On 28 January 2016 at 14:06, Anastasia Lubennikova
31.08.2015 10:41, Anastasia Lubennikova:
I'm going to begin work on effective storage of duplicate
keys in B-tree index.
The main idea is to implement posting lists and posting
trees for B-tree index pages as it's already done for GIN.
In a nutshell, effective storing of duplicates in GIN is
organised as follows.
Index stores single index tuple for each unique key. That
index tuple points to posting list which contains pointers
to heap tuples (TIDs). If too many rows having the same key,
multiple pages are allocated for the TIDs and these
constitute so called posting tree.
You can find wonderful detailed descriptions in gin readme
and articles <http://www.cybertec.at/gin-just-an-index-type/>.
It also makes possible to apply compression algorithm to
posting list/tree and significantly decrease index size.
Read more in presentation (part 1)
Now new B-tree index tuple must be inserted for each table
row that we index.
It can possibly cause page split. Because of MVCC even
unique index could contain duplicates.
Storing duplicates in posting list/tree helps to avoid
I'd like to share the progress of my work. So here is a WIP
It provides effective duplicate handling using posting lists
the same way as GIN does it.
Layout of the tuples on the page is changed in the following way:
TID (ip_blkid, ip_posid) + key, TID (ip_blkid, ip_posid) +
key, TID (ip_blkid, ip_posid) + key
TID (N item pointers, posting list offset) + key, TID
(ip_blkid, ip_posid), TID (ip_blkid, ip_posid), TID
It seems that backward compatibility works well without any
changes. But I haven't tested it properly yet.
Here are some test results. They are obtained by test
functions test_btbuild and test_ginbuild, which you can find
in attached sql file.
i - number of distinct values in the index. So i=1 means that
all rows have the same key, and i=10000000 means that all
keys are different.
The other columns contain the index size (MB).
i B-tree Old B-tree New GIN
1 214,234375 87,7109375 10,2109375
10 214,234375 87,7109375 10,71875
100 214,234375 87,4375 15,640625
1000 214,234375 86,2578125 31,296875
10000 214,234375 78,421875 104,3046875
100000 214,234375 65,359375 49,078125
1000000 214,234375 90,140625 106,8203125
10000000 214,234375 214,234375 534,0625
You can note that the last row contains the same index sizes
for B-tree, which is quite logical - there is no compression
if all the keys are distinct.
Other cases looks really nice to me.
Next thing to say is that I haven't implemented posting list
compression yet. So there is still potential to decrease size
of compressed btree.
I'm almost sure, there are still some tiny bugs and missed
functions, but on the whole, the patch is ready for testing.
I'd like to get a feedback about the patch testing on some
real datasets. Any bug reports and suggestions are welcome.
Here is a couple of useful queries to inspect the data inside
the index pages:
create extension pageinspect;
select * from bt_metap('idx');
select bt.* from generate_series(1,1) as n, lateral
bt_page_stats('idx', n) as bt;
select n, bt.* from generate_series(1,1) as n, lateral
bt_page_items('idx', n) as bt;
And at last, the list of items I'm going to complete in the
1. Add storage_parameter 'enable_compression' for btree
access method which specifies whether the index handles
duplicates. default is 'off'
2. Bring back microvacuum functionality for compressed indexes.
3. Improve insertion speed. Insertions became significantly
slower with compressed btree, which is obviously not what we
4. Clean the code and comments, add related documentation.
This doesn't apply cleanly against current git head. Have you
caught up past commit 65c5fcd35?