本文介绍了在 Spark 数据框中分解嵌套结构的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!
问题描述
我正在研究一个 Databricks 示例.数据框的架构如下所示:
I'm working through a Databricks example. The schema for the dataframe looks like:
> parquetDF.printSchema
root
|-- department: struct (nullable = true)
| |-- id: string (nullable = true)
| |-- name: string (nullable = true)
|-- employees: array (nullable = true)
| |-- element: struct (containsNull = true)
| | |-- firstName: string (nullable = true)
| | |-- lastName: string (nullable = true)
| | |-- email: string (nullable = true)
| | |-- salary: integer (nullable = true)
在示例中,他们展示了如何将员工列分解为 4 个附加列:
In the example, they show how to explode the employees column into 4 additional columns:
val explodeDF = parquetDF.explode($"employees") {
case Row(employee: Seq[Row]) => employee.map{ employee =>
val firstName = employee(0).asInstanceOf[String]
val lastName = employee(1).asInstanceOf[String]
val email = employee(2).asInstanceOf[String]
val salary = employee(3).asInstanceOf[Int]
Employee(firstName, lastName, email, salary)
}
}.cache()
display(explodeDF)
我将如何对部门列执行类似的操作(即向名为id"和name"的数据框添加两个额外的列)?方法并不完全相同,我只能弄清楚如何使用以下方法创建全新的数据框:
How would I do something similar with the department column (i.e. add two additional columns to the dataframe called "id" and "name")? The methods aren't exactly the same, and I can only figure out how to create a brand new data frame using:
val explodeDF = parquetDF.select("department.id","department.name")
display(explodeDF)
如果我尝试:
val explodeDF = parquetDF.explode($"department") {
case Row(dept: Seq[String]) => dept.map{dept =>
val id = dept(0)
val name = dept(1)
}
}.cache()
display(explodeDF)
我收到警告和错误:
<console>:38: warning: non-variable type argument String in type pattern Seq[String] is unchecked since it is eliminated by erasure
case Row(dept: Seq[String]) => dept.map{dept =>
^
<console>:37: error: inferred type arguments [Unit] do not conform to method explode's type parameter bounds [A <: Product]
val explodeDF = parquetDF.explode($"department") {
^
推荐答案
你可以这样使用:
var explodeDF = explodeDF.withColumn("id", explodeDF("department.id"))
explodeDeptDF = explodeDeptDF.withColumn("name", explodeDeptDF("department.name"))
你帮助我解决了这些问题:
which you helped me into and these questions:
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