横向视图/爆炸在火花与多个列，得到重复

Question

我有以下数据帧，其中包含一些包含数组的列。（我们使用的是火花 1.6）

+--------------------+--------------+------------------+--------------+--------------------+-------------+
|            UserName|     col1     |    col2          |col3          |col4                |col5         |
+--------------------+--------------+------------------+--------------+--------------------+-------------+
|foo                 |[Main, Indi...|[1777203, 1777203]|    [GBP, GBP]|            [CR, CR]|   [143, 143]|
+--------------------+--------------+------------------+--------------+--------------------+-------------+

我期望得到以下结果：

+--------------------+--------------+------------------+--------------+--------------------+-------------+
|            UserName|     explod   |    explod2       |explod3       |explod4             |explod5      |
+--------------------+--------------+------------------+--------------+--------------------+-------------+
|NNNNNNNNNNNNNNNNN...|      Main    |1777203           |    GBP      |     CR              |    143      |
|NNNNNNNNNNNNNNNNN...|Individual    |1777203           |    GBP      |     CR              |    143      |
----------------------------------------------------------------------------------------------------------

我尝试过横向视图：

sqlContext.sql("SELECT `UserName`, explod, explod2, explod3, explod4, explod5 FROM sourceDF
LATERAL VIEW explode(`col1`) sourceDF AS explod 
LATERAL VIEW explode(`col2`) explod AS explod2 
LATERAL VIEW explode(`col3`) explod2 AS explod3 
LATERAL VIEW explode(`col4`) explod3 AS explod4 
LATERAL VIEW explode(`col5`) explod4 AS explod5")

但是我得到了一个笛卡尔积，有很多重复。我已经尝试了相同的方法，使用带有列的方法分解所有列，但仍然得到很多重复项

.withColumn("col1", explode($"col1"))...

当然，我可以对最终的数据帧进行区分，但这不是一个完美的解决方案。有什么方法可以分解这些列而不得到所有这些副本吗？

谢啦！

Answer 1

如果您使用的是Spark 2.4.0或更高版本，< code>arrays_zip会使任务变得更容易

val df = Seq(
  ("foo",
   Seq("Main", "Individual"),
   Seq(1777203, 1777203),
   Seq("GBP", "GBP"),
   Seq("CR", "CR"),
   Seq(143, 143)))
  .toDF("UserName", "col1", "col2", "col3", "col4", "col5")

df.select($"UserName",
          explode(arrays_zip($"col1", $"col2", $"col3", $"col4", $"col5")))
  .select($"UserName", $"col.*")
  .show()

输出：

+--------+----------+-------+----+----+----+
|UserName|      col1|   col2|col3|col4|col5|
+--------+----------+-------+----+----+----+
|     foo|      Main|1777203| GBP|  CR| 143|
|     foo|Individual|1777203| GBP|  CR| 143|
+--------+----------+-------+----+----+----+