横向视图/在spark中分解多个列，获得重复项

lrpiutwd 于 2021-05-29 发布在 Hadoop

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我有下面的dataframe和一些包含数组的列(我们使用的是spark 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      |
----------------------------------------------------------------------------------------------------------

我试过侧视图：

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")

但我得到一个笛卡尔积，有很多重复项。我也尝试过同样的方法，用withcolumn方法分解所有的列，但是仍然得到很多重复项

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

当然，我可以对最终的Dataframe进行区分，但这不是一个优雅的解决方案。有没有什么方法可以在不得到所有这些重复数据的情况下分解列？
谢谢！

hadoop Hive scala apache-spark xml

来源：https://stackoverflow.com/questions/56242598/lateral-view-explode-in-spark-with-multiple-columns-getting-duplicates

1条答案

按热度按时间

iyr7buue1#

如果您使用的是spark 2.4.0或更高版本， arrays_zip 使任务更容易

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|
+--------+----------+-------+----+----+----+

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横向视图/在spark中分解多个列，获得重复项

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