在 Pyspark SQL 中展开 JSON

Question

我希望将嵌套的 json 分解为 CSV 文件。 希望将嵌套的 json 解析为行和列。

from pyspark.sql import SparkSession
from pyspark.sql import SQLContext
from pyspark.sql.types import *
from pyspark.sql import functions as F
from pyspark.sql import Row
df=spark.read.option("multiline","true").json("sample1.json")
df.printSchema()

root
 |-- pid: struct (nullable = true)
 |    |-- Body: struct (nullable = true)
 |    |    |-- Vendor: struct (nullable = true)
 |    |    |    |-- RC: struct (nullable = true)
 |    |    |    |    |-- Updated_From_Date: string (nullable = true)
 |    |    |    |    |-- Updated_To_Date: string (nullable = true)
 |    |    |    |-- RD: struct (nullable = true)
 |    |    |    |    |-- Supplier: struct (nullable = true)
 |    |    |    |    |    |-- Supplier_Data: struct (nullable = true)
 |    |    |    |    |    |    |-- Days: long (nullable = true)
 |    |    |    |    |    |    |-- Reference: struct (nullable = true)
 |    |    |    |    |    |    |    |-- ID: array (nullable = true)
 |    |    |    |    |    |    |    |    |-- element: string (containsNull = true)
 |    |    |    |    |    |    |-- Expected: long (nullable = true)
 |    |    |    |    |    |    |-- Payments: long (nullable = true)
 |    |    |    |    |    |    |-- Approval: struct (nullable = true)
 |    |    |    |    |    |    |    |-- ID: array (nullable = true)
 |    |    |    |    |    |    |    |    |-- element: string (containsNull = true)
 |    |    |    |    |    |    |-- Areas_Changed: struct (nullable = true)
 |    |    |    |    |    |    |    |-- Alternate_Names: long (nullable = true)
 |    |    |    |    |    |    |    |-- Attachments: long (nullable = true)
 |    |    |    |    |    |    |    |-- Classifications: long (nullable = true)
 |    |    |    |    |    |    |    |-- Contact_Information: long (nullable = true)

我的代码：

df2=(df.select(F.explode("pid").alias('pid'))
         .select('pid.*')
         .select(F.explode('Body').alias('Body'))
         .select('Body.*')
         .select((F.explode('Vendor').alias('Vendor'))
         .select('Vendor.*')
         .select((F.explode('RC').alias('RC'))
         .select('RC.*'))))

错误： AnalysisException: 由于数据类型不匹配，无法解析“explode(pid)”：函数explode 的输入应该是数组或映射类型，而不是struct

如何解析为结构字段。 任何帮助将不胜感激:)

Answer 1

您只能在映射或数组类型上使用explode 函数。要访问 strcut 类型，只需使用 . 运算符。

假设你想获取 RC 和 RD 下的列，那么代码语法应该如下所示。

df.select("pid.Body.Vendor.RC.*", "pid.Body.Vendor.RD.*")