一.簡介
為了在Scala和Java API之間保持相當程度的一緻性，用于批處理和流傳輸的标準API省略了一些允許在Scala中進行高水準表達的功能。
如果想享受完整的Scala體驗，則可以選擇加入通過隐式轉換來增強Scala API的擴充。
要使用所有可用的擴充，隻需導入相應的擴充元件即可：
1.DataSet API
import org.apache.flink.api.scala.extensions._
2.DataStream API
import org.apache.flink.streaming.api.scala.extensions._
另外，也可以根據需要導入單個擴充。
二.擴充模式比對
通常，DataSet和DataStream API都不接受匿名模式比對函數來比對元組，案例類或集合，如下所示：
val data: DataSet[(Int, String, Double)] = // [...]
data.map {
case (id, name, temperature) => // [...]
// The previous line causes the following compilation error:
// "The argument types of an anonymous function must be fully known. (SLS 8.5)"
}
此擴充在DataSet和DataStream Scala API中引入了新方法，這些新方法在擴充API中具有一對一的對應關系。這些擴充方法支援匿名模式比對功能。
1.DataSet API
DataSet要專門使用此擴充，可以添加以下内容：
import org.apache.flink.api.scala.extensions.acceptPartialFunctions
2.DataStream API
DataStream要專門使用此擴充，可以添加以下内容：
import org.apache.flink.streaming.api.scala.extensions.acceptPartialFunctions
三.代碼案例
以下代碼片段顯示了如何一起使用這些擴充方法（與DataSet API一起使用）的示例：
package cn.extensions
import org.apache.flink.api.scala._
import org.apache.flink.api.scala.ExecutionEnvironment
/**
* Created by Administrator on 2020/5/29.
*/
case class Person(x: String, y: Int)
object Match {
def main(args: Array[String]): Unit = {
// 設定execution執行環境
val env = ExecutionEnvironment.getExecutionEnvironment
val text = "Apache Flink apache spark apache solr hbase hive flink kafka redis tachyon redis"
val persons = text.toLowerCase.split(" ").map(row => Person(row, 1))
import org.apache.flink.api.scala.extensions._
val ds = env.fromCollection(persons)
val result = ds.filterWith {
case Person(x, y) => y > 0
}.groupingBy{
case Person(x, _) => x
}.sum("y")
result.first(5).print()
}
}
異常報錯資訊：
Exception in thread "main" java.lang.UnsupportedOperationException: Aggregate does not support grouping with KeySelector functions, yet.
at org.apache.flink.api.scala.operators.ScalaAggregateOperator.translateToDataFlow(ScalaAggregateOperator.java:220)
at org.apache.flink.api.scala.operators.ScalaAggregateOperator.translateToDataFlow(ScalaAggregateOperator.java:55)
at org.apache.flink.api.java.operators.OperatorTranslation.translateSingleInputOperator(OperatorTranslation.java:148)
at org.apache.flink.api.java.operators.OperatorTranslation.translate(OperatorTranslation.java:102)
at org.apache.flink.api.java.operators.OperatorTranslation.translateSingleInputOperator(OperatorTranslation.java:146)
at org.apache.flink.api.java.operators.OperatorTranslation.translate(OperatorTranslation.java:102)
at org.apache.flink.api.java.operators.OperatorTranslation.translate(OperatorTranslation.java:63)
at org.apache.flink.api.java.operators.OperatorTranslation.translateToPlan(OperatorTranslation.java:52)
at org.apache.flink.api.java.ExecutionEnvironment.createProgramPlan(ExecutionEnvironment.java:955)
at org.apache.flink.api.java.ExecutionEnvironment.createProgramPlan(ExecutionEnvironment.java:922)
at org.apache.flink.api.java.LocalEnvironment.execute(LocalEnvironment.java:85)
at org.apache.flink.api.java.ExecutionEnvironment.execute(ExecutionEnvironment.java:816)
at org.apache.flink.api.java.DataSet.collect(DataSet.java:413)
at org.apache.flink.api.java.DataSet.print(DataSet.java:1652)
at org.apache.flink.api.scala.DataSet.print(DataSet.scala:1726)
at cn.extensions.Match$.main(Match.scala:29)
at cn.extensions.Match.main(Match.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:497)
at com.intellij.rt.execution.application.AppMain.main(AppMain.java:144)
可知是使用groupingWith導緻的，意思是不支援使用該擴充API，換回原來的groupWith即可：