HashMap collision speed (regression 7->8)

Peter Levart peter.levart at gmail.com
Sun Jan 11 23:26:35 UTC 2015


On 01/11/2015 10:00 PM, Doug Lea wrote:
> On 01/11/2015 02:26 PM, Peter Levart wrote:
>
>> Although majority of entries constitute the bins of size 13 or 14, 
>> there's only
>> a single hashCode value per bin.
>>
>> So in this benchmark, treeifying with non-comparable keys is a waste 
>> of effort.
>
> On the other hand, the waste seems to only cost about 10% in your runs.
> I wonder why the original report using jdk7 vs jdk8 seemed larger.

I don't know. I ran the same benchmark with same VM options on JDK 7 
too. Here are all results together:

Original JDK 7 HashMap (and JVM):

Benchmark                               (initialSize)   Mode 
Samples        Score  Score error    Units
j.t.HashMapCollision.badDistNoComp                 16     ss 60     
2839.458      157.299       ms
j.t.HashMapCollision.badDistWithComp               16     ss 60     
2673.924      187.063       ms
j.t.HashMapCollision.goodDistNoComp                16     ss 60      
686.972       32.928       ms
j.t.HashMapCollision.goodDistWithComp              16     ss 60      
631.001        6.574       ms

Original JDK 9 HashMap:

Benchmark                               (initialSize)   Mode 
Samples        Score  Score error    Units
j.t.HashMapCollision.badDistNoComp                 16     ss 60     
3011.738       78.249       ms
j.t.HashMapCollision.badDistWithComp               16     ss 60     
2984.280       48.315       ms
j.t.HashMapCollision.goodDistNoComp                16     ss 60      
682.060       52.341       ms
j.t.HashMapCollision.goodDistWithComp              16     ss 60      
685.705       55.183       ms

Original JDK 9 HashMap with TREEIFY_THRESHOLD = 1 << 20:

Benchmark                               (initialSize)   Mode 
Samples        Score  Score error    Units
j.t.HashMapCollision.badDistNoComp                 16     ss 60     
2780.771      236.647       ms
j.t.HashMapCollision.badDistWithComp               16     ss 60     
2541.740      233.429       ms
j.t.HashMapCollision.goodDistNoComp                16     ss 60      
757.364       67.869       ms
j.t.HashMapCollision.goodDistWithComp              16     ss 60      
671.617       54.943       ms

Caching of comparableClassFor (in ClassRepository - good for 
heterogeneous keys too):

Benchmark                               (initialSize)   Mode 
Samples        Score  Score error    Units
j.t.HashMapCollision.badDistNoComp                 16     ss 60     
3014.888       71.778       ms
j.t.HashMapCollision.badDistWithComp               16     ss 60     
2279.757       54.159       ms
j.t.HashMapCollision.goodDistNoComp                16     ss 60      
760.743       70.674       ms
j.t.HashMapCollision.goodDistWithComp              16     ss 60      
725.188       67.853       ms

Caching of comparableClassFor (internally - good for homogeneous keys only):

Benchmark                               (initialSize)   Mode 
Samples        Score  Score error    Units
j.t.HashMapCollision.badDistNoComp                 16     ss 60     
3026.707       84.571       ms
j.t.HashMapCollision.badDistWithComp               16     ss 60     
2137.296       66.140       ms
j.t.HashMapCollision.goodDistNoComp                16     ss 60      
635.964        8.213       ms
j.t.HashMapCollision.goodDistWithComp              16     ss 60      
685.129       46.783       ms

>
>>
>> Are there (non-forged) sets of non-comparable keys with hashCodes where
>> treeifying makes sense?
>
> Try using a class like:
>   class FHC { float f; int hashCode() { return 
> Float.floatToIntBits(f); } }
> and populate with instances with integral values for f.
>
> Similarly for doubles.
>
> Pre-jdk8, we devised a bit-smearing function that (among other
> constraints) did OK for float/double keys with integral values,
> that are not all that rare.  With treeification, we don't need to
> penalize classes with decent hashCodes by bit-smearing to still
> get OK performance for these kinds of cases where the tree-based
> hashCode comparison helps more than Comparability per se.

I see. These keys actually have unique or near unique hashCodes but 
which are not good for power of two length tables without bit-smearing. 
With tree bins we don't need heavy bit-smearing to get decent 
performance in speed, but the table gets quite sparse anyway (although 
this is the smaller of the space overheads - tree nodes are bigger). For 
example, for 1M integral Floats, we get the following:

 >>> Float ...
                  Capacity: 2097152
               Load factor: 0.75
                      Size: 1000000
                 Bin sizes: 0*1966080 1*0 2*0 3*24288 4*41248 5*0 6*0 
7*0 8*0 9*0 10*4456 11*22963 12*30554 13*7539 14*24 total=1000000
                Empty bins: 93.8 %
Unique hash codes per bin: 0*1966080 1*0 2*0 3*24288 4*41248 5*0 6*0 7*0 
8*0 9*0 10*4456 11*22963 12*30554 13*7539 14*24 total=1000000


>
> Also...
>
> It looks like the simplest path to a minor improvement is
> just to cache internally (your fourth test below). But I now
> recall not doing this because it adds to footprint and
> the field could prevent class unloading, for only a small
> benefit.

Footprint, yes (one reference field in HM instance), while class 
unloading is taken care of using WeakReference:

http://cr.openjdk.java.net/~plevart/jdk9-dev/HM.comparableClassFor/HomogeneousKeysCache/webrev.01/

>
> (Every time HashMap has changed, there have been reports of
> performance regressions even though typical performance
> generally improves.)
>
> -Doug

Regards, Peter

>
>
>>> Original JDK9 HashMap:
>>>
>>> Benchmark                               (initialSize)   Mode Samples
>>> Score  Score error    Units
>>> j.t.HashMapCollision.badDistNoComp                 16 ss        60
>>> 3011.738       78.249       ms
>>> j.t.HashMapCollision.badDistWithComp               16 ss        60
>>> 2984.280       48.315       ms
>>> j.t.HashMapCollision.goodDistNoComp                16 ss        60
>>> 682.060       52.341       ms
>>> j.t.HashMapCollision.goodDistWithComp              16 ss        60
>>> 685.705       55.183       ms
>>>
>>> Original JDK9 HashMap with TREEIFY_THRESHOLD = 1 << 20:
>>>
>>> Benchmark                               (initialSize)   Mode Samples
>>> Score  Score error    Units
>>> j.t.HashMapCollision.badDistNoComp                 16 ss        60
>>> 2780.771      236.647       ms
>>> j.t.HashMapCollision.badDistWithComp               16 ss        60
>>> 2541.740      233.429       ms
>>> j.t.HashMapCollision.goodDistNoComp                16 ss        60
>>> 757.364       67.869       ms
>>> j.t.HashMapCollision.goodDistWithComp              16 ss        60
>>> 671.617       54.943       ms
>>>
>>> Caching of comparableClassFor (in ClassRepository - good for 
>>> heterogeneous
>>> keys too):
>>>
>>> Benchmark                               (initialSize)   Mode Samples
>>> Score  Score error    Units
>>> j.t.HashMapCollision.badDistNoComp                 16 ss        60
>>> 3014.888       71.778       ms
>>> j.t.HashMapCollision.badDistWithComp               16 ss        60
>>> 2279.757       54.159       ms
>>> j.t.HashMapCollision.goodDistNoComp                16 ss        60
>>> 760.743       70.674       ms
>>> j.t.HashMapCollision.goodDistWithComp              16 ss        60
>>> 725.188       67.853       ms
>>>
>>> Caching of comparableClassFor (internally - good for homogeneous 
>>> keys only):
>>>
>>> Benchmark                               (initialSize)   Mode Samples
>>> Score  Score error    Units
>>> j.t.HashMapCollision.badDistNoComp                 16 ss        60
>>> 3026.707       84.571       ms
>>> j.t.HashMapCollision.badDistWithComp               16 ss        60
>>> 2137.296       66.140       ms
>>> j.t.HashMapCollision.goodDistNoComp                16 ss        60
>>> 635.964        8.213       ms
>>> j.t.HashMapCollision.goodDistWithComp              16 ss        60
>>> 685.129       46.783       ms
>>>
>>>
>




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