantity")]
    )
    .filter(col("total_quantity") > QUANTITY)
    .join(df_orders, left_on="l_orderkey", right_on="o_orderkey")
    .join(df_customer, left_on="o_custkey", right_on="c_custkey")
    .select(
        "c_name",
        "c_custkey",
        "o_orderkey",
        "o_orderdate",
        "o_totalprice",
        "total_quantity",
    )
    .sort(col("o_totalprice").sort(ascending=False), "o_orderdate")
)

df.show()