On Mon, May 01, 2017 at 07:26:35PM +0200, Levente Uzonyi wrote:
> I presume that a general purpose in-image solution would be more complex. 
> String already has too many subclasses (6 in Squeak), while at the same 
> time other kind of new subclasses would be welcome too, e.g. Strings with 
> 2-byte characters.
> Since these properties are orthogonal, there would be many new subclasses 
> to cover all cases.
> Storing the size of the string in a different header word is a VM specific 
> detail, so I think caching the hash could also be hidden from the image.
> 
> Levente

Actually, I meant something more like this:

   Object subclass: #LargeString
	instanceVariableNames: 'anyKindOfString cachedHashValueForTheString'
	classVariableNames: ''
	poolDictionaries: ''
	category: 'Probably a Bad Idea'


I was guessing that hashing very large strings would imply a somewhat
specialized problem domain, for which a wrapper class might make sense.
Certainly it would not be a general solution.

I am probably over my quota of bad ideas for today, so I'll stop now ;-)

Dave


> 
> On Mon, 1 May 2017, David T. Lewis wrote:
> 
> >
> >Does it need to be done in the VM? Why not make a class LargeString with
> >instance variables aString and myCalculatedHashValueForTheString. That way
> >you can cache the hash value and calculate it any way you want.
> >
> >I know vey little about hashing, just wondering if this kind of thing can
> >be handled more easily in the image.
> >
> >Dave
> >
> >
> >>
> >>On Mon, 1 May 2017, Levente Uzonyi wrote:
> >>
> >>>Well, I had started to write a reply, but I had to postpone it.
> >>>I mostly agree with your suggestions.
> >>>
> >>>One thing that can be done about large strings is to cache the
> >>>calculated
> >>>hash value in the larger strings. Currently the object representation
> >>>changes when the string contains 255 or more characters. In that case an
> >>>additional 64 bit field is added to the object header to store its
> >>>length.
> >>>If we were to use the upper 28+1 bits of that field to cache the hash,
> >>>there would still be 35-bits to encode length, which would be enough to
> >>>represent strings up to 8 GiB.
> >>
> >>Well, we can keep the whole range minus one bit, but then we can't store
> >>the hash for strings larger than 8 GiB.
> >>
> >>Levente
> >>
> >>>But this would require further VM changes (e.g. at:put: would have to
> >>>flush the cache).
> >>>
> >>>Levente
> >>>
> >>>On Mon, 1 May 2017, Martin McClure wrote:
> >>>
> >>>>I see no replies to this on any of the three lists it was sent to, so I
> >>>>guess I'll chime in.
> >>>>
> >>>>tl;dr:
> >>>>Making a primitive for #hashMultiply, probably a good idea, in some
> >>>>form, since doing it in Smalltalk is awkward.
> >>>>Only hashing every N-th character of large strings, probably a very bad
> >>>>idea. Performance might well get worse, the complexity does not seem
> >>>>justified, and it would open a sizeable security hole.
> >>>>
> >>>>More verbiage below for those interested.
> >>>>
> >>>>Regards,
> >>>>-Martin
> >>>>
> >>>>On 04/18/2017 07:09 PM, Eliot Miranda wrote:
> >>>>>Hi All,
> >>>>>
> >>>>>    the hash algorithm used for ByteString in Squeak and Pharo is good
> >>>>>for "small" strings and overkill for large strings.
> >>>>
> >>>>Why do you say it's overkill for large strings? Are there applications
> >>>>with large strings that are being negatively impacted by the current
> >>>>algorithm? Which ones, and impacted how?
> >>>>
> >>>>>It is important in many applications to get well distributed string
> >>>>>hashes, especially over the range of strings that constitute things
> >>>>>like method names, URLs, etc.  Consequently, the current algorithm
> >>>>>includes every character in a string.  This works very well for
> >>>>>"small" strings and results in very slow hashes (and hence long
> >>>>>latencies, because the hash is an uninterruptible primitive) for large
> >>>>>strings, where large may be several megabytes.
> >>>>
> >>>>A simple solution for the uninterruptable primitive is to not make it a
> >>>>primitive. Make #hashMultiply a primitive (since this particular kind
> >>>>of
> >>>>numeric modulo computation is really painful in Smalltalk), and do the
> >>>>rest in a loop in Smalltalk. It sounds like you've done the
> >>>>#hashMultiply primitive already.
> >>>>
> >>>>If the overhead of calling a primitive for each character proves to be
> >>>>too much, even with the faster primitive calling methodologies you
> >>>>talked about in the "Cog Primitive Performance" thread on the Vm-dev
> >>>>list, a more complex primitive could take a range of bytes, so large
> >>>>strings would be done in batches, solving the latency problem.
> >>>>
> >>>>>
> >>>>>Let's look at the basic hash algorithm.
> >>>>[...]
> >>>>>
> >>>>>In looking at this I've added a primitive for hashMultiply; primitive
> >>>>>#159 implements precisely self * 1664525 bitAnd: 16r0FFFFFFF for
> >>>>>SmallInteger and LargePositiveInteger receivers, as fast as possible
> >>>>>in the Cog JIT.  With this machinery in place it's instructive to
> >>>>>compare the cost of the primitive against the non-primitive Smalltalk
> >>>>>code.
> >>>>>
> >>>>>First let me introduce a set of replacement hash functions, newHashN.
> >>>>>These hash all characters in strings up to a certain size, and then no
> >>>>>more than that number for larger strings.  Here are newHash64 and
> >>>>>newHash2048, which use pure Smalltalk, including an inlined
> >>>>>hashMultiply written to avoid SmallInteger overflow.  Also measured
> >>>>>are the obvious variants newHash128, newHash256, newHash512 &
> >>>>>mewHash1024.
> >>>>>
> >>>>>
> >>>>[...]
> >>>>>So the idea here is to step through the string by 1 for strings sizes
> >>>>>up to N - 1, and by greater than 1 for strings of size >= N, limiting
> >>>>>the maximum number of characters sampled to between N // 2 and N - 1.
> >>>>
> >>>>The history of computing is littered with the bones of those who have
> >>>>tried this kind of thing. It doesn't end well. Yes, you get a faster
> >>>>hash function. And then you find, for sets of data that you or your
> >>>>users actually want to use, that you get collisions like crazy, and
> >>>>much
> >>>>worse overall performance than you started with.
> >>>>
> >>>>Sure, it works OK for the sets of data that the designer *tested*, and
> >>>>probably for the sets of data that they *anticipated*. But real-world
> >>>>data is tricky. It includes data sets where the characters that differ
> >>>>are the ones that the hash thinks are unimportant, and there goes your
> >>>>performance, by orders of magnitude. For instance, early versions of
> >>>>Java used a limited number of characters to hash strings. One of the
> >>>>biggest compatibility-breaking changes they were forced to make in
> >>>>later
> >>>>Java versions was to consider *all* characters in hashing. It turned
> >>>>out
> >>>>that it was very common to hash URLs, and many distinct URLs had most
> >>>>of
> >>>>their characters in common.
> >>>>
> >>>>And you don't always get to choose your data -- sometimes you have an
> >>>>opponent who is actively looking to create collisions as a
> >>>>denial-of-service attack. There was a fair-sized kerfluffle about this
> >>>>a
> >>>>few years ago -- most web scripting languages made it too easy to mount
> >>>>this kind of attack.
> >>>>
> >>>https://arstechnica.com/business/2011/12/huge-portions-of-web-vulnerable-to-hashing-denial-of-service-attack/
> >>>>"...an attacker can degenerate the hash table by sending lots of
> >>>>colliding keys. ...making it possible to exhaust hours of CPU time
> >>>>using
> >>>>a single HTTP request."
> >>>>To guard against this kind of attack you need a randomized element in
> >>>>your hash (not a bad idea for Smalltalk, actually, and pretty easy --
> >>>>mixing in the identity hash of the collection might be sufficient) or a
> >>>>cryptographic hash (not worth the computational expense for most
> >>>>purposes). However, even adding a randomized element would not prevent
> >>>>this kind of attack if you predictably completely ignore some
> >>>>characters
> >>>>of the input string. That just makes it *so* easy to generate data that
> >>>>validates, and is not equal, but causes collisions.
> >>>>
> >>>>So really, for general-purpose use (i.e. what's built into the
> >>>>language)
> >>>>hash *every* character of *all* strings. If someone finds that this is
> >>>>a
> >>>>performance problem in a real-world situation, it can be addressed in
> >>>>an
> >>>>application-specific way.
> >>>
> >>>
> >>
>