Scala/Spark-如何获取所有子数组的第一个元素 [英] Scala/Spark - How to get first elements of all sub-arrays

问题描述

我在Spark中具有以下DataFrame(我正在使用Scala):

I have the following DataFrame in a Spark (I'm using Scala):

[[1003014, 0.95266926], [15, 0.9484202], [754, 0.94236785], [1029530, 0.880922], [3066, 0.7085166], [1066440, 0.69400793], [1045811, 0.663178], [1020059, 0.6274495], [1233982, 0.6112905], [1007801, 0.60937023], [1239278, 0.60044676], [1000088, 0.5789191], [1056268, 0.5747936], [1307569, 0.5676605], [10334513, 0.56592846], [930, 0.5446228], [1170206, 0.52525467], [300, 0.52473146], [2105178, 0.4972785], [1088572, 0.4815367]]

我想获得一个仅包含每个子数组的第一个Ints的数据框，如下所示:

I want to get a Dataframe with only first Ints of each sub-array, something like:

[1003014, 15, 754, 1029530, 3066, 1066440, ...]

因此，仅保留上面列出的数组的每个子数组x的 x [0] .

Keeping hence only the x[0] of each sub-array x of the Array listed above.

我是Scala的新手，无法找到合适的匿名地图功能.预先感谢您的帮助

I'm new to Scala, and couldn't find the right anonymous map function. Thanks in advance for any help

推荐答案

对于 Spark> = 2.4 ，您可以使用

For Spark >= 2.4, you can use Higher-Order Function transform with lambda function to extract the first element of each value array.

scala> df.show(false)

+----------------------------------------------------------------------------------------+
|arrays                                                                                  |
+----------------------------------------------------------------------------------------+
|[[1003014.0, 0.95266926], [15.0, 0.9484202], [754.0, 0.94236785], [1029530.0, 0.880922]]|
+----------------------------------------------------------------------------------------+

scala> df.select(expr("transform(arrays, x -> x[0])").alias("first_array_elements")).show(false)

+-----------------------------------+
|first_array_elements               |
+-----------------------------------+
|[1003014.0, 15.0, 754.0, 1029530.0]|
+-----------------------------------+

火花<2.4

分解初始数组，然后与 collect_list 聚合以收集每个子数组的第一个元素:

Explode the initial array and then aggregate with collect_list to collect the first element of each sub array:

df.withColumn("exploded_array", explode(col("arrays")))
  .agg(collect_list(col("exploded_array")(0)))
  .show(false)

如果数组包含结构而不是子数组，只需更改对结构元素使用点的访问方法即可:

In case the array contains structs and not sub-arrays, just change the accessing method using dots for struct elements:

val transfrom_expr = "transform(arrays, x -> x.canonical_id)"
df.select(expr(transfrom_expr).alias("first_array_elements")).show(false)

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