Hashmap单键持有一个类。计数键和检索计数器 [英] Hashmap single key holding a class. count the key and retrieve counter

问题描述

我正在开发一个数据库自我项目。我有一个输入文件，来自： http：//ir.dcs.gla。 ac.uk/resources/test_collections/cran/

在处理成1400个独立文件后，每个文件命名为 00001.txt 。 .. 01400.txt ...），然后在它们上应用停止之后，我们将它们分别存储在特定文件夹中，可以调用 StemmedFolder ，其格式如下：

在 StemmedFolder：

 调查
 aerodynam 
 wing 
 slipstream 
 brenckman 
 experiment 
 investig 
 aerodynam 
 wing 
  

StemmedFolder： 00756.txt包括：

 注释
 eddi 
 viscos 
 compress 
 mix 
 flow 
 lu 
 ting 
  

$ b b

等等....

我写了代码：

1. 取得 。

< >添加文档的ID

2. 将每个文件保存到新文件00001.txt到01400.txt，如下所述

{我可以提供我的代码这4个部分，以防有人需要看看如何实现或更改或任何编辑}

$每个文件的b $ b

---

输出将导致单独的文件。 （1400，每个名为 00001.txt ， 00002.txt ...）可以调用 FrequenceyFolder strong>使用以下格式：

在 FrequenceyFolder： 00001.txt包括：

  00001，aerodynam，2 
 00001，agre，3 
 00001，angl，1 
 00001，attack，7 
 00001，basi，4 
 .... 
  

< FrequenceyFolder： 00999.txt包括：

  00999，aerodynam，5 
 00999，评估，1 
 00999，电梯，3 
 00999，比率，2 
 00999，结果，9 
 .... 
     中的  包含
： 
  01400，减去，1 
 01400，支持，1 
 01400，理论，1 
 01400，theori，1 
 01400，..... 
  
 
 
 
 
 
 
 strong>    ：
 
 
 
我需要再次合并这1400个文件，输出一个txt文件，看起来像这样的格式与一些计算：
 'airodynam'totalFrequency = 3docs：[[Doc_00001,5]，[Doc_01344,4]，[Doc_00123,3]] 
'book'totalFrequncy = 2docs：[[Doc_00562,6]，[Doc_01111,1] 
 .... 
 .... 
'result'totalFrequency = 1doc：[[Doc_00010,5]] 
 .... 
 .... 
 
'zzzz'totalFrequency = 1doc：[[Doc_01235,1]] 
  
 
 
 
 
 
 
感谢您花费时间阅读这篇长文章
解决方案
 code> 列表的映射。 
 
 
 
  Map< String，List< FileInformation> statistics = new HashMap<>（） 
 
 
 
在上面的映射中，键将是字，值将是 List< FileInformation> 对象描述包含单词的单个文件的统计。  FileInformation 类可以声明如下：
  class FileInformation {
 int occurrenceCount; 
 String fileName; 
 
 // getters和setters 
} 
  
填充上面的映射，请使用以下步骤：
 
 
读取 FrequencyFolder  / li> 
 
当你第一次遇到某个单词时，将其作为一个键放在 Map 中。
 
 
创建一个 FileInformation 对象，并将 occurrenceCount 设置为找到的出现次数，并将 fileName 添加到在 List< FileInformation> 中创建的文件对应的第2步。
 
 
下次在另一个文件中遇到同一个词时，创建一个新的 FileInfomation 对象， 列表< FileInformation> 对应于地图中该字词的条目。
 
 
一旦您已经填充 Map ，打印统计信息应该是一块蛋糕。 
  for（String word：statistics.keySet（））{
 List< FileInformation> fileInfos = statistics.get（word）; 
 for（FileInformation fileInfo：fileInfos）{
 //总结单词的occureneceCount以获得总频率
} 
} 
  
 
I am working on a database self project. I have an input file got from: http://ir.dcs.gla.ac.uk/resources/test_collections/cran/ 


After processing into 1400 separate file, each named 00001.txt,... 01400.txt...) and after applying Stemming on them, I will store them separately in a specific folder lets call it StemmedFolder with the following format:

in StemmedFolder: 00001.txt includes:
investig
aerodynam
wing
slipstream
brenckman
experiment
investig
aerodynam
wing
in StemmedFolder: 00756.txt includes: 
remark
eddi
viscos
compress
mix
flow
lu
ting
And so on....

I wrote the codes that do: 

get the StemmedFolder, Count the Unique words
Sort Alphabetically
Add the ID of the document
save each to a new file 00001.txt to 01400.txt as will be described
{I can provide my codes for these 4 sections in case somebody needs to see how is the implementation or  change or any edit}



output of each file will be result to a separate file. (1400, each named 00001.txt, 00002.txt...) in a specific folder lets call it FrequenceyFolder with the following format:

in FrequenceyFolder: 00001.txt includes: 
00001,aerodynam,2
00001,agre,3
00001,angl,1
00001,attack,7
00001,basi,4
....
in FrequenceyFolder: 00999.txt includes: 
00999,aerodynam,5
00999,evalu,1
00999,lift,3
00999,ratio,2
00999,result,9
....
in FrequenceyFolder: 01400.txt includes: 
01400,subtract,1
01400,support,1
01400,theoret,1
01400,theori,1
01400,.....




______________

Now my question:

I need to combine these 1400 files again to output a txt file that looks like this format with some calculation:
'aerodynam' totalFrequency=3docs: [[Doc_00001,5],[Doc_01344,4],[Doc_00123,3]]
'book' totalFrequncy=2docs: [[Doc_00562,6],[Doc_01111,1]
....
....
'result' totalFrequency=1doc: [[Doc_00010,5]]
....
....

'zzzz' totalFrequency=1doc: [[Doc_01235,1]]




Thanks for spending time reading this long post
解决方案
You can use a Map of List. 

Map<String,List<FileInformation>> statistics = new HashMap<>()

In the above map, the key will be the word and the value will be a List<FileInformation> object describing the statistics of individual files containing the word. The FileInformation class can be declared as follows :
class FileInformation {
    int occurrenceCount;
    String fileName;

    //getters and setters
}
To populate the above Map, use the following steps :

Read each file in the FrequencyFolder
When you come across a word for the first time, put it as a key in the Map.
Create a FileInformation object and set the occurrenceCount to the number of occurrences found and set the fileName to the name of the file it was found in. Add this object in the List<FileInformation> corresponding to the key created in step 2.
The next time you come across the same word in another file, create a new FileInfomation object and add it to the List<FileInformation> corresponding to the entry in the map for the word.
Once you have the Map populated, printing the statistics should be a piece of cake. 
for(String word : statistics.keySet()) {
  List<FileInformation> fileInfos = statistics.get(word);
  for(FileInformation fileInfo : fileInfos) {
      //sum up the occureneceCount for the word to get the total frequency
  }
}


                        
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