Scala

Question

我正在尝试在 Dataframe 映射函数内进行模式匹配 - 将行与具有嵌套大小写的行模式匹配 Class。此数据框是连接的结果，具有如下所示的架构。它有一些原始类型的列和 2 个复合列：

case class MyList(values: Seq[Integer])
case class MyItem(key1: String, key2: String, field1: Integer, group1: MyList, group2: MyList, field2: Integer)
val myLine1 = new MyItem ("MyKey01", "MyKey02", 1, new MyList(Seq(1)), new MyList(Seq(2)), 2)
val myLine2 = new MyItem ("YourKey01", "YourKey02", 2, new MyList(Seq(2,3)), new MyList(Seq(4,5)), 20)
val dfRaw = Seq(myLine1, myLine2).toDF
dfRaw.printSchema
dfRaw.show
val df2 = dfRaw.map(r => r match {
    case Row(key1: String, key2: String, field1: Integer, group1: MyList, group2: MyList, field2: Integer) => "Matched"
    case _ => "Un matched"
})
df2.show

我的问题是，在那个地图函数之后，我得到的只是 "Un matched":

root
 |-- key1: string (nullable = true)
 |-- key2: string (nullable = true)
 |-- field1: integer (nullable = true)
 |-- group1: struct (nullable = true)
 |    |-- values: array (nullable = true)
 |    |    |-- element: integer (containsNull = true)
 |-- group2: struct (nullable = true)
 |    |-- values: array (nullable = true)
 |    |    |-- element: integer (containsNull = true)
 |-- field2: integer (nullable = true)
+---------+---------+------+--------------------+--------------------+------+
|     key1|     key2|field1|              group1|              group2|field2|
+---------+---------+------+--------------------+--------------------+------+
|  MyKey01|  MyKey02|     1|   [WrappedArray(1)]|   [WrappedArray(2)]|     2|
|YourKey01|YourKey02|     2|[WrappedArray(2, 3)]|[WrappedArray(4, 5)]|    20|
+---------+---------+------+--------------------+--------------------+------+
df2: org.apache.spark.sql.Dataset[String] = [value: string]
+----------+
|     value|
+----------+
|Un matched|
|Un matched|
+----------+

如果我忽略 case 分支中的那两个结构列（将 group1: MyList, group2: MyList 替换为 _, _, 就可以了

case Row(key1: String, key2: String, field1: Integer, group1: MyList, group2: MyList, field2: Integer) => "Matched"

能否请您帮忙解决一下如何对该案例进行模式匹配class？谢谢！

Answer 1

struct 列在 spark

中被视为 org.apache.spark.sql.catalyst.expressions.GenericRowWithSchema

因此您必须将匹配大小写定义为

import org.apache.spark.sql.catalyst.expressions._
val df2 = dfRaw.map(r => r match {
    case Row(key1: String, key2: String, field1: Integer, group1: GenericRowWithSchema, group2: GenericRowWithSchema, field2: Integer) => "Matched"
    case _ => "Un matched"
})

并且使用通配符 (_) 定义匹配案例 因为 Scala 编译器将 org.apache.spark.sql.catalyst.expressions.GenericRowWithSchema 隐式计算为数据类型 。

如下定义 case 也应该有效 由于隐式评估的通配符

case Row(key1: String, key2: String, field1: Integer, group1, group2, field2: Integer) => "Matched"

Scala - Spark sql 结构上的行模式匹配

Scala - Spark sql row pattern matching on struct

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apache-spark