Modify a struct column in spark dataframe

问题

I have a pyspark dataframe which contains a column "student" as follows:

"student" : {
   "name" : "kaleem",
   "rollno" : "12"
}

Schema for this in dataframe is :

structType(List(
   name: String, 
   rollno: String))

I need to modify this column as

"student" : {
   "student_details" : {
         "name" : "kaleem",
         "rollno" : "12"
   }
}

Schema for this in dataframe must be :

structType(List(
  student_details: 
     structType(List(
         name: String, 
         rollno: String))
))

How to do this in spark?

回答1:

Use named_struct function to achieve this-

1. Read the json as column

val  data =
      """
        | {
        |   "student": {
        |       "name": "kaleem",
        |       "rollno": "12"
        |   }
        |}
      """.stripMargin
    val df = spark.read.json(Seq(data).toDS())
    df.show(false)
    println(df.schema("student"))

Output-

+------------+
|student     |
+------------+
|[kaleem, 12]|
+------------+

StructField(student,StructType(StructField(name,StringType,true), StructField(rollno,StringType,true)),true)

2. change the schema using named_struct

val processedDf = df.withColumn("student",
      expr("named_struct('student_details', student)")
    )
    processedDf.show(false)
    println(processedDf.schema("student"))

Output-

+--------------+
|student       |
+--------------+
|[[kaleem, 12]]|
+--------------+

StructField(student,StructType(StructField(student_details,StructType(StructField(name,StringType,true), StructField(rollno,StringType,true)),true)),false)

For python step#2 will work as is just remove val

回答2:

With a library called spark-hats - This library extends Spark DataFrame API with helpers for transforming fields inside nested structures and arrays of arbitrary levels of nesting., you can do a lot of these transformations.

scala> import za.co.absa.spark.hats.Extensions._

scala> df.printSchema
root
 |-- ID: string (nullable = true)

scala> val df2 = df.nestedMapColumn("ID", "ID", c => struct(c as alfa))

scala> df2.printSchema
root
 |-- ID: struct (nullable = false)
 |    |-- alfa: string (nullable = true)

scala> val df3 = df2.nestedMapColumn("ID.alfa", "ID.alfa", c => struct(c as "beta"))

scala> df3.printSchema
root
 |-- ID: struct (nullable = false)
 |    |-- alfa: struct (nullable = false)
 |    |    |-- beta: string (nullable = true)

Your query would be

df.nestedMapColumn("student", "student", c => struct(c as "student_details"))

来源：https://stackoverflow.com/questions/62050145/modify-a-struct-column-in-spark-dataframe