添加父列名称作为前缀以避免歧义

如何解决添加父列名称作为前缀以避免歧义

检查以下代码。如果存在重复的密钥，它将生成含糊不清的数据帧。我们应该如何修改代码以添加父列名称作为前缀。

添加了另一列包含json数据。

scala> val df = Seq(
    (77,"email1","""{"key1":38,"key3":39}""","""{"name":"aaa","age":10}"""),(78,"email2","key4":39}""","""{"name":"bbb","age":20}"""),(178,"email21","""{"key1":"when string","key4":36,"key6":"test","key10":false }""","""{"name":"ccc","age":30}"""),(179,"email8","""{"sub1":"qwerty","sub2":["42"]}""","""{"name":"ddd","age":40}"""),(180,"sub2":["42","56","test"]}""","""{"name":"eee","age":50}""")
).toDF("id","name","colJson","personInfo")

scala> df.printSchema
root
 |-- id: integer (nullable = false)
 |-- name: string (nullable = true)
 |-- colJson: string (nullable = true)
 |-- personInfo: string (nullable = true)

scala> df.show(false)
+---+-------+---------------------------------------------------------------+-----------------------+
|id |name   |colJson                                                        |personInfo             |
+---+-------+---------------------------------------------------------------+-----------------------+
|77 |email1 |{"key1":38,"key3":39}                                          |{"name":"aaa","age":10}|
|78 |email2 |{"key1":38,"key4":39}                                          |{"name":"bbb","age":20}|
|178|email21|{"key1":"when string","key10":false }|{"name":"ccc","age":30}|
|179|email8 |{"sub1":"qwerty","sub2":["42"]}                                |{"name":"ddd","age":40}|
|180|email8 |{"sub1":"qwerty","test"]}                  |{"name":"eee","age":50}|
+---+-------+---------------------------------------------------------------+-----------------------+

创建了 fromJson 隐式函数，您可以将多个列传递给此＆它将解析并从json中提取列。

scala> :paste
// Entering paste mode (ctrl-D to finish)

import org.apache.spark.sql.{Column,DataFrame,Row}
    import org.apache.spark.sql.functions.from_json
    implicit class DFHelper(inDF: DataFrame) {
      import inDF.sparkSession.implicits._
      def fromJson(columns:Column*):DataFrame = {
        val schemas = columns.map(column => (column,inDF.sparkSession.read.json(inDF.select(column).as[String]).schema))
        val mdf = schemas.foldLeft(inDF)((df,schema) => {
                df.withColumn(schema._1.toString(),from_json(schema._1,schema._2))
        })        
        mdf.selectExpr(mdf.schema.map(c => if(c.dataType.typeName =="struct") s"${c.name}.*" else c.name):_*)
      }
    }

// Exiting paste mode,now interpreting.

import org.apache.spark.sql.{Column,Row}
import org.apache.spark.sql.functions.from_json
defined class DFHelper

scala> df.fromJson($"colJson",$"personInfo").show(false)

+---+-------+-----------+-----+----+----+----+------+--------------+---+----+
|id |name   |key1       |key10|key3|key4|key6|sub1  |sub2          |age|name|
+---+-------+-----------+-----+----+----+----+------+--------------+---+----+
|77 |email1 |38         |null |39  |null|null|null  |null          |10 |aaa |
|78 |email2 |38         |null |null|39  |null|null  |null          |20 |bbb |
|178|email21|when string|false|null|36  |test|null  |null          |30 |ccc |
|179|email8 |null       |null |null|null|null|qwerty|[42]          |40 |ddd |
|180|email8 |null       |null |null|null|null|qwerty|[42,56,test]|50 |eee |
+---+-------+-----------+-----+----+----+----+------+--------------+---+----+

scala> df.fromJson($"colJson",$"personInfo").printSchema()
root
 |-- id: integer (nullable = false)
 |-- name: string (nullable = true)
 |-- key1: string (nullable = true)
 |-- key10: boolean (nullable = true)
 |-- key3: long (nullable = true)
 |-- key4: long (nullable = true)
 |-- key6: string (nullable = true)
 |-- sub1: string (nullable = true)
 |-- sub2: array (nullable = true)
 |    |-- element: string (containsNull = true)
 |-- age: long (nullable = true)
 |-- name: string (nullable = true)

解决方法

试试这个-

<form action = "s{{url_for('success')}}" methods="POST">

<form action = "{{url_for('success')}}" method="POST">

  df.show(false)
    df.printSchema()
    /**
      * +---+-------+---------------------------------------------------------------+-----------------------+
      * |id |name   |colJson                                                        |personInfo             |
      * +---+-------+---------------------------------------------------------------+-----------------------+
      * |77 |email1 |{"key1":38,"key3":39}                                          |{"name":"aaa","age":10}|
      * |78 |email2 |{"key1":38,"key4":39}                                          |{"name":"bbb","age":20}|
      * |178|email21|{"key1":"when string","key4":36,"key6":"test","key10":false }|{"name":"ccc","age":30}|
      * |179|email8 |{"sub1":"qwerty","sub2":["42"]}                                |{"name":"ddd","age":40}|
      * |180|email8 |{"sub1":"qwerty","sub2":["42","56","test"]}                  |{"name":"eee","age":50}|
      * +---+-------+---------------------------------------------------------------+-----------------------+
      *
      * root
      * |-- id: integer (nullable = false)
      * |-- name: string (nullable = true)
      * |-- colJson: string (nullable = true)
      * |-- personInfo: string (nullable = true)
      *
      * @param inDF
      */