Java 在arraylist中缓存iterable以在reducer中迭代两次不会';行不通

Java 在arraylist中缓存iterable以在reducer中迭代两次不会';行不通,java,hadoop,arraylist,mapreduce,iterable,Java,Hadoop,Arraylist,Mapreduce,Iterable,我的MR程序有一些奇怪的问题,不知道为什么会这样。 也许你能给我一个提示它有什么问题 这就是我的映射器函数的外观: Integer Click_ID = 0; public void map(LongWritable key, Text value, Context context) throws IOException , InterruptedException { String line = value.toString();

我的MR程序有一些奇怪的问题,不知道为什么会这样。 也许你能给我一个提示它有什么问题

这就是我的映射器函数的外观:

    Integer Click_ID = 0;

  public void map(LongWritable key, Text value, Context context)
        throws IOException , InterruptedException
  {

      String line = value.toString();

      String []lineArr = line.split("\t");

      String nm_uv_id = lineArr[0];
      String session_id = lineArr[1];
      String time_stamp = lineArr[2];
      String click_counter = lineArr[3];
      String is_robot = lineArr[4];

      Click_ID++;

      String full_line =  Click_ID + "\t"+ nm_uv_id +"\t"+ session_id+"\t"+time_stamp+"\t"+click_counter+"\t"+ is_robot;


      context.write(new Text(session_id), new Text(full_line));

   }
到目前为止,一切都很好——当我将还原数设置为0时,我的映射器生成预期的输出

这是我的减速机的样子。我想做的是,对我的每个键迭代两次。为此,我尝试将Iterable的每个值缓存在单独的ArrayList中:

    public void reduce(Text key, Iterable<Text> values, Context context)
        throws IOException, InterruptedException {
    List<Text> cache = new ArrayList<Text>();

           // first iterable
    for (Text value : values) {
                                       cache.add(value); }

           //second iterable
        for (Text entity : cache) {

            context.write(key, entity);  }
    }
但是,我的输出文件如下所示:

nm_uv_id_1  session_id_2    1234567891  1   is_robot_no
nm_uv_id_1  session_id_2    1234567892  2   is_robot_no
nm_uv_id_1  session_id_2    1234567893  3   is_robot_no
nm_uv_id_1  session_id_2    1234567894  3   is_robot_no
nm_uv_id_1  session_id_1    1234567895  1   is_robot_no
nm_uv_id_1  session_id_1    1234567896  2   is_robot_no
nm_uv_id_1  session_id_1    1234567897  3   is_robot_no
nm_uv_id_1  session_id_1    1234567898  4   is_robot_no
nm_uv_id_1  session_id_1    1234567899  5   is_robot_no
nm_uv_id_1  session_id_1    1234567888  6   is_robot_no
nm_uv_id_1  session_id_1    1234567890  7   is_robot_no
nm_uv_id_1  session_id_1    1234567890  8   is_robot_no
nm_uv_id_1  session_id_1    1234567890  9   is_robot_no
nm_uv_id_1  session_id_1    1234567890  10  is_robot_no
nm_uv_id_1  session_id_3    1234567890  1   is_robot_no
nm_uv_id_2  session_id_4    1234587890  1   is_robot_no
nm_uv_id_2  session_id_4    1234587890  2   is_robot_no
nm_uv_id_2  session_id_4    1234587890  3   is_robot_no
nm_uv_id_2  session_id_4    1234587890  4   is_robot_no
nm_uv_id_2  session_id_4    1234587890  5   is_robot_no
nm_uv_id_2  session_id_4    1234587890  6   is_robot_no
nm_uv_id_2  session_id_4    1234587890  7   is_robot_no
nm_uv_id_2  session_id_4    1234587890  8   is_robot_no
nm_uv_id_2  session_id_4    1234587890  9   is_robot_no
nm_uv_id_2  session_id_5    1234587890  1   is_robot_no
nm_uv_id_2  session_id_5    1234587890  2   is_robot_no
nm_uv_id_2  session_id_5    1234587890  3   is_robot_yes
nm_uv_id_2  session_id_5    1234587890  4   is_robot_yes
nm_uv_id_2  session_id_5    1234587890  5   is_robot_no
nm_uv_id_2  session_id_5    123457890   6   is_robot_no
session_id_1    13  nm_uv_id_1  session_id_1    1234567890  9   is_robot_no
session_id_1    13  nm_uv_id_1  session_id_1    1234567890  9   is_robot_no
session_id_1    13  nm_uv_id_1  session_id_1    1234567890  9   is_robot_no
session_id_1    13  nm_uv_id_1  session_id_1    1234567890  9   is_robot_no
session_id_1    13  nm_uv_id_1  session_id_1    1234567890  9   is_robot_no
session_id_1    13  nm_uv_id_1  session_id_1    1234567890  9   is_robot_no
session_id_1    13  nm_uv_id_1  session_id_1    1234567890  9   is_robot_no
session_id_1    13  nm_uv_id_1  session_id_1    1234567890  9   is_robot_no
session_id_1    13  nm_uv_id_1  session_id_1    1234567890  9   is_robot_no
session_id_1    13  nm_uv_id_1  session_id_1    1234567890  9   is_robot_no
session_id_2    2   nm_uv_id_1  session_id_2    1234567892  2   is_robot_no
session_id_2    2   nm_uv_id_1  session_id_2    1234567892  2   is_robot_no
session_id_2    2   nm_uv_id_1  session_id_2    1234567892  2   is_robot_no
session_id_2    2   nm_uv_id_1  session_id_2    1234567892  2   is_robot_no
session_id_3    15  nm_uv_id_1  session_id_3    1234567890  1   is_robot_no
session_id_4    24  nm_uv_id_2  session_id_4    1234587890  9   is_robot_no
session_id_4    24  nm_uv_id_2  session_id_4    1234587890  9   is_robot_no
session_id_4    24  nm_uv_id_2  session_id_4    1234587890  9   is_robot_no
session_id_4    24  nm_uv_id_2  session_id_4    1234587890  9   is_robot_no
session_id_4    24  nm_uv_id_2  session_id_4    1234587890  9   is_robot_no
session_id_4    24  nm_uv_id_2  session_id_4    1234587890  9   is_robot_no
session_id_4    24  nm_uv_id_2  session_id_4    1234587890  9   is_robot_no
session_id_4    24  nm_uv_id_2  session_id_4    1234587890  9   is_robot_no
session_id_4    24  nm_uv_id_2  session_id_4    1234587890  9   is_robot_no
session_id_5    30  nm_uv_id_2  session_id_5    123457890   6   is_robot_no
session_id_5    30  nm_uv_id_2  session_id_5    123457890   6   is_robot_no
session_id_5    30  nm_uv_id_2  session_id_5    123457890   6   is_robot_no
session_id_5    30  nm_uv_id_2  session_id_5    123457890   6   is_robot_no
session_id_5    30  nm_uv_id_2  session_id_5    123457890   6   is_robot_no
session_id_5    30  nm_uv_id_2  session_id_5    123457890   6   is_robot_no
我不理解为什么减缩器总是为一个特定的键写入相同的键值对。我尝试了几种方法,似乎第一个for循环(我在其中进行缓存)可以很好地工作。当我写context.write(key,value)时,我得到了预期的输出。 然而,第二次,当我想在第二个for循环中使用缓存时,程序为我写了一些奇怪的东西


有人能帮忙吗?

这是重复使用相同的
文本
缓冲区作为优化。因此,您需要手动克隆以缓存它

我只想更改您的缓存循环:

for (Text value : values) { cache.add(new Text(value)); }