我们如何使用jdbc执行连接查询,而不是使用pyspark获取多个表
客户-c_id、c_名称、c_地址 产品-p_id、p_名称、价格 供应商-s_id、s_名称、s_地址 订单-订单id、订单id、订单id、数量、时间我们如何使用jdbc执行连接查询,而不是使用pyspark获取多个表,pyspark,pyspark-sql,Pyspark,Pyspark Sql,客户-c_id、c_名称、c_地址 产品-p_id、p_名称、价格 供应商-s_id、s_名称、s_地址 订单-订单id、订单id、订单id、数量、时间 SELECT o.o_id, c.c_id, c.c_name, p.p_id, p.p_name, p.price * o.quantity AS amount FROM customer c JOIN orders o ON o.c_id = c.c_id JOIN pr
SELECT o.o_id,
c.c_id,
c.c_name,
p.p_id,
p.p_name,
p.price * o.quantity AS amount
FROM customer c
JOIN orders o ON o.c_id = c.c_id
JOIN product p ON p.p_id = o.p_id;
我想执行上述查询,而不必在pyspark中获取3个表作为单独的数据帧,并对数据帧执行联接 您可以使用查询代替表,如下所述 参考文献 在您的情况下,它将是:
df = spark.read.jdbc("url", """
(
SELECT o.o_id,
c.c_id,
c.c_name,
p.p_id,
p.p_name,
p.price * o.quantity AS amount
FROM customer c
JOIN orders o ON o.c_id = c.c_id
JOIN product p ON p.p_id = o.p_id
) as table""", properties={"user":"username", "password":"password"})
这使用了这种类型的查询来代替表。这也与你的情况有关
df = spark.read.jdbc("url", """
(
SELECT o.o_id,
c.c_id,
c.c_name,
p.p_id,
p.p_name,
p.price * o.quantity AS amount
FROM customer c
JOIN orders o ON o.c_id = c.c_id
JOIN product p ON p.p_id = o.p_id
) as table""", properties={"user":"username", "password":"password"})