Question

我在Scala中具有以下功能：

  def getData(spark: SparkSession,
              indices: Option[String]): Option[DataFrame] = {

    indices match {
      case None => {
        println("Undefined field.")
        None
      }
      case Some(ind) => {
        val df = spark
          .read.format("org.elasticsearch.spark.sql")
          .load(ind)
        df
      }
    }
}

但是，出现编译错误：

类型sql.DataFrame的表达式不符合预期的类型选项[sql.DataFrame]

我试图返回Option[df]，但是它都不会编译。

Answer 1

将您的Array //1st_array ( [0] => Array ( [timestamp] => 7/10/2018 15:24:06 [username] => giakhang [status] => Yes ) [1] => Array ( [timestamp] => 8/10/2018 5:11:25 [username] => haophan [status] => No ) [2] => Array ( [timestamp] => 8/10/2018 6:38:18 [username] => TTQ1504 [status] => No ) [3] => Array ( [timestamp] => 08/10/2018 7:04:20 [username] => btcgainer24724 [status] => Yes ) ) Array //2nd_array ( [0] => Array ( [timestamp] => 8/10/2018 5:10:06 [username] => giakhang ) [1] => Array ( [timestamp] => 8/10/2018 5:13:25 [username] => btcgainer24724 ) )换成df：

Some

Answer 2

您返回了错误的类型：

class MyComponent extend React.Component {
   constructor(props) {
      super(props);
      this.state = {
         isNavigationBlocked: false;
      }
   }

   render(){ 
      return (<div>
      <Prompt when={this.state.isNavigationBlocked}/>
      </div>)
   }
}

或更惯用

  def getData(spark: SparkSession,
              indices: Option[String]): Option[DataFrame] = {

    indices match {
      case None => {
        println("Undefined field.")
        None
      }
      case Some(ind) => {
        val df = spark
          .read.format("org.elasticsearch.spark.sql")
          .load(ind)
        Some(df) // <- Here!!!
      }
    }
}

类型sql.DataFrame的表达式不符合预期的类型Option [sql.DataFrame]

2 个答案: