Spark：Union只能在具有兼容列类型的表上执行,Struct< name，id>！= Struct< id，name>

zzlelutf  于 2023-06-24  发布在  Apache
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错误：只能对具有兼容列类型的表执行联合。**struct（tier：string，skyward_number：string，skyward_points：string）<> struct（skyward_number：string，tier：string，skyward_points：string）**在第二表的第一列;;
这里结构体字段的顺序是不同的，但其余的都是相同的。
dataframe 1架构

root
 |-- emcg_uuid: string (nullable = true)
 |-- name: string (nullable = true)
 |-- phone_no: string (nullable = true)
 |-- dob: string (nullable = true)
 |-- country: string (nullable = true)
 |-- travel_type: string (nullable = true)
 |-- gdpr_restricted_flg: string (nullable = false)
 |-- gdpr_reason_code: string (nullable = false)
 |-- document: map (nullable = true)
 |    |-- key: string
 |    |-- value: string (valueContainsNull = true)
 |-- skyward: struct (nullable = false)
 |    |-- tier: string (nullable = false)
 |    |-- skyward_number: string (nullable = false)
 |    |-- skyward_points: string (nullable = false)

dataframe2 schema
root
 |-- emcg_uuid: string (nullable = true)
 |-- name: string (nullable = true)
 |-- phone_no: string (nullable = true)
 |-- dob: string (nullable = true)
 |-- country: string (nullable = true)
 |-- travel_type: string (nullable = true)
 |-- gdpr_restricted_flg: string (nullable = true)
 |-- gdpr_reason_code: string (nullable = true)
 |-- document: map (nullable = true)
 |    |-- key: string
 |    |-- value: string (valueContainsNull = true)
 |-- skyward: struct (nullable = false)
 |    |-- skyward_number: string (nullable = false)
 |    |-- tier: string (nullable = false)
 |    |-- skyward_points: string (nullable = false)

如何解决这个问题？

apache-spark

4条答案

按热度按时间
8fq7wneg

8fq7wneg1#

union的默认Spark行为是标准的SQL行为，所以是按位置匹配。这意味着，两个DataFrame中的模式必须包含相同的字段，并且相同的字段具有相同的顺序。
如果你想通过名称匹配schema，可以使用Spark 2.3中引入的unionByName。
您也可以重新Map字段：

val df1 = ...
val df2 = /...
df1.toDF(df2.columns: _*).union(df2)

编辑：我现在看到编辑了。
您可以再次添加这些列：

import org.apache.spark.sql.functions._
val withCorrectedStruct = df1.withColumn("skyward", struct($"skyward_number", $"tier", $"skyward_points"))
赞(0）分享  回复(0）举报  2023-06-24
tmb3ates

tmb3ates2#

//preserves the order the columns while doing union
  def getStructRecursiveDataFrame(df1 : DataFrame, df2 : DataFrame,columns : Array[String]) : DataFrame = {
    if(columns.isEmpty) {
      df2
    }
    else {
      println("test")
      val col_name = columns.head
      val col_schema = df1.schema.fields.find(_.name == col_name).get
      if(col_schema.dataType.typeName.equals("struct")){
        println("test1")
        val updatedStructNames: Seq[Column] = col_schema.dataType.asInstanceOf[StructType].fieldNames.map(name => col(col_name+"." + name))
        getStructRecursiveDataFrame(df1,df2.withColumn(col_name, struct(updatedStructNames: _*)),columns.tail)
      }
      else{ getStructRecursiveDataFrame(df1,df2,columns.tail)}
    }
  }

  def unionByName(a:  org.apache.spark.sql.DataFrame, b:  org.apache.spark.sql.DataFrame):  org.apache.spark.sql.DataFrame = {

    val b_new_df = getStructRecursiveDataFrame(a,b,a.columns)
    val columns_seq = a.columns.toSet.intersect(b_new_df.columns.toSet).map(col).toSeq
    a.select(columns_seq: _*).union(b_new_df.select(columns_seq: _*))
  }

成果

[INFO] DATAFRAME-1 SCHEME
root
 |-- emcg_uuid: string (nullable = true)
 |-- name: string (nullable = true)
 |-- phone_no: string (nullable = true)
 |-- dob: string (nullable = true)
 |-- country: string (nullable = true)
 |-- travel_type: string (nullable = true)
 |-- gdpr_restricted_flg: string (nullable = false)
 |-- gdpr_reason_code: string (nullable = false)
 |-- document: map (nullable = true)
 |    |-- key: string
 |    |-- value: string (valueContainsNull = true)
 |-- skyward: struct (nullable = false)
 |    |-- tier: string (nullable = false)
 |    |-- skyward_number: string (nullable = false)
 |    |-- skyward_points: string (nullable = false)

[INFO] DATAFRAME-2 SCHEME
root
 |-- emcg_uuid: string (nullable = true)
 |-- name: string (nullable = true)
 |-- phone_no: string (nullable = true)
 |-- dob: string (nullable = true)
 |-- country: string (nullable = true)
 |-- travel_type: string (nullable = true)
 |-- gdpr_restricted_flg: string (nullable = true)
 |-- gdpr_reason_code: string (nullable = true)
 |-- document: map (nullable = true)
 |    |-- key: string
 |    |-- value: string (valueContainsNull = true)
 |-- skyward: struct (nullable = false)
 |    |-- skyward_number: string (nullable = false)
 |    |-- tier: string (nullable = false)
 |    |-- skyward_points: string (nullable = false)

[INFO] DATAFRAME SCHEME AFTER THE UNION
root
 |-- skyward: struct (nullable = false)
 |    |-- skyward_number: string (nullable = false)
 |    |-- tier: string (nullable = false)
 |    |-- skyward_points: string (nullable = false)
 |-- name: string (nullable = true)
 |-- document: map (nullable = true)
 |    |-- key: string
 |    |-- value: string (valueContainsNull = true)
 |-- phone_no: string (nullable = true)
 |-- travel_type: string (nullable = true)
 |-- gdpr_restricted_flg: string (nullable = true)
 |-- dob: string (nullable = true)
 |-- gdpr_reason_code: string (nullable = true)
 |-- country: string (nullable = true)
 |-- emcg_uuid: string (nullable = true)

[INFO] TEST CASE FOR ANONYMIZATION VALIDATION
[INFO] INPUT DATA
+----+----------+-----------+-------------------+----------+----------------+-------+---------+-------------------------------------------+-----------------+
|name|phone_no  |travel_type|gdpr_restricted_flg|dob       |gdpr_reason_code|country|emcg_uuid|document                                   |skyward          |
+----+----------+-----------+-------------------+----------+----------------+-------+---------+-------------------------------------------+-----------------+
|ravi|8747436090|freq       |                   |1988-05-28|                |dubai  |uuid_1   |Map(document_type -> passport, id -> A3343)|[123456,blue,687]|
|aaaa|8747436091|freg       |                   |1988-06-25|                |europe |uuid_2   |Map(document_type -> passport, id -> A3341)|[123456,blue,687]|
|bbbb|8747436092|reg        |                   |1988-07-26|                |india  |uuid_3   |Map(document_type -> passport, id -> A3345)|[123456,blue,687]|
|cccc|8747436093|na         |                   |1988-08-27|                |georgia|uuid_4   |Map(document_type -> passport, id -> A3349)|[123456,blue,687]|
|dddd|8747436094|na         |                   |1988-09-29|                |swis   |uuid_5   |Map(document_type -> passport, id -> B3343)|[123456,blue,687]|
|null|8747436095|freq       |                   |1988-02-30|                |us     |uuid_6   |Map(document_type -> passport, id -> C3343)|[123456,blue,687]|
|null|8747436096|na         |                   |1988-01-01|                |canada |uuid_7   |Map(document_type -> null, id -> D3343)    |[123456,blue,687]|
+----+----------+-----------+-------------------+----------+----------------+-------+---------+-------------------------------------------+-----------------+

[INFO] EXPECTED OUTPUT
+-------+----------+-----------+-------------------+----------+----------------+-------+---------+-------------------------------------------+-----------------+
|name   |phone_no  |travel_type|gdpr_restricted_flg|dob       |gdpr_reason_code|country|emcg_uuid|document                                   |skyward          |
+-------+----------+-----------+-------------------+----------+----------------+-------+---------+-------------------------------------------+-----------------+
|DDDDDDD|9999999   |freq       |Y                  |1988-05-XX|13-001          |XXXXXXX|uuid_1   |Map(document_type -> ZZZZZ, id -> HH343)   |[123456,blue,687]|
|aaaa   |8747436091|freg       |                   |1988-06-25|                |europe |uuid_2   |Map(document_type -> passport, id -> A3341)|[123456,blue,687]|
|DDDDDDD|9999999   |reg        |Y                  |1988-07-XX|13-001          |XXXXXXX|uuid_3   |Map(document_type -> ZZZZZ, id -> HH345)   |[123456,blue,687]|
|cccc   |8747436093|na         |                   |1988-08-27|                |georgia|uuid_4   |Map(document_type -> passport, id -> A3349)|[123456,blue,687]|
|dddd   |8747436094|na         |                   |1988-09-29|                |swis   |uuid_5   |Map(document_type -> passport, id -> B3343)|[123456,blue,687]|
|null   |8747436095|freq       |                   |1988-02-30|                |us     |uuid_6   |Map(document_type -> passport, id -> C3343)|[123456,blue,687]|
|null   |9999999   |na         |Y                  |1988-01-XX|13-001          |XXXXXXX|uuid_7   |Map(document_type -> null, id -> HH343)    |[123456,blue,687]|
+-------+----------+-----------+-------------------+----------+----------------+-------+---------+-------------------------------------------+-----------------+

[INFO] ACTUAL OUTPUT
+-------+----------+-----------+-------------------+----------+----------------+-------+---------+-------------------------------------------+-----------------+
|name   |phone_no  |travel_type|gdpr_restricted_flg|dob       |gdpr_reason_code|country|emcg_uuid|document                                   |skyward          |
+-------+----------+-----------+-------------------+----------+----------------+-------+---------+-------------------------------------------+-----------------+
|DDDDDDD|9999999   |freq       |Y                  |1988-05-XX|13-001          |XXXXXXX|uuid_1   |Map(document_type -> ZZZZZ, id -> HH343)   |[UUUUU,blue,JJ7] |
|aaaa   |8747436091|freg       |                   |1988-06-25|                |europe |uuid_2   |Map(document_type -> passport, id -> A3341)|[123456,blue,687]|
|DDDDDDD|9999999   |reg        |Y                  |1988-07-XX|13-001          |XXXXXXX|uuid_3   |Map(document_type -> ZZZZZ, id -> HH345)   |[UUUUU,blue,JJ7] |
|cccc   |8747436093|na         |                   |1988-08-27|                |georgia|uuid_4   |Map(document_type -> passport, id -> A3349)|[123456,blue,687]|
|dddd   |8747436094|na         |                   |1988-09-29|                |swis   |uuid_5   |Map(document_type -> passport, id -> B3343)|[123456,blue,687]|
|null   |8747436095|freq       |                   |1988-02-30|                |us     |uuid_6   |Map(document_type -> passport, id -> C3343)|[123456,blue,687]|
|null   |9999999   |na         |Y                  |1988-01-XX|13-001          |XXXXXXX|uuid_7   |Map(document_type -> null, id -> HH343)    |[UUUUU,blue,JJ7] |
+-------+----------+-----------+-------------------+----------+----------------+-------+---------+-------------------------------------------+-----------------+
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k4aesqcs

k4aesqcs3#

如果只有一个字段不同，并且名称已知（“skyward”），则可以解析为：

val data = List(("1", "2", "3"))
val bulkDF = data.toDF("emcg_uuid", "tier", "skyward_number")

// union parts
val tsDF = bulkDF.withColumn("skyward", struct($"tier", $"skyward_number"))
val stDF = bulkDF.withColumn("skyward", struct($"skyward_number", $"tier"))

// change struct "skyward" in last stDF
val schema = tsDF.schema.fields.find(_.name == "skyward").get
val updatedStructNames: Seq[Column] = schema.dataType.asInstanceOf[StructType].fieldNames.map(name => col("skyward." + name))
val withUpdatedSchema = stDF.withColumn("skyward", struct(updatedStructNames: _*))

// union
tsDF.union(withUpdatedSchema).show(false)

对于许多这样的结构字段，可以只使用一些循环。

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ryevplcw

ryevplcw4#

我遇到了同样的问题“错误：只能对具有兼容列类型的表执行联合。
调查了以下可能导致该问题的可能性。

  1. dataset 1和dataset 2之间的模式不匹配-我的情况是匹配。
  2. dataset 1和dataset 2之间的列顺序-列顺序不匹配导致了问题。为了按照以下步骤维持数据集1和数据集2中的列顺序，
    打印dataset 1和dataset 2的模式，以了解dataset 1的当前列顺序，根据dataset 2对齐dataset 1的列，反之亦然。示例：datset 1（column 2，column 1）dataset 2（column 1，column 1）datset1.select（“column 1”，“column 2”））.union（dataset 2）-将排列列并解决问题。
赞(0）分享  回复(0）举报  2023-06-24
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