如何删除隐藏的课程?为了显示色带?
HTML
<div id="alwaysInStockRibbon" class="ribbon-wrapper-productpage hidden">
的CSS
.hidden {
display: none!important;
visibility: hidden!important;
我在下面尝试过这些但没有成功。
Jquery的
$(".hidden").remove();
$(".hidden").removeClass();
https://api.jquery.com/remove/
https://api.jquery.com/removeClass/
输入
答案 0 :(得分:2)
您需要在removeClass方法中将classname作为参数传递,以便在匹配的集合中删除它:
从匹配元素集中的每个元素中删除单个类,多个类或所有类。
$(".hidden").removeClass('hidden');
答案 1 :(得分:1)
$("#alwaysInStockRibbon").removeClass('hidden');
答案 2 :(得分:1)
您必须告诉您要删除的课程。
$(".hidden").removeClass("hidden");
答案 3 :(得分:1)
试试这个:removeClass方法需要删除类名。如果要删除多个类,可以放置空格分隔的类名
$('.hidden').removeClass("hidden");
答案 4 :(得分:-2)
或者您可以执行以下操作来显示功能区:
String[] hexList = input.toString().split(",");
int numHex = (int) Math.pow(9, lLevel_From_config - hLevel_From_config);
for (String hex : hexList) {
for (int i = 0; i < numHex; i++) {
context.write(m_mapKey, generateHexagon(hex, i));
}
}
java.lang.OutOfMemoryError: GC overhead limit exceeded
at java.util.HashMap.createEntry(HashMap.java:897)
at java.util.HashMap.addEntry(HashMap.java:884)
at java.util.HashMap.put(HashMap.java:505)
at java.util.HashSet.add(HashSet.java:217)
at com.pb.hadoop.spark.hexgen.function.HexGenMapFunction.call(HexGenMapFunction.java:56)
at com.pb.hadoop.spark.hexgen.function.HexGenMapFunction.call(HexGenMapFunction.java:21)
at org.apache.spark.api.java.JavaRDDLike$$anonfun$fn$1$1.apply(JavaRDDLike.scala:129)
at org.apache.spark.api.java.JavaRDDLike$$anonfun$fn$1$1.apply(JavaRDDLike.scala:129)
at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopDataset$1$$anonfun$13$$anonfun$apply$6.apply$mcV$sp(PairRDDFunctions.scala:1197)
at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopDataset$1$$anonfun$13$$anonfun$apply$6.apply(PairRDDFunctions.scala:1197)
at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopDataset$1$$anonfun$13$$anonfun$apply$6.apply(PairRDDFunctions.scala:1197)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1251)
at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopDataset$1$$anonfun$13.apply(PairRDDFunctions.scala:1205)
at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopDataset$1$$anonfun$13.apply(PairRDDFunctions.scala:1185)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)