python - Pyspark:将具有嵌套结构的数组转换为字符串

Question

我有一个名为 Filters 的 pyspark 数据框: “数组>”

我想将我的数据框保存在 csv 文件中，为此我需要将数组转换为字符串类型。

我尝试转换它:DF.Filters.tostring() 和 DF.Filters.cast(StringType())，但是这两种解决方案都会为每个解决方案生成错误消息列过滤器中的行:

org.apache.spark.sql.catalyst.expressions.UnsafeArrayData@56234c19

代码如下

from pyspark.sql.types import StringType

DF.printSchema()

|-- ClientNum: string (nullable = true)
|-- Filters: array (nullable = true)
    |-- element: struct (containsNull = true)
          |-- Op: string (nullable = true)
          |-- Type: string (nullable = true)
          |-- Val: string (nullable = true)

DF_cast = DF.select ('ClientNum',DF.Filters.cast(StringType())) 

DF_cast.printSchema()

|-- ClientNum: string (nullable = true)
|-- Filters: string (nullable = true)

DF_cast.show()

| ClientNum | Filters 
|  32103    | org.apache.spark.sql.catalyst.expressions.UnsafeArrayData@d9e517ce
|  218056   | org.apache.spark.sql.catalyst.expressions.UnsafeArrayData@3c744494

示例 JSON 数据:

{"ClientNum":"abc123","Filters":[{"Op":"foo","Type":"bar","Val":"baz"}]}

谢谢!!

Answer 1

我创建了一个示例 JSON 数据集来匹配该模式:

{"ClientNum":"abc123","Filters":[{"Op":"foo","Type":"bar","Val":"baz"}]}

select(s.col("ClientNum"),s.col("Filters").cast(StringType)).show(false)

+---------+------------------------------------------------------------------+
|ClientNum|Filters                                                           |
+---------+------------------------------------------------------------------+
|abc123   |org.apache.spark.sql.catalyst.expressions.UnsafeArrayData@60fca57e|
+---------+------------------------------------------------------------------+

最好使用展开数组的 explode() 函数解决您的问题，然后使用星号扩展符号:

s.selectExpr("explode(Filters) AS structCol").selectExpr("structCol.*").show()
+---+----+---+
| Op|Type|Val|
+---+----+---+
|foo| bar|baz|
+---+----+---+

要使其成为以逗号分隔的单列字符串:

s.selectExpr("explode(Filters) AS structCol").select(F.expr("concat_ws(',', structCol.*)").alias("single_col")).show()
+-----------+
| single_col|
+-----------+
|foo,bar,baz|
+-----------+

分解数组引用:Flattening Rows in Spark

“结构”类型的星号扩展引用:How to flatten a struct in a spark dataframe?