Question

我有这个模式，我想将结果的内部拆分为列，以便有col1：EventCode，col2：Message等...我正在使用Pyspark，我尝试了爆炸功能，但它没有'似乎在structType上工作，有没有办法在Spark中做到这一点？

root
 |-- result: struct (nullable = true)
 |    |-- EventCode: string (nullable = true)
 |    |-- Message: string (nullable = true)
 |    |-- _bkt: string (nullable = true)
 |    |-- _cd: string (nullable = true)
 |    |-- _indextime: string (nullable = true)
 |    |-- _pre_msg: string (nullable = true)
 |    |-- _raw: string (nullable = true)
 |    |-- _serial: string (nullable = true)
 |    |-- _si: array (nullable = true)
 |    |    |-- element: string (containsNull = true)
 |    |-- _sourcetype: string (nullable = true)
 |    |-- _time: string (nullable = true)
 |    |-- host: string (nullable = true)
 |    |-- index: string (nullable = true)
 |    |-- linecount: string (nullable = true)
 |    |-- source: string (nullable = true)
 |    |-- sourcetype: string (nullable = true)

Answer 1

将数据行划分为简单行很容易。您所要做的就是从数据框中选择所有列并将其分配给另一个数据帧。像这样：

simpleDF = df.select("result.*")

它会将上面给出的模式转换为以下模式：

simpleDF.printSchema

root
 |-- EventCode: string (nullable = true)
 |-- Message: string (nullable = true)
 |-- _bkt: string (nullable = true)
 |-- _cd: string (nullable = true)
 |-- _indextime: string (nullable = true)
 |-- _pre_msg: string (nullable = true)
 |-- _raw: string (nullable = true)
 |-- _serial: string (nullable = true)
 |-- _si: array (nullable = true)
 |    |-- element: string (containsNull = true)
 |-- _sourcetype: string (nullable = true)
 |-- _time: string (nullable = true)
 |-- host: string (nullable = true)
 |-- index: string (nullable = true)
 |-- linecount: string (nullable = true)
 |-- source: string (nullable = true)
 |-- sourcetype: string (nullable = true)

在Pyspark中将数据行划分为简单行

1 个答案: