q04_order_priority_checking.py

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"""
TPC-H Problem Statement Query 4:

The Order Priority Checking Query counts the number of orders ordered in a given quarter of a given
year in which at least one lineitem was received by the customer later than its committed date. The
query lists the count of such orders for each order priority sorted in ascending priority 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
        o_orderpriority,
        count(*) as order_count
    from
        orders
    where
        o_orderdate >= date '1993-07-01'
        and o_orderdate < date '1993-07-01' + interval '3' month
        and exists (
                select
                        *
                from
                        lineitem
                where
                        l_orderkey = o_orderkey
                        and l_commitdate < l_receiptdate
        )
    group by
        o_orderpriority
    order by
        o_orderpriority;
"""

from datetime import date

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

QUARTER_START = date(1993, 7, 1)
QUARTER_END = date(1993, 10, 1)

# Load the dataframes we need

ctx = SessionContext()

df_orders = ctx.read_parquet(get_data_path("orders.parquet")).select(
    "o_orderdate", "o_orderpriority", "o_orderkey"
)
df_lineitem = ctx.read_parquet(get_data_path("lineitem.parquet")).select(
    "l_orderkey", "l_commitdate", "l_receiptdate"
)

# Keep only orders in the quarter of interest, then restrict to those that
# have at least one late lineitem via a semi join (the DataFrame form of
# ``EXISTS`` from the reference SQL).
df_orders = df_orders.filter(
    col("o_orderdate") >= lit(QUARTER_START),
    col("o_orderdate") < lit(QUARTER_END),
)

late_lineitems = df_lineitem.filter(col("l_commitdate") < col("l_receiptdate"))

df = df_orders.join(
    late_lineitems, left_on="o_orderkey", right_on="l_orderkey", how="semi"
)

# Count the number of orders in each priority group and sort.
df = df.aggregate(["o_orderpriority"], [F.count_star().alias("order_count")]).sort_by(
    "o_orderpriority"
)

df.show()