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Pyspark:将具有嵌套结构的数组转换为字符串

sql

我有pyspark数据框,其中包含名为 Filters 的列:“ array>”

我想将数据帧保存在csv文件中,为此,我需要将数组转换为字符串类型。

我尝试将其强制转换为:DF.Filters.tostring()DF.Filters.cast(StringType()),但是这两种解决方案都会为“过滤器”列中的每一行生成错误消息:

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

样本JSON数据:

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

谢谢 !!


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2021-03-10

共1个答案

小编典典

我创建了一个样本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|
+---------+------------------------------------------------------------------+

使用explode()函数可以最佳化解决您的问题,该函数可以展平数组,然后使用星号扩展表示法:

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

使其成为由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|
+-----------+
2021-03-10