HashMap collision speed (regression 7->8)
Peter Levart
peter.levart at gmail.com
Thu Jan 8 22:10:10 UTC 2015
Bernd,
I tried to change the "comparableClassFor" myself and it didn't work
(HashMap is used very early in boot-up sequence and initializing
ClassValue at that time triggers a NPE).
Anyway, caching of "comparableClassFor" result would only potentially
improve the "badDistWithComp" result. But can not improve
"badDistNoComp" which is the one with speed regression as you're
benchmark suggests.
But your feeling that this is caused by "simpler" hashCode bits
spreading function is not correct. I tried to replace the hash() method
with the one that was in HM before and I get comparable results. This is
the JDK8 HashMap.hash() method:
static final int hash(Object key) {
int h;
return (key == null) ? 0 : (h = key.hashCode()) ^ (h >>> 16);
}
Benchmark (initialSize) Mode
Samples Score Score error Units
j.t.HashMapCollision.badDistNoComp 16 avgt 4
3171.264 1152.995 ms/op
j.t.HashMapCollision.badDistWithComp 16 avgt 4
2819.342 422.861 ms/op
j.t.HashMapCollision.goodDistNoComp 16 avgt 4
1026.064 72.049 ms/op
j.t.HashMapCollision.goodDistWithComp 16 avgt 4
1025.312 39.858 ms/op
...and this is my re-interpretation of pre JDK8 HashMap.hash():
static final int randomHash = mix32(System.currentTimeMillis() ^
System.nanoTime());
private static int mix32(long z) {
z = (z ^ (z >>> 33)) * 0xff51afd7ed558ccdL;
return (int)(((z ^ (z >>> 33)) * 0xc4ceb9fe1a85ec53L) >>> 32);
}
static final int hash(Object k) {
int h = k == null ? randomHash : randomHash ^ k.hashCode();
// This function ensures that hashCodes that differ only by
// constant multiples at each bit position have a bounded
// number of collisions (approximately 8 at default load factor).
h ^= (h >>> 20) ^ (h >>> 12);
return h ^ (h >>> 7) ^ (h >>> 4);
}
Benchmark (initialSize) Mode
Samples Score Score error Units
j.t.HashMapCollision.badDistNoComp 16 avgt 4
3257.348 1079.088 ms/op
j.t.HashMapCollision.badDistWithComp 16 avgt 4
2866.740 414.687 ms/op
j.t.HashMapCollision.goodDistNoComp 16 avgt 4
1041.068 99.370 ms/op
j.t.HashMapCollision.goodDistWithComp 16 avgt 4
1041.653 53.925 ms/op
Your benchmark does not show much difference. Perhaps the regression for
"badDistNoComp" case could be caused by the fact that with really bad
hashCode and no Comparable interface, the red-black tree becomes less
performant to search than a simple linked list of Nodes...
Regards, Peter
On 01/08/2015 08:41 PM, Bernd Eckenfels wrote:
> Hello Peter,
>
> yes it is only keys without an Compareable interface, but they are
> quite common. I think the main problem with the internal comparator
> (based on instance identity) is, that it would work for looking up the
> same instance again, but not for the case where the actual instance is
> re-created (as in my example code).
>
> I would love to test your modified code, but I don't have a
> OpenJDK build environment handy. Or actually I can try to get one, is
> there somewhere a Virtulisation or Cloud Image available which is
> pre-installed?
>
> I have (1.6) a compiled benchmark.jar here, in case anyone wants to try
> it:
>
> https://onedrive.live.com/redir?resid=A98B6F4E09966AFD!20440&authkey=!AFFk03-5jq21Xz0&ithint=file%2cjar
>
> BTW: I am (as usual) not expecting commoents on that, but just to
> mention it: the expected good behavior of degenerated hashmaps (due to
> the tree) was reason for removing the hashcode secret randomization. I
> wonder if that was such a good idea if colliding lookups (with more
> than a handfull of entries in a bucket) have this 50% penalty.
>
> Greetings
> Bernd
>
>
>
> Am Thu, 08 Jan 2015 20:22:13 +0100
> schrieb Peter Levart <peter.levart at gmail.com>:
>
>> Hi Bernd,
>>
>> It seems that only bad hash codes (without comparable keys) in JDK8
>> HM are worse than JDK7 HM.
>>
>>
>> Since you have already taken time to measure JDK7 vs JDK8 HM, could
>> you try to take the JDK8 source and just replace the internal
>> "comparableClassFor" method with the following implementation:
>>
>> static final ClassValue<Boolean> selfComparable = new
>> ClassValue<Boolean>() {
>> @Override
>> protected Boolean computeValue(Class<?> c) {
>> Type[] as; ParameterizedType p;
>> for (Type t : c.getGenericInterfaces()) {
>> if (t instanceof ParameterizedType &&
>> (p = (ParameterizedType) t).getRawType() ==
>> Comparable.class &&
>> (as = p.getActualTypeArguments()).length == 1 &&
>> as[0] == c) // type arg is c
>> return true;
>> }
>> return false;
>> }
>> };
>>
>> static Class<?> comparableClassFor(Object x) {
>> if (x instanceof Comparable) {
>> Class<?> c = x.getClass();
>> if (c == String.class || selfComparable.get(c)) {
>> return c;
>> }
>> }
>> return null;
>> }
>>
>>
>> ...and retry your measurements. I just want to see if it has any
>> impact.
>>
>>
>> Thanks, Peter
>>
>>
>> On 01/08/2015 05:38 PM, Bernd Eckenfels wrote:
>>> Hello,
>>>
>>> I think it was topic before, but I just wanted to point out, that
>>> it is still an topic on the internetz. :)
>>>
>>> Motivated by a StackOverflow question regarding HashMap performance
>>> regression in Java 8
>>>
>>> http://stackoverflow.com/questions/27759527/using-java-7-hashmap-in-java-8/27760442
>>>
>>> I made a JMH test and compared 7 and 8 speed. (the test is not very
>>> scientific as I dont really know how to squeeze the longrunning
>>> loop which alters state into the harness, but the results seem to
>>> be consitent wth theory and stopwatch testing)
>>>
>>> https://gist.github.com/ecki/9f69773eb29428a36077
>>>
>>> What can be seen is, that with a good distribution of hash keys 8
>>> looks faster than 7, and with a bad distribution of hash keys Java
>>> 7 is faster (unless you supply a Comparator for the key). (and a
>>> good distributed hashkey with comparable seems to be a bit slower)
>>>
>>> I think the regression is somewhat expected, but I guess its not
>>> widely known.
>>>
>>> (I do not use a cached hashcode, but it has a nearly trivial
>>> implementation just to make it more life like. the tests also
>>> compares different initial sizes, but they do not have an
>>> measurable effect on the performance, I show only default size
>>> below:)
>>>
>>> java version "1.7.0_72"
>>>
>>> Benchmark (initialSize) Mode Samp Score
>>> Error Units n.e.j.h.HashMapCollision.badDistNoComp 16 avgt 4
>>> 10847,318 ± 5596,690 ms/op n.e.j.h.HashMapCollision.badDistWithComp
>>> 16 avgt 4 10761,430 ± 5376,975 ms/op
>>> n.e.j.h.HashMapCollision.goodDistNoComp 16 avgt 4 3613,923 ±
>>> 254,823 ms/op n.e.j.h.HashMapCollision.goodDistWithComp 16 avgt
>>> 4 3656,229 ± 274,350 ms/op
>>> java version "1.8.0_25"
>>>
>>> Benchmark (initialSize) Mode Samp Score
>>> Error Units n.e.j.h.HashMapCollision.badDistNoComp 16 avgt 4
>>> 14309,880 ± 1811,709 ms/op <-slower
>>> n.e.j.h.HashMapCollision.badDistWithComp 16 avgt 4 8232,037 ±
>>> 5974,530 ms/op n.e.j.h.HashMapCollision.goodDistNoComp 16 avgt
>>> 4 3304,698 ± 116,866 ms/op
>>> n.e.j.h.HashMapCollision.goodDistWithComp 16 avgt 4 3425,762 ±
>>> 107,659 ms/op
>>>
>>>
>>> Greetings
>>> Bernd
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