spark 表关联

发现用spark写表join比flink 简单很多，至少schema 可以省了，下面是一个例子

public static void main(String[] args) {                 SparkSession s= SparkSession.builder().appName("rec").getOrCreate();         Dataset user=s.read().format("jdbc")          .option("driver", "com.mysql.jdbc.Driver")          .option("url", "jdbc:mysql://*")          .option("dbtable", "user")          .option("user", "1")          .option("password", "1")          .load();         Dataset house=s.read().format("jdbc")                  .option("driver", "com.mysql.jdbc.Driver")                  .option("url", "jdbc:mysql://")                  .option("dbtable", "house")                  .option("user", "1")                  .option("password", "1")                  .load();         user.cache();         house.cache();         user.createOrReplaceTempView("user");         house.createOrReplaceTempView("house");         Dataset temp= s.sql("select user.user_name, house.house_name from user inner join house where user.uid=house.uid ");         temp.write().csv("/home/ziroom/house-user");    }