Spark：将dataframe列与数组连接

Question

我有两个带有两列的DataFrame

• df1 与模式 (key1:Long, Value)

• df2 与模式 (key2:Array[Long], Value)

我需要将这些DataFrame加入键列（在key1和之间找到匹配的值key2）。但是问题在于它们的类型不同。有没有办法做到这一点？

Answer 1

做到这一点的最佳方法（并且不需要任何数据帧的转换或分解）是使用array_containsspark sql表达式，如下所示。

import org.apache.spark.sql.functions.expr
import spark.implicits._

val df1 = Seq((1L,"one.df1"), (2L,"two.df1"),(3L,"three.df1")).toDF("key1","Value")

val df2 = Seq((Array(1L,1L),"one.df2"), (Array(2L,2L),"two.df2"), (Array(3L,3L),"three.df2")).toDF("key2","Value")

val joinedRDD = df1.join(df2, expr("array_contains(key2, key1)")).show

+----+---------+------+---------+
|key1|    Value|  key2|    Value|
+----+---------+------+---------+
|   1|  one.df1|[1, 1]|  one.df2|
|   2|  two.df1|[2, 2]|  two.df2|
|   3|three.df1|[3, 3]|three.df2|
+----+---------+------+---------+

请注意，您不能org.apache.spark.sql.functions.array_contains直接使用该函数，因为它要求第二个参数是文字，而不是列表达式。

Answer 2

您可以强制转换key1 和 key2 的类型，然后使用contains函数，如下所示。

val df1 = sc.parallelize(Seq((1L,"one.df1"), 
                             (2L,"two.df1"),      
                             (3L,"three.df1"))).toDF("key1","Value")  

DF1:
+----+---------+
|key1|Value    |
+----+---------+
|1   |one.df1  |
|2   |two.df1  |
|3   |three.df1|
+----+---------+

val df2 = sc.parallelize(Seq((Array(1L,1L),"one.df2"),
                             (Array(2L,2L),"two.df2"),
                             (Array(3L,3L),"three.df2"))).toDF("key2","Value")
DF2:
+------+---------+
|key2  |Value    |
+------+---------+
|[1, 1]|one.df2  |
|[2, 2]|two.df2  |
|[3, 3]|three.df2|
+------+---------+

val joinedRDD = df1.join(df2, col("key2").cast("string").contains(col("key1").cast("string")))

JOIN:
+----+---------+------+---------+
|key1|Value    |key2  |Value    |
+----+---------+------+---------+
|1   |one.df1  |[1, 1]|one.df2  |
|2   |two.df1  |[2, 2]|two.df2  |
|3   |three.df1|[3, 3]|three.df2|
+----+---------+------+---------+