Thank you for the update. I am currently working on updating the
patch Neil Conway sent in against 8.0-ish that stores only the hash
in the index and locates the entries within the page using a binary
search. Then I will fold in your recent update.

On Sun, Oct 21, 2007 at 01:13:48PM -0700, Tom Raney wrote:
> Kenneth, I just pushed the revised patch (v2!).  The revised approach 
> samples the parent relation to estimate the number of tuples rather than 
> performing a complete scan.  In my tests, the estimate appears to be 
> accurate, erring on the larger side, which is fine.

Yes, larger is great and what we need to avoid all the index tuple
suffling between pages.

>> Tom,
>> That is great. I am looking forward to your patch. After the
>> issues that you needed to address, I think that it would be
>> reasonable to add a few more user settings for the hash index.
>> Fill-factor is too course a knob. The others that I have been
>> considering are:
>> maxtuples - Not really the maximum, but a target value to use
>>   for setting up the initial buckets. This would allow you to
>>   set it for data loads and avoid the "split-n-copy" trauma
>>   that you are trying to avoid with your new hash build process.
> If I understand you correctly, I believe we already do this with our 
> current build process, there should not be any splits of the index if we 
> estimated the tuple count correctly.  However, what gets you is collisions 
> where lots of overflow pages occur when distinct keys map to the same 
> bucket, or if you have lots of duplicate keys.  Because your overall tuple 
> count doesn't exceed the fill factor, no splits occur, but lengthy bucket 
> chains lead to lots of IOs.  You touch on this below.

Yes, you do address this in your patches and it works well for an
existing heap. My idea was to minimize the shuffling problem when we
are doing a data load and do not have a heap to get a count from
because it has not been loaded yet.
>> multiplicity - Try to capture use cases that would require many
>>   overflow pages. In particular, if we discard the normal index
>>   page layout we can skip the space overhead of the page pointer
>>   and generate a more compact index. Then you could use a few
>>   more hash bits to lookup the index entry in the page. How many
>>   bits would be determined by this factor. 8-bits would give
>>   you 256 sub-pieces that could each hold about 3 entries using
>>   the current 4-byte hash, or 2 entries using an 8-byte hash.
>> What do you think?
> Yes, this is a good direction.  If we can increase the number of buckets 
> and reduce the bucket size (either physically or virtually) to allow more 
> direct access without creating a huge index on disk, that would be ideal.  
> But, then if you do have collisions, overflows occur more frequently.  I 
> spoke with Neil Conway yesterday at the PG conference here in Portland and 
> he piqued my interest in examining his hash code more closely to see what 
> he has already done in this area.

Right, overflows would occur more frequently and any overflow would
allocate a full page. It may be possible to estimate the multiplicity
and minimize the use of overflow pages. If we know that on average that
there are no more than 10 items in a bucket, we can size the virtual
buckets on the first page to support 10 items and minimize the rollover
to an overflow page.

Other ideas, once we hit the overflow page, back-off to the current
fullpage use to maximize the fill-factor, possibly using Neil's
binary search to speed lookups within the overflow pages. Also, with
the smaller virtual buckets use the remaining space on the page as
the first overflow page to hopefully prevent needing to allocate a
full new overflow page. This would be most useful for the smaller
virtual bucket sizes and improve the overall packing efficiency of
the index. If we intend to take advantage of the O(1) behavior, it
will be most useful for large numbers of tuples, more than 10^9. A
32-bit hash is not good enough and we will need to use a 64-bit hash
to reduce collisions in the hash table and consequent need for overflow
pages. I already have the hash function updated to support 64-bit and
will look at getting that functional once I have the hash-only version
working with the 32-bit hashes. Also, without the need to store the
value in the index, we can boost the size of indexable fields to the
page size, and larger. I was tentatively targeting 32k as the implementation
max, because then hashing time becomes the issue. Of course, all of these
changes and options will need to be benchmarked and discussed.

Thank you again for posting the updated patch.


> -Tom
>> Cheers,
>> Ken
>> On Wed, Oct 17, 2007 at 03:31:58PM -0700, Tom Raney wrote:
>>> Kenneth,
>>> Great!
>>> Yes, we did update the code to use the estimate.  I will post the patch 
>>> with this update.  We only saw a very small difference in index build 
>>> time, but you may when you add many columns to the base relation. With 1 
>>> billion tuples, you should start to see the hash index outperform the 
>>> btree for some equality probes, I would imagine.  With a 90% fill factor, 
>>> the btree would require 4 levels to index that many tuples.  If the top 
>>> two were in memory, there would be 3 IOs needed.  I don't think PG 
>>> supports index only scans, so it will take the extra IO to probe the base 
>>> relation.  The hash may take up to 2 IOs and maybe even less (or maybe 
>>> more depending on how many overflow buckets there are).  It might be 
>>> interesting to fiddle with the fill factors of each index - hash pages 
>>> (buckets) default to 75% full. -Tom
>>>> Tom,
>>>> I am getting ready to stitch in an updated, simplified version
>>>> of Neil Conway's hash-only hash index patch. Did you have a
>>>> chance to update your sizing function to use the planner-like
>>>> estimate and not a full table scan? I would like to be able
>>>> to use that when my test table start to have 10^9 entries.
>>>> If you have not had a chance, I will try and add it myself.
>>>> Regards,
>>>> Ken
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