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import pyspark | |
from pyspark.sql import SparkSession | |
create_table_query = ''' | |
SELECT | |
item_id_1, | |
item_id_2 | |
FROM ( | |
SELECT | |
item_id_1, | |
item_id_2, | |
ROW_NUMBER() OVER(PARTITION BY item_id_1 ORDER BY similarity_score DESC) as row_num | |
FROM {similarity_table} s | |
{same_category_q} | |
) | |
WHERE row_num <= {num_items} | |
''' | |
def create_new_table(spark, table_paths, params, from_date, to_date, same_category_q): | |
similarity_table = table_paths["product_similarity"]["table"] | |
created_table = spark.sql(create_table_query.format(similarity_table=similarity_table, | |
same_category_q=same_category_q, | |
num_items=params["num_items"])) | |
# Write table to some path | |
created_table.coalesce(1).write.save(table_paths["created_table"]["path"], | |
format="orc", mode="Overwrite") | |
def make_query(same_category, table_paths): | |
if same_category is True: | |
same_category_q = ''' | |
INNER JOIN {product_table} p | |
ON s.item_id_1 = p.item_id | |
INNER JOIN {product_table} q | |
ON s.item_id_2 = q.item_id | |
WHERE item_id_1 != item_id_2 | |
AND p.category_id = q.category_id | |
'''.format(product_table=table_paths["product_table"]["table"]) | |
else: | |
same_category_q = '' | |
return same_category_q | |
if __name__ == "__main__": | |
spark = (SparkSession | |
.builder | |
.appName("testing_tutorial") | |
.enableHiveSupport() | |
.getOrCreate()) | |
same_category = True # or False | |
table_paths = foo # Assume paths are in some JSON | |
params = bar | |
same_category_q, target_join_q = make_query(same_category, table_paths) | |
create_new_table(spark, table_paths, params, same_category_q) |
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