小编Kar*_*way的帖子

我有一个有另一个static内部类的类:

class A {
    private List<String> list;

    public static class B {
        // I want to update list here without making list as static 
        // I don't have an object for outer class
    }
}

有人可以请解释什么区别ArrayList<?>,ArrayList而且ArrayList<Object>是,当使用的呢？它们是相同的还是在实施层面上都有不同的含义？

嗨我的python安装在不同的目录中,我正在使用基于mac的docker镜像,它在shell脚本的其他文件夹中将shebang行称为/ user/local/bin/python3.

我的python安装路径

Python 3.4.3 (default, Oct 14 2015, 20:28:29) 
[GCC 4.8.4] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import sys
>>> sys.path
['', '/home/myuser/project', '/usr/lib/python3.4', '/usr/lib/python3.4/plat-x86_64-linux-gnu', '/usr/lib/python3.4/lib-dynload', '/usr/local/lib/python3.4/dist-packages', '/usr/lib/python3/dist-packages']
>>> 

所以有没有办法没有改变shebang线我可以重定向或链接到我的python3安装,以摆脱这个错误.

是否建议在给定路径中安装python3.？

请指教.

我正在尝试运行一个docker镜像,它说的是已经在使用的地址

 driver failed programming external connectivity on endpoint jovial_saha (c79c98cbcef6340cd7867571278f401c9cbea1fd7137a39fe5d7de1c454d4e6e): Error starting userland proxy: listen tcp 0.0.0.0:9042: bind: address already in use.

但是我删除了所有容器和图像,然后即使我打电话来运行我的图像

docker run -d -p 9042:9042 myimage . i get above error. what  should i do ?

我在emr上运行spark job并使用datastax连接器连接到cassandra集群.我正面临着番石榴罐的问题,请找到下面的详细信息,我在cassandra deps下面使用

cqlsh 5.0.1 | Cassandra 3.0.1 | CQL spec 3.3.1 

使用以下maven deps在EMR 4.4上运行spark工作

org.apache.spark spark-streaming_2.10 1.5.0

<dependency>
    <groupId>org.apache.spark</groupId>
    <artifactId>spark-core_2.10</artifactId>
    <version>1.5.0</version>
</dependency>

<dependency>
    <groupId>org.apache.spark</groupId><dependency>
    <groupId>com.datastax.spark</groupId>
    <artifactId>spark-cassandra-connector_2.10</artifactId>
    <version>1.5.0</version>
</dependency>

    <artifactId>spark-streaming-kinesis-asl_2.10</artifactId>
    <version>1.5.0</version>
</dependency>

当我提交火花工作时遇到问题如下

ava.lang.ExceptionInInitializerError
       at com.datastax.spark.connector.cql.DefaultConnectionFactory$.clusterBuilder(CassandraConnectionFactory.scala:35)
       at com.datastax.spark.connector.cql.DefaultConnectionFactory$.createCluster(CassandraConnectionFactory.scala:87)
       at com.datastax.spark.connector.cql.CassandraConnector$.com$datastax$spark$connector$cql$CassandraConnector$$createSession(CassandraConnector.scala:153)
       at com.datastax.spark.connector.cql.CassandraConnector$$anonfun$2.apply(CassandraConnector.scala:148)
       at com.datastax.spark.connector.cql.CassandraConnector$$anonfun$2.apply(CassandraConnector.scala:148)
       at com.datastax.spark.connector.cql.RefCountedCache.createNewValueAndKeys(RefCountedCache.scala:31)
      at com.datastax.spark.connector.cql.RefCountedCache.acquire(RefCountedCache.scala:56)
       at com.datastax.spark.connector.cql.CassandraConnector.openSession(CassandraConnector.scala:81)
       at ampush.event.process.core.CassandraServiceManagerImpl.getAdMetaInfo(CassandraServiceManagerImpl.java:158)
       at ampush.event.config.metric.processor.ScheduledEventAggregator$4.call(ScheduledEventAggregator.java:308)
       at ampush.event.config.metric.processor.ScheduledEventAggregator$4.call(ScheduledEventAggregator.java:290)
       at org.apache.spark.api.java.JavaRDDLike$$anonfun$foreachPartition$1.apply(JavaRDDLike.scala:222)
       at org.apache.spark.api.java.JavaRDDLike$$anonfun$foreachPartition$1.apply(JavaRDDLike.scala:222)
       at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1$$anonfun$apply$29.apply(RDD.scala:902)
       at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1$$anonfun$apply$29.apply(RDD.scala:902)
       at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1850)
       at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1850)
       at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
       at org.apache.spark.scheduler.Task.run(Task.scala:88)
       at org.apache.spark.executor.Executor$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) …

下面是我的POM文件.我正在用aws kinesis写一个火花流

<dependency>
        <groupId>org.apache.spark</groupId>
        <artifactId>spark-streaming_2.10</artifactId>
        <version>1.6.0</version>
    </dependency>

    <dependency>
        <groupId>org.apache.spark</groupId>
        <artifactId>spark-core_2.10</artifactId>
        <version>1.6.0</version>
    </dependency>
     <dependency>
        <groupId>com.amazonaws</groupId>
        <artifactId>amazon-kinesis-client</artifactId>
        <version>1.6.1</version>
    </dependency>
    <dependency>
        <groupId>org.apache.spark</groupId>
        <artifactId>spark-streaming-kinesis-asl_2.10</artifactId>
        <version>1.6.0</version>
    </dependency>

我在Cloudera 5.10的火花程序运行期间面临异常

17/04/27 05:34:04 WARN scheduler.TaskSetManager: Lost task 0.0 in stage 58.0 (TID 179, hadoop1.local, executor 5): java.lang.AbstractMethodError
at org.apache.spark.Logging$class.log(Logging.scala:50)
at org.apache.spark.streaming.kinesis.KinesisCheckpointer.log(KinesisCheckpointer.scala:39)
at org.apache.spark.Logging$class.logDebug(Logging.scala:62)
at org.apache.spark.streaming.kinesis.KinesisCheckpointer.logDebug(KinesisCheckpointer.scala:39)
at org.apache.spark.streaming.kinesis.KinesisCheckpointer.startCheckpointerThread(KinesisCheckpointer.scala:119)
at org.apache.spark.streaming.kinesis.KinesisCheckpointer.<init>(KinesisCheckpointer.scala:50)
at org.apache.spark.streaming.kinesis.KinesisReceiver.onStart(KinesisReceiver.scala:149)
at org.apache.spark.streaming.receiver.ReceiverSupervisor.startReceiver(ReceiverSupervisor.scala:148)
at org.apache.spark.streaming.receiver.ReceiverSupervisor.start(ReceiverSupervisor.scala:130)
at org.apache.spark.streaming.scheduler.ReceiverTracker$ReceiverTrackerEndpoint$$anonfun$9.apply(ReceiverTracker.scala:575)
at org.apache.spark.streaming.scheduler.ReceiverTracker$ReceiverTrackerEndpoint$$anonfun$9.apply(ReceiverTracker.scala:565)
at org.apache.spark.SparkContext$$anonfun$38.apply(SparkContext.scala:2000)
at org.apache.spark.SparkContext$$anonfun$38.apply(SparkContext.scala:2000)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:242)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)

这在EMR4.4上运行完全正常但是CDH失败了.任何建议

我有一个如下代码

var newWidth = Math.floor(width * .75) + 'px';
$(this).find("input:first").attr('style', 'width:newWidth ');

你可以请你纠正我,因为正确的语法是直接传递newWidth不起作用我也必须通过样式才能这样做