Joining two DataFrames in Spark SQL and selecting

问题:

I have two DataFrames in Spark SQL (D1 and D2).

I am trying to inner join both of them D1.join(D2, "some column") and get back data of only D1, not the complete data set.

Both D1 and D2 are having the same columns.

Could some one please help me on this?

I am using Spark 1.6.

回答1:

Let say you want to join on "id" column. Then you could write :

val sqlContext = new org.apache.spark.sql.SQLContext(sc)
import sqlContext.implicits._    
d1.as("d1").join(d2.as("d2"), $"d1.id" === $"d2.id").select($"d1.*")

回答2:

As an alternate answer, you could also do the following without adding aliases:

d1.join(d2, d1("id") === d2("id"))
  .select(d1.columns.map(c => d1(c)): _*)