Re: Patricia trie vs binary search.

From:
Daniel Pitts <newsgroup.nospam@virtualinfinity.net>
Newsgroups:
comp.lang.java.programmer
Date:
Tue, 29 May 2012 15:39:16 -0700
Message-ID:
<pecxr.10088$br3.3802@newsfe10.iad>
On 5/29/12 3:23 PM, Daniel Pitts wrote:

On 5/29/12 2:49 PM, Gene Wirchenko wrote:

On Tue, 29 May 2012 14:03:10 -0700 (PDT), Lew<lewbloch@gmail.com>
wrote:

Gene Wirchenko wrote:

Daniel Pitts wrote:

[snip]

Are you arguing that a modern system can't handle that number of
words?


No. I simply stating that the real size of the problem is much
bigger.


With no numbers that differ from Daniel's to back up your claim.

You called my numbers "made up", but it turned out they were
*larger* than the real numbers.

You cite "a quarter of a million" words. Daniel counted roughly
*150%* of that in his word base.


Ah, selective reading.

For root forms, it was 1/4 million. With affixes -- and remember
that my first question was about them -- the figure was 3/4 million.
This is double what Daniel counted, and 3/4 million does not include
technical words, etc. Take a look at the *full* paragraph that I
quoted, not just the lowest number.

My numbers were generous. Yours are not even significantly different,
and in fact are smaller than his. The numbers do show there is not
much problem, yet somehow you claim with no logic or reasoning or
different data that they do show a problem.


Take another look at that paragraph I quoted. Really.

Clearly you are mistaken.

Daniel showed evidence from experimentation. His numbers jibe with
yours. Without compression, his data occupy roughly 5 MiB of memory.

Show the problem or withdraw the claim.


Read my statement of the problem.

A modern desktop has more than enough memory to easily handle a
quarter
*billion* words, which is a 100 times greater than your guessed
upper limit.

And that's *without* compression.


Sure. If that is all that it does. My main (and older) desktop
box has 1.5 GB. I have trouble with not enough memory at times.
Adding another app might break its back.


Again, how much damage will< 5 MiB of data do to that system?

How about 50 MiB? That's *ten times* the number of words you might
need to handle.
Without any compression.


Fine. My system is currently using 1547 MB of memory. It only
has 1536 MB. With some intensive uses, I have seen the commit go to
as high as about 2200 MB. My system crawls then. Using 50 MB more in
those circumstances would not be good.

You haven't shown a problem. You just chant, "The sky is falling!"


I believe that I have. Handwaving the possibility away does not
make it go away.

Sincerely,

Gene Wirchenko


Test program:

package net.virtualinfinity.moby;

import java.io.BufferedReader;
import java.io.FileReader;
import java.io.IOException;
import java.util.Arrays;

public class WordTree {
WordNode start = new WordNode(-1);

public void addWord(String word) {
start.addWord(word);
}

public static void main(String[] args) throws IOException {
WordTree tree = new WordTree();
int wordsLoaded = 0;
for (String filename: args) {
System.out.println("Loading " + filename);
BufferedReader reader = new BufferedReader(new FileReader(filename),
1024*256);
String line;
while ((line = reader.readLine()) != null) {
++wordsLoaded;
if ((wordsLoaded & 127) == 0) {
printStatus(wordsLoaded);
}
tree.addWord(line.trim());
}
System.gc();
printStatus(wordsLoaded);
System.out.println();
}
}

private static void printStatus(int wordsLoaded) {
System.out.print("\rWords loaded: " + wordsLoaded + ", Total Memory
used: " + Runtime.getRuntime().totalMemory() + ". ");
}
}

class WordNode {
private boolean terminal;
private final int value;
private WordNode[] next;

public WordNode(int ch) {
value = ch;
}

public void addWord(String word) {
if ("".equals(word)) {
terminal = true;
return;
}
final int ch = word.codePointAt(0);
getNext(ch).addWord(word.substring(Character.charCount(ch)));
}

private WordNode getNext(int ch) {
if (next == null) {
next = new WordNode[1];
next[0] = new WordNode(ch);
}
for (WordNode node: next) {
if (node.value == ch) {
return node;
}
}
next = Arrays.copyOf(next, next.length +1);
final WordNode newNode = new WordNode(ch);
next[next.length-1] = newNode;
return newNode;
}
}

------- Output -----

Loading compound-words.txt
Words loaded: 256772, Total Memory used: 120909824.
Loading often-mispelled.txt
Words loaded: 257138, Total Memory used: 121106432.
Loading english-most-frequent.txt
Words loaded: 258141, Total Memory used: 121106432.
Loading male-names.txt
Words loaded: 262038, Total Memory used: 121106432.
Loading female-names.txt
Words loaded: 266984, Total Memory used: 121106432.
Loading common-names.txt
Words loaded: 288970, Total Memory used: 121106432.
Loading common-dictionary.txt
Words loaded: 363520, Total Memory used: 127373312.
Loading official-scrabble-1st-edition.txt
Words loaded: 477329, Total Memory used: 129957888.
Loading official-scrabble-2nd-edition-delta.txt
Words loaded: 481489, Total Memory used: 129957888.


BTW, if I check the memory usage before loading words and after, the
difference is ~ 42MB

So, loading 481k words takes up about 42MB. This is in java, which has a
fairly high overhead per string. And the implementation of my data
structure is also fairly naive as well.

Extrapolating that data to an extreme 2 million words, that would be
less than 200MB in memory.

My gut feeling beats your gut feeling, and my science proves it true. If
you are going to reply with a counter argument, please provide a
reproducible experiment to prove your argument. Otherwise, this
conversation is over.

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