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from datetime import datetime
from fireducks_queries import utils
Q_NUM = 3
def q():
var1 = var2 = datetime(1995, 3, 15)
var3 = "BUILDING"
customer_ds = utils.get_customer_ds
line_item_ds = utils.get_line_item_ds
orders_ds = utils.get_orders_ds
# first call one time to cache in case we don't include the IO times
customer_ds()
line_item_ds()
orders_ds()
def query():
nonlocal customer_ds
nonlocal line_item_ds
nonlocal orders_ds
customer_ds = customer_ds()
line_item_ds = line_item_ds()
orders_ds = orders_ds()
lineitem_filtered = line_item_ds.loc[
:, ["l_orderkey", "l_extendedprice", "l_discount", "l_shipdate"]
]
orders_filtered = orders_ds.loc[
:, ["o_orderkey", "o_custkey", "o_orderdate", "o_shippriority"]
]
customer_filtered = customer_ds.loc[:, ["c_mktsegment", "c_custkey"]]
lsel = lineitem_filtered.l_shipdate > var1
osel = orders_filtered.o_orderdate < var2
csel = customer_filtered.c_mktsegment == var3
flineitem = lineitem_filtered[lsel]
forders = orders_filtered[osel]
fcustomer = customer_filtered[csel]
jn1 = fcustomer.merge(forders, left_on="c_custkey", right_on="o_custkey")
jn2 = jn1.merge(flineitem, left_on="o_orderkey", right_on="l_orderkey")
jn2["revenue"] = jn2.l_extendedprice * (1 - jn2.l_discount)
total = (
jn2.groupby(
["l_orderkey", "o_orderdate", "o_shippriority"], as_index=False
)["revenue"]
.sum()
.sort_values(["revenue"], ascending=False)
)
result_df = total[:10].loc[
:, ["l_orderkey", "revenue", "o_orderdate", "o_shippriority"]
]
return result_df
utils.run_query(Q_NUM, query)
if __name__ == "__main__":
q()
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