File size: 1,988 Bytes
2eae90c |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 |
import datetime
from fireducks_queries import utils
Q_NUM = 5
def q():
date1 = datetime.datetime.strptime("1994-01-01", "%Y-%m-%d")
date2 = datetime.datetime.strptime("1995-01-01", "%Y-%m-%d")
region_ds = utils.get_region_ds
nation_ds = utils.get_nation_ds
customer_ds = utils.get_customer_ds
line_item_ds = utils.get_line_item_ds
orders_ds = utils.get_orders_ds
supplier_ds = utils.get_supplier_ds
# first call one time to cache in case we don't include the IO times
region_ds()
nation_ds()
customer_ds()
line_item_ds()
orders_ds()
supplier_ds()
def query():
nonlocal region_ds
nonlocal nation_ds
nonlocal customer_ds
nonlocal line_item_ds
nonlocal orders_ds
nonlocal supplier_ds
region_ds = region_ds()
nation_ds = nation_ds()
customer_ds = customer_ds()
line_item_ds = line_item_ds()
orders_ds = orders_ds()
supplier_ds = supplier_ds()
rsel = region_ds.r_name == "ASIA"
osel = (orders_ds.o_orderdate >= date1) & (orders_ds.o_orderdate < date2)
forders = orders_ds[osel]
fregion = region_ds[rsel]
jn1 = fregion.merge(nation_ds, left_on="r_regionkey", right_on="n_regionkey")
jn2 = jn1.merge(customer_ds, left_on="n_nationkey", right_on="c_nationkey")
jn3 = jn2.merge(forders, left_on="c_custkey", right_on="o_custkey")
jn4 = jn3.merge(line_item_ds, left_on="o_orderkey", right_on="l_orderkey")
jn5 = supplier_ds.merge(
jn4,
left_on=["s_suppkey", "s_nationkey"],
right_on=["l_suppkey", "n_nationkey"],
)
jn5["revenue"] = jn5.l_extendedprice * (1.0 - jn5.l_discount)
gb = jn5.groupby("n_name", as_index=False)["revenue"].sum()
result_df = gb.sort_values("revenue", ascending=False)
return result_df
utils.run_query(Q_NUM, query)
if __name__ == "__main__":
q()
|