Replacement of Quicksort in java.util.Arrays with new Dual-Pivot Quicksort

Fri Sep 11 13:43:36 UTC 2009

sure, will do it

Rémi Forax wrote:
> just my two cents :
> In the loop tagged "sorting" and "equals element",
> a[k] can be stored in a local variable to avoid to recompute it several 
> time.
> 
> The algorithm use two constants: 37 and 13,
> I think they should be declared as private static final.
> 
> Rémi
> 
> Le 11/09/2009 12:35, Vladimir Yaroslavskiy a écrit :
>> Hello All,
>>
>> I'd like to share with you new Dual-Pivot Quicksort which is
>> faster than the known implementations (theoretically and
>> experimental). I'd like to propose to replace the JDK's
>> Quicksort implementation by new one.
>>
>> Description
>> -----------
>> The classical Quicksort algorithm uses the following scheme:
>>
>> 1. Pick an element P, called a pivot, from the array.
>> 2. Reorder the array so that all elements, which are less than
>>    the pivot, come before the pivot and all elements greater than
>>    the pivot come after it (equal values can go either way). After
>>    this partitioning, the pivot element is in its final position.
>> 3. Recursively sort the sub-array of lesser elements and the
>>    sub-array of greater elements.
>>
>> The invariant of classical Quicksort is:
>>
>> [ <= p | >= p ]
>>
>> There are several modifications of the schema:
>>
>> [ < p | = p | > p ]  or  [ = p | < p | > p | = p ]
>>
>> But all of them use *one* pivot.
>>
>> The new Dual-Pivot Quicksort uses *two* pivots elements in this manner:
>>
>> 1. Pick an elements P1, P2, called pivots from the array.
>> 2. Assume that P1 <= P2, otherwise swap it.
>> 3. Reorder the array into three parts: those less than the smaller
>>    pivot, those larger than the larger pivot, and in between are
>>    those elements between (or equal to) the two pivots.
>> 4. Recursively sort the sub-arrays.
>>
>> The invariant of the Dual-Pivot Quicksort is:
>>
>> [ < P1 | P1 <= & <= P2 } > P2 ]
>>
>> The new Quicksort is faster than current implementation of Quicksort
>> in JDK (L. Bentley and M. Douglas McIlroy) and classical Quicksort.
>>
>> The full description of the Dual-Pivot Quicksort you can find
>> on my page: http://iaroslavski.narod.ru/quicksort
>>
>> Performance tests
>> -----------------
>> Here is result of running on different types of input data:
>>
>> Client VM                          all    85%  organ  0..1          0..4
>>              random ascend descend equal  equal pipes random 010101 
>> random
>> Dual-Pivot:  16.83  5.31    5.47   0.35  0.68  10.59  1.06   1.02   2.18
>>   Bentley's:  19.77  9.08   10.13   0.63  1.12  13.22  1.63   1.08   2.49
>>
>> Server VM                          all    85%  organ  0..1          0..4
>>              random ascend descend equal  equal pipes random 010101 
>> random
>> Dual-Pivot:  23.94  6.68    6.63   0.43  0.62  17.14  1.42   1.96   3.41
>>   Bentley's:  25.20 10.18   10.32   2.07  1.33  16.72  2.95   1.82   3.39
>>
>> The a lot of other tests have been run under client and server mode.
>> The most interesting is BentleyBasher test framework. It runs battery
>> of tests for all cases:
>>
>> { 100, 1000, 10000, 1000000 } x
>> { sawtooth, rand, stagger, plateau, shuffle } x
>> { ident, reverse, reverse_front, reverse_back, sort, dither}
>>
>> where
>>
>> 100, ... , 1000000 - array length
>>
>> sawtooth: x[i] =i%m
>> rand: x[i] = rand() % m
>> stagger: x[i] = (i*m + i) % n
>> plateau: x[i] = min(i, m)
>> shuffle: x[i] = rand()%m? (j+=2): (k+=2)
>>
>> ident(x) - a copy of x
>> reverse(x, 0, n) - reversed copy
>> reverse_front(x, 0, n/2) - front half reversed
>> reverse_back(x, n/2, n) - back half reversed
>> sort(x) - an ordered copy
>> dither(x) - add i%5 to x[i]
>>
>> Here is the result of execution:
>> Server VM: 
>> http://spreadsheets.google.com/pub?key=t_EAWUkQ4mD3BIbOv8Fa-AQ&output=html 
>>
>> Client VM: 
>> http://spreadsheets.google.com/pub?key=tdiMo8xleTxd23nKUObcz0Q&single=true&gid=0&output=html 
>>
>>
>> Mathematical investigations
>> ---------------------------
>> It is proved that for the Dual-Pivot Quicksort the average number of
>> comparisons is 2*n*ln(n), the average number of swaps is 0.8*n*ln(n),
>> whereas classical Quicksort algorithm has 2*n*ln(n) and 1*n*ln(n)
>> respectively. Full mathematical proof see in attached proof.txt
>> and proof_add.txt files. Theoretical results are also confirmed
>> by experimental counting of the operations.
>>
>> Diff between current and new implementation of Quicksort
>> --------------------------------------------------------
>>
>> Here is the link to the diff for java.util.Arrays class:
>> http://cr.openjdk.java.net/~alanb/6880672/webrev.00
>>
>> If you like to look and play with new algorithm,
>> please, take attached class DualPivotQuicksort.java
>>
>> Feedback
>> --------
>>
>> Also I'd like to share a feedback from Joshua Bloch and
>> Jon Bentley who spent a lot of time investigating this
>> algorithm, who gave me many advices and tips how to
>> make new Quicksort better.
>>
>> -------- Original Message --------
>> Subject: Re: Integration of new Dual-Pivot Quicksort into JDK 7
>> Date: Thu, 10 Sep 2009 07:20:11 -0700
>> From: Joshua Bloch <jjb at google.com>
>>
>> Jon also says that Vladimir should make every reasonable improvement to
>> the basic method before checking in the code. In his words, "It would be
>> horrible to put the new code into the library, and then have someone
>> else come along and speed it up by another 20% by using standard
>> techniques." I believe it's not unlikely that this code may end up
>> getting ported to many languages and widely deployed in much the manner
>> of Bentley and McIlroy's fine sort (which is nearing 20 successful years
>> in the field). Jon will help Vladimir do this.
>>
>> -------- Original Message --------
>> Subject: Dual-Pivot Quicksort: Next Steps
>> Date: Wed, 09 Sep 2009 15:02:25 -0400
>> From: Jon Bentley <jbentley at avaya.com>
>>
>> Vladimir, Josh,
>>      I *finally* feel like I understand what is going on.  Now that I
>> (think that) I see it, it seems straightforward and obvious.
>>      Tony Hoare developed Quicksort in the early 1960s. I was very
>> proud to make minor contributions to a particularly clean (binary)
>> quicksort in the mid 1980s, to a relatively straightforward, industrial
>> strength Quicksort with McIlroy in the early 1990s, and then to
>> algorithms and data structures for strings with Sedgewick in the mid 
>> 1990s.
>>      I think that Vladimir's contributions to Quicksort go way beyond
>> anything that I've ever done, and rank up there with Hoare's original
>> design and Sedgewick's analysis. I feel so privileged to play a very,
>> very minor role in helping Vladimir with the most excellent work!
>>
>> -----------------------------------------------
>>
>> Let me know, if you have any questions/comments.
>>
>> Thank you,
>> Vladimir