pgsql: Add a macro templatized hashtable.

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От Andres Freund
Тема pgsql: Add a macro templatized hashtable.
Дата
Msg-id E1bvBn6-0002DF-7c@gemulon.postgresql.org
обсуждение исходный текст
Ответы Re: pgsql: Add a macro templatized hashtable.  (Peter Eisentraut <peter.eisentraut@2ndquadrant.com>)
Список pgsql-committers
Add a macro templatized hashtable.

dynahash.c hash tables aren't quite fast enough for some
use-cases. There are several reasons for lacking performance:
- the use of chaining for collision handling makes them cache
  inefficient, that's especially an issue when the tables get bigger.
- as the element sizes for dynahash are only determined at runtime,
  offset computations are somewhat expensive
- hash and element comparisons are indirect function calls, causing
  unnecessary pipeline stalls
- it's two level structure has some benefits (somewhat natural
  partitioning), but increases the number of indirections
to fix several of these the hash tables have to be adjusted to the
individual use-case at compile-time. C unfortunately doesn't provide a
good way to do compile code generation (like e.g. c++'s templates for
all their weaknesses do).  Thus the somewhat ugly approach taken here is
to allow for code generation using a macro-templatized header file,
which generates functions and types based on a prefix and other
parameters.

Later patches use this infrastructure to use such hash tables for
tidbitmap.c (bitmap scans) and execGrouping.c (hash aggregation,
...). In queries where these use up a large fraction of the time, this
has been measured to lead to performance improvements of over 100%.

There are other cases where this could be useful (e.g. catcache.c).

The hash table design chosen is a variant of linear open-addressing. The
biggest disadvantage of simple linear addressing schemes are highly
variable lookup times due to clustering, and deletions leaving a lot of
tombstones around.  To address these issues a variant of "robin hood"
hashing is employed.  Robin hood hashing optimizes chaining lengths by
moving elements close to their optimal bucket ("rich" elements), out of
the way if a to-be-inserted element is further away from its optimal
position (i.e. it's "poor").  While that can make insertions slower, the
average lookup performance is a lot better, and higher fill factors can
be used in a still performant manner.  To avoid tombstones - which
normally solve the issue that a deleted node's presence is relevant to
determine whether a lookup needs to continue looking or is done -
buckets following a deleted element are shifted backwards, unless
they're empty or already at their optimal position.

There's further possible improvements that can be made to this
implementation. Amongst others:
- Use distance as a termination criteria during searches. This is
  generally a good idea, but I've been able to see the overhead of
  distance calculations in some cases.
- Consider combining the 'empty' status into the hashvalue, and enforce
  storing the hashvalue. That could, in some cases, increase memory
  density and remove a few instructions.
- Experiment further with the, very conservatively choosen, fillfactor.
- Make maximum size of hashtable configurable, to allow storing very
  very large tables. That'd require 64bit hash values to be more common
  than now, though.
- some smaller memcpy calls could be optimized to copy larger chunks
But since the new implementation is already considerably faster than
dynahash it seem sensible to start using it.

Reviewed-By: Tomas Vondra
Discussion: <20160727004333.r3e2k2y6fvk2ntup@alap3.anarazel.de>

Branch
------
master

Details
-------
http://git.postgresql.org/pg/commitdiff/b30d3ea824c5ccba43d3e942704f20686e7dbab8

Modified Files
--------------
src/include/lib/simplehash.h     | 878 +++++++++++++++++++++++++++++++++++++++
src/tools/pgindent/typedefs.list |   3 +
2 files changed, 881 insertions(+)


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