Question

在角度4中，我有一个嵌套在另一个内部的组件。内部或子组件包含：按钮，输入和下拉列表在父页面上，当我单击按钮时，将显示输入和下拉列表。

单击按钮时设置输入焦点的好方法是什么？

到目前为止我尝试了什么：
在子组件中，我在输入中添加了一个id：println，然后在按下按钮时触发的同一方法中，在子组件中，我添加了：

import org.apache.spark._
import org.apache.spark.rdd._
import org.apache.spark.SparkContext._
import org.apache.spark.mllib.feature.HashingTF
import org.apache.spark.{SparkConf, SparkContext}
import org.apache.spark.ml.feature.{LabeledPoint => NewLabeledPoint}
import org.apache.spark.mllib.tree.GradientBoostedTrees
import org.apache.spark.mllib.tree.configuration.BoostingStrategy
import org.apache.spark._
import org.apache.spark.rdd._
import org.apache.spark.SparkContext._
import scala.util.{Success, Try}

import org.apache.spark.ml.feature.Word2Vec
import org.apache.spark.ml.linalg.Vector
import org.apache.spark.sql.Row

val input_labelled = labelledTweets.map(
      t => (t._1, word2VecModel2.transform(t._2.toDF("text")).select("result").first().getAs[org.apache.spark.ml.linalg.Vector](0)))
      .map(x => new LabeledPoint((x._1).toDouble, x._2)) 

input_labelled.take(3).foreach(println)

documentDF2: org.apache.spark.sql.DataFrame = [value: array<string>]
word2Vec2: org.apache.spark.ml.feature.Word2Vec = w2v_643337d9029a
word2VecModel2: org.apache.spark.ml.feature.Word2VecModel = w2v_643337d9029a
input_labelled: org.apache.spark.rdd.RDD[org.apache.spark.ml.feature.LabeledPoint] = MapPartitionsRDD[52] at map at <console>:74
input1: org.apache.spark.sql.DataFrame = [value: array<string>]
model2: org.apache.spark.ml.linalg.Vector = [9.573533798832813E-5,-1.8443804499634973E-4,3.803069862805999E-5,-4.663512611061804E-5,1.3393058071633097E-4]
[9.573533798832813E-5,-1.8443804499634973E-4,3.803069862805999E-5,-4.663512611061804E-5,1.3393058071633097E-4]
org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 21.0 failed 4 times, most recent failure: Lost task 0.3 in stage 21.0 (TID 159, sandbox-hdp.hortonworks.com, executor 1): java.lang.NullPointerException
    at $anonfun$1.apply(<console>:73)
    at $anonfun$1.apply(<console>:73)
    at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
    at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
    at scala.collection.Iterator$$anon$12.nextCur(Iterator.scala:434)
    at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:440)
    at scala.collection.Iterator$class.foreach(Iterator.scala:893)
    at scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
    at org.apache.spark.rdd.RDD$$anonfun$foreach$1$$anonfun$apply$28.apply(RDD.scala:918)
    at org.apache.spark.rdd.RDD$$anonfun$foreach$1$$anonfun$apply$28.apply(RDD.scala:918)
    at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2069)
    at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2069)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
    at org.apache.spark.scheduler.Task.run(Task.scala:108)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:338)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
    at java.lang.Thread.run(Thread.java:748)
Driver stacktrace:
  at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1517)
  at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1505)
  at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1504)
  at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
  at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
  at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1504)
  at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:814)
  at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:814)
  at scala.Option.foreach(Option.scala:257)
  at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:814)
  at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1732)
  at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1687)
  at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1676)
  at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
  at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:630)
  at org.apache.spark.SparkContext.runJob(SparkContext.scala:2029)
  at org.apache.spark.SparkContext.runJob(SparkContext.scala:2050)
  at org.apache.spark.SparkContext.runJob(SparkContext.scala:2069)
  at org.apache.spark.SparkContext.runJob(SparkContext.scala:2094)
  at org.apache.spark.rdd.RDD$$anonfun$foreach$1.apply(RDD.scala:918)
  at org.apache.spark.rdd.RDD$$anonfun$foreach$1.apply(RDD.scala:916)
  at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
  at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
  at org.apache.spark.rdd.RDD.withScope(RDD.scala:362)
  at org.apache.spark.rdd.RDD.foreach(RDD.scala:916)
  ... 58 elided
Caused by: java.lang.NullPointerException
  at $anonfun$1.apply(<console>:73)
  at $anonfun$1.apply(<console>:73)
  at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
  at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)

但这没有效果......
有什么建议？

Answer 1

符号#inputId不是您可以使用jQuery选择器搜索的内容。该符号为您提供的是您可以使用以下声明从父组件访问的内容：

  @ViewChild('inputId') myInput: ElementRef;

获得此元素参考后，您将获得焦点：

(myInput.nativeElement as HTMLInputElement).focus();

在某些情况下，您可能需要：

setTimeout(() => {
  (myInput.nativeElement as HTMLInputElement).focus();
});

将焦点设置为Angular 4中嵌套组件的元素

1 个答案: