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_609.java
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_609.java
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package com.fishercoder.solutions;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
/**
* 609. Find Duplicate File in System
*
* Given a list of directory info including directory path, and all the files with contents in this directory,
* you need to find out all the groups of duplicate files in the file system in terms of their paths.
* A group of duplicate files consists of at least two files that have exactly the same content.
A single directory info string in the input list has the following format:
"root/d1/d2/.../dm f1.txt(f1_content) f2.txt(f2_content) ... fn.txt(fn_content)"
It means there are n files (f1.txt, f2.txt ... fn.txt with content f1_content, f2_content ... fn_content, respectively)
in directory root/d1/d2/.../dm. Note that n >= 1 and m >= 0. If m = 0, it means the directory is just the root directory.
The output is a list of group of duplicate file paths.
For each group, it contains all the file paths of the files that have the same content.
A file path is a string that has the following format:
"directory_path/file_name.txt"
Example 1:
Input:
["root/a 1.txt(abcd) 2.txt(efgh)", "root/c 3.txt(abcd)", "root/c/d 4.txt(efgh)", "root 4.txt(efgh)"]
Output:
[["root/a/2.txt","root/c/d/4.txt","root/4.txt"],["root/a/1.txt","root/c/3.txt"]]
Note:
No order is required for the final output.
You may assume the directory name,
file name and file content only has letters and digits, and the length of file content is in the range of [1,50].
The number of files given is in the range of [1,20000].
You may assume no files or directories share the same name in a same directory.
You may assume each given directory info represents a unique directory. Directory path and file infos are separated by a single blank space.
Follow up beyond contest:
Imagine you are given a real file system, how will you search files? DFS or BFS ?
If the file content is very large (GB level), how will you modify your solution?
If you can only read the file by 1kb each time, how will you modify your solution?
What is the time complexity of your modified solution? What is the most time consuming part and memory consuming part of it? How to optimize?
How to make sure the duplicated files you find are not false positive?
*/
public class _609 {
public static class Solution1 {
public List<List<String>> findDuplicate(String[] paths) {
Map<String, List<String>> map = new HashMap<>();//key is the file content, value is the list of directories that has this directory/file
for (String path : paths) {
String[] dirAndFiles = path.split(" ");
for (int i = 1; i < dirAndFiles.length; i++) {
String content = dirAndFiles[i].substring(dirAndFiles[i].indexOf("(") + 1, dirAndFiles[i].indexOf(")"));
if (!map.containsKey(content)) {
map.put(content, new ArrayList<>());
}
List<String> dirs = map.get(content);
dirs.add(dirAndFiles[0] + "/" + dirAndFiles[i].substring(0, dirAndFiles[i].indexOf("(")));
map.put(content, dirs);
}
}
List<List<String>> result = new ArrayList<>();
for (String content : map.keySet()) {
if (map.get(content).size() > 1) {
List<String> dupFile = new ArrayList<>();
for (String dir : map.get(content)) {
dupFile.add(dir);
}
result.add(dupFile);
}
}
return result;
}
}
/**Answers to follow-up questions:
* 1. Imagine you are given a real file system, how will you search files? DFS or BFS ?
* A: Both BFS and DFS could do the work, but BFS will use extra memory, however, BFS takes advantage of memory locality, so BFS could be faster.
*
* 2. If the file content is very large (GB level), how will you modify your solution?
* A: We'll fist map all files according to their sizes, since files with different sizes are guaranteed to be different, then
* we can hash a small part of the files using MD5, SHA256, etc. Only when their md5 or sha256 is the same, we'll compare the contents byte by byte.
*
* 3. If you can only read the file by 1kb each time, how will you modify your solution?
* A: This is not going to change the solution, we can hash this 1kb chunk, and then also only compare byte by byte when it's necessary.
*
* 4. What is the time complexity of your modified solution? What is the most time consuming part and memory consuming part of it? How to optimize?
* A: O(n^2*k), in the worst time, we'll have to compare the file with every other file, k is the length of the file.
* Comparing the file (by size, by hash and eventually byte by byte) is the most time consuming part.
* Generating hash for every file will be the most memory consuming part.
*
* 5. How to make sure the duplicated files you find are not false positive?
* A: Size comparision, hash detection, byte by byte check, etc. will pretty sure to rule out false positive.
* */
}