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from spark_queries import utils
Q_NUM = 8
def q():
query_str = f"""
select
o_year,
round(
sum(case
when nation = 'BRAZIL' then volume
else 0
end) / sum(volume)
, 2) as mkt_share
from
(
select
extract(year from o_orderdate) as o_year,
l_extendedprice * (1 - l_discount) as volume,
n2.n_name as nation
from
part,
supplier,
lineitem,
orders,
customer,
nation n1,
nation n2,
region
where
p_partkey = l_partkey
and s_suppkey = l_suppkey
and l_orderkey = o_orderkey
and o_custkey = c_custkey
and c_nationkey = n1.n_nationkey
and n1.n_regionkey = r_regionkey
and r_name = 'AMERICA'
and s_nationkey = n2.n_nationkey
and o_orderdate between date '1995-01-01' and date '1996-12-31'
and p_type = 'ECONOMY ANODIZED STEEL'
) as all_nations
group by
o_year
order by
o_year
"""
utils.get_part_ds()
utils.get_supplier_ds()
utils.get_line_item_ds()
utils.get_orders_ds()
utils.get_customer_ds()
utils.get_nation_ds()
utils.get_region_ds()
q_final = utils.get_or_create_spark().sql(query_str)
utils.run_query(Q_NUM, q_final)
if __name__ == "__main__":
q()