Apache spark: Write JSON DataFrame partitionBy nested columns

Question

I have this kind of JSON data:

{
 "data": [
    {
      "id": "4619623",
      "team": "452144",
      "created_on": "2018-10-09 02:55:51",
      "links": {
        "edit": "https://some_page",
        "publish": "https://some_publish",
        "default": "https://some_default"
      }
    },
    {
      "id": "4619600",
      "team": "452144",
      "created_on": "2018-10-09 02:42:25",
      "links": {
        "edit": "https://some_page",
        "publish": "https://some_publish",
        "default": "https://some_default"
      }
    }
}

I read this data using Apache spark and I want to write them partition by id column. When I use this: df.write.partitionBy("data.id").json(<path_to_folder>)

I will get error:
Exception in thread "main" org.apache.spark.sql.AnalysisException: Partition column data.id not found in schema

I also tried to use explode function like that:

import org.apache.spark.sql.functions.{col, explode}
val renamedDf= df.withColumn("id", explode(col("data.id")))
renamedDf.write.partitionBy("id").json(<path_to_folder>)

That actually helped, but each id partition folder contained the same original JSON file.

EDIT: schema of df DataFrame:

 |-- data: array (nullable = true)
 |    |-- element: struct (containsNull = true)
 |    |    |-- created_on: string (nullable = true)
 |    |    |-- id: string (nullable = true)
 |    |    |-- links: struct (nullable = true)
 |    |    |    |-- default: string (nullable = true)
 |    |    |    |-- edit: string (nullable = true)
 |    |    |    |-- publish: string (nullable = true)

Schema of renamedDf DataFrame:

 |-- data: array (nullable = true)
 |    |-- element: struct (containsNull = true)
 |    |    |-- created_on: string (nullable = true)
 |    |    |-- id: string (nullable = true)
 |    |    |-- links: struct (nullable = true)
 |    |    |    |-- default: string (nullable = true)
 |    |    |    |-- edit: string (nullable = true)
 |    |    |    |-- publish: string (nullable = true)
 |-- id: string (nullable = true)

I am using spark 2.1.0

I found this solution: DataFrame partitionBy on nested columns

And this example:http://bigdatums.net/2016/02/12/how-to-extract-nested-json-data-in-spark/

But none of this helped me to solve my problem.

Thanks in andvance for any help.

Answer 1

try the following code:

val renamedDf = df
         .select(explode(col("data")) as "x" )
         .select($"x.*")             
renamedDf.write.partitionBy("id").json(<path_to_folder>)