如何将一行数组平面映射为多行? [英] How do I flatMap a row of arrays into multiple rows?

问题描述

解析一些jsons后，我有一个一列的数组DataFrame

After parsing some jsons I have a one-column DataFrame of arrays

scala> val jj =sqlContext.jsonFile("/home/aahu/jj2.json")
res68: org.apache.spark.sql.DataFrame = [r: array<bigint>]
scala> jj.first()
res69: org.apache.spark.sql.Row = [List(0, 1, 2, 3, 4, 5, 6, 7, 8, 9)]

我想将每一行分解成几行.怎么样?

I'd like to explode each row out into several rows. How?

原始json文件:

{"r": [0,1,2,3,4,5,6,7,8,9]}
{"r": [0,1,2,3,4,5,6,7,8,9]}

我想要一个 20 行的 RDD 或 DataFrame.

I want an RDD or a DataFrame with 20 rows.

我不能在这里简单地使用 flatMap - 我不确定 spark 中合适的命令是什么:

I can't simply use flatMap here - I'm not sure what the appropriate command in spark is:

scala> jj.flatMap(r => r)
<console>:22: error: type mismatch;
 found   : org.apache.spark.sql.Row
 required: TraversableOnce[?]
              jj.flatMap(r => r)

推荐答案

您可以使用 DataFrame.explode 来实现您的愿望.以下是我在 spark-shell 中使用您的示例 json 数据尝试的内容.

You can use DataFrame.explode to achieve what you desire. Below is what I tried in spark-shell with your sample json data.

import scala.collection.mutable.ArrayBuffer
val jj1 = jj.explode("r", "r1") {list : ArrayBuffer[Long] => list.toList }
val jj2 = jj1.select($"r1")
jj2.collect

可以参考API文档了解更多DataFrame.explode

You can refer to API documentation to understand more DataFrame.explode

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