Databases
StackOverflow2013
Postsdbo
POLogLog and HyperLogLog algorithms for counting of large cardinalities
 

Note that there are some explanatory texts on larger screens.

plurals
  1. POLogLog and HyperLogLog algorithms for counting of large cardinalities
    primarykey
    data
    text
    <p>Where can I find a valid implementation of <a href="http://algo.inria.fr/flajolet/Publications/DuFl03.pdf" rel="nofollow noreferrer">LogLog algorithm</a>? Have tried to implement it by myself but my draft implementation yields strange results.</p> <p><a href="http://jsfiddle.net/LCDLL/1/" rel="nofollow noreferrer">Here</a> it is:</p> <pre><code>function LogLog(max_error, max_count) { function log2(x) { return Math.log(x) / Math.LN2; } var m = 1.30 / max_error; var k = Math.ceil(log2(m * m)); m = Math.pow(2, k); var k_comp = 32 - k; var l = log2(log2(max_count / m)); if (isNaN(l)) l = 1; else l = Math.ceil(l); var l_mask = ((1 &lt;&lt; l) - 1) &gt;&gt;&gt; 0; var M = []; for (var i = 0; i &lt; m; ++i) M[i] = 0; function count(hash) { if (hash !== undefined) { var j = hash &gt;&gt;&gt; k_comp; var rank = 0; for (var i = 0; i &lt; k_comp; ++i) { if ((hash &gt;&gt;&gt; i) &amp; 1) { rank = i + 1; break; } } M[j] = Math.max(M[j], rank &amp; l_mask); } else { var c = 0; for (var i = 0; i &lt; m; ++i) c += M[i]; return 0.79402 * m * Math.pow(2, c / m); } } return {count: count}; } function fnv1a(text) { var hash = 2166136261; for (var i = 0; i &lt; text.length; ++i) { hash ^= text.charCodeAt(i); hash += (hash &lt;&lt; 1) + (hash &lt;&lt; 4) + (hash &lt;&lt; 7) + (hash &lt;&lt; 8) + (hash &lt;&lt; 24); } return hash &gt;&gt;&gt; 0; } var words = ['aardvark', 'abyssinian', ... ,'zoology']; // about 2 300 words var log_log = LogLog(0.01, 100000); for (var i = 0; i &lt; words.length; ++i) log_log.count(fnv1a(words[i])); alert(log_log.count()); </code></pre> <p>For unknown reason implementation is very sensitive to <code>max_error</code> parameter, it is the main factor that determines the magnitude of the result. I'm sure, there is some stupid mistake :)</p> <p><strong>UPDATE:</strong> This problem is solved in the <a href="http://algo.inria.fr/flajolet/Publications/FlFuGaMe07.pdf" rel="nofollow noreferrer">newer version</a> of algorithm. I will post its implementation later.</p>
    singulars
    1. PO
      singulars
      1. PTAnswer
    1. This table or related slice is empty.
    1. PTQuestion
    1. USRia
    1. USactual
    plurals
    1. This table or related slice is empty.
    1. PL
      singulars
      1. LTLinked
    1. This table or related slice is empty.
    1. PO
      singulars
      1. PTAnswer
    2. PO
      singulars
      1. PTAnswer
    3. PO
      singulars
      1. PTAnswer
    1. VO
      singulars
      1. POLogLog and HyperLogLog algorithms for counting of large cardinalities
      1. This table or related slice is empty.
      1. VTUpMod
    2. VO
      singulars
      1. POLogLog and HyperLogLog algorithms for counting of large cardinalities
      1. This table or related slice is empty.
      1. VTUpMod
    3. VO
      singulars
      1. POLogLog and HyperLogLog algorithms for counting of large cardinalities
      1. This table or related slice is empty.
      1. VTUpMod
    1. COFWIW - I think you'll have better luck emailing the paper's authors.
      singulars
      1. POLogLog and HyperLogLog algorithms for counting of large cardinalities
      1. USdfb
    2. CO@spinning_plate, one of the authors died about a month ago, email address of the other one is not functional.
      singulars
      1. POLogLog and HyperLogLog algorithms for counting of large cardinalities
      1. USactual
    3. COIt would help if you post what you've tried so far and explain your results.
      singulars
      1. POLogLog and HyperLogLog algorithms for counting of large cardinalities
      1. USBill the Lizard
 

Querying!

 
Guidance
A row detail

Detail views are divided into sections. All the information in the data section comes from columns in the selected row. The other sections display data from other, related rows.

Related data can be related in a to-one or a to-many fashion. Captions of data related in a to-many fashion link to a list view showing a filtered view of the table.

Try moving around until you find a non-empty to-many entry and click on the label to get to one. You can move back to the root by clicking on the database name in the header.

SQuiL has stopped working due to an internal error.

If you are curious you may find further information in the browser console, which is accessible through the devtools (F12).

Reload