java-通过apache spark将行作为列表进行分组

我有一个特殊的用例,其中我为同一位客户有多行,每行对象看起来像：

root
 -c1: BigInt
 -c2: String
 -c3: Double
 -c4: Double
 -c5: Map[String, Int]

现在,我按列c1进行分组,并为同一客户收集所有行作为列表,例如：

c1, [Row1, Row3, Row4]
c2, [Row2, Row5]

我试图这样做
dataset.withColumn(“ combined”,array(“ c1”,“ c2”,“ c3”,“ c4”,“ c5”)).groupBy(“ c1”).agg(collect_list(“ combined”))但我得到一个例外：

Exception in thread "main" org.apache.spark.sql.AnalysisException: cannot resolve 'array(`c1`, `c2`, `c3`, `c4`, `c5`)' due to data type mismatch: input to function array should all be the same type, but it's [bigint, string, double, double, map<string,map<string,double>>];;

解决方法:

您可以使用struct函数合并列,而不使用array,并使用groupBy和collect_list聚合函数

import org.apache.spark.sql.functions._
df.withColumn("combined", struct("c1","c2","c3","c4","c5"))
    .groupBy("c1").agg(collect_list("combined").as("combined_list"))
    .show(false)

这样就可以将数据集与架构分组为

root
 |-- c1: integer (nullable = false)
 |-- combined_list: array (nullable = true)
 |    |-- element: struct (containsNull = true)
 |    |    |-- c1: integer (nullable = false)
 |    |    |-- c2: string (nullable = true)
 |    |    |-- c3: string (nullable = true)
 |    |    |-- c4: string (nullable = true)
 |    |    |-- c5: map (nullable = true)
 |    |    |    |-- key: string
 |    |    |    |-- value: integer (valueContainsNull = false)

我希望答案是有帮助的

标签：scala,apache-spark,apache-spark-sql,spark-streaming,java
来源： https://codeday.me/bug/20191025/1925983.html