In a similar effort to f01592f91, here we mostly rename shadowed local
variables to remove the warnings produced when compiling with
-Wshadow=compatible-local.
This fixes 63 warnings and leaves just 5.
Author: Justin Pryzby, David Rowley
Reviewed-by: Justin Pryzby
Discussion https://postgr.es/m/20220817145434.GC26426%40telsasoft.com
PostgreSQL contains the implementation of the red-black tree. The red-black
tree is the ordered data structure, and one of its advantages is the ability
to do inequality searches. This commit adds rbt_find_less() and
rbt_find_great() functions implementing these searches. While these searches
aren't yet used in the core code, they might be useful for extensions.
Discussion: https://postgr.es/m/CAGRrpzYE8-7GCoaPjOiL9T_HY605MRax-2jgTtLq236uksZ1Sw%40mail.gmail.com
Author: Steve Chavez, Alexander Korotkov
Reviewed-by: Alexander Korotkov
Get rid of the separate "FATAL" log level, as it was applied
so inconsistently as to be meaningless. This mostly involves
s/pg_log_fatal/pg_log_error/g.
Create a macro pg_fatal() to handle the common use-case of
pg_log_error() immediately followed by exit(1). Various
modules had already invented either this or equivalent macros;
standardize on pg_fatal() and apply it where possible.
Invent the ability to add "detail" and "hint" messages to a
frontend message, much as we have long had in the backend.
Except where rewording was needed to convert existing coding
to detail/hint style, I have (mostly) resisted the temptation
to change existing message wording.
Patch by me. Design and patch reviewed at various stages by
Robert Haas, Kyotaro Horiguchi, Peter Eisentraut and
Daniel Gustafsson.
Discussion: https://postgr.es/m/1363732.1636496441@sss.pgh.pa.us
The previous coding of dshash_seq_next(), on the first call, accessed
status->hash_table->size_log2 without holding a partition lock and without
guaranteeing that ensure_valid_bucket_pointers() had ever been called.
That oversight turns out to not have immediately visible effects, because
bucket 0 is always in partition 0, and ensure_valid_bucket_pointers() was
called after acquiring the partition lock. However,
PARTITION_FOR_BUCKET_INDEX() with a size_log2 of 0 ends up triggering formally
undefined behaviour.
Simplify by accessing partition 0, without using PARTITION_FOR_BUCKET_INDEX().
While at it, remove dshash_get_current(), there is no convincing use
case. Also polish a few comments.
Author: Andres Freund <andres@anarazel.de>
Reviewed-By: Thomas Munro <thomas.munro@gmail.com>
Discussion: https://postgr.es/m/CA+hUKGL9hY_VY=+oUK+Gc1iSRx-Ls5qeYJ6q=dQVZnT3R63Taw@mail.gmail.com
Add ability to scan all entries sequentially to dshash. The interface is
similar but a bit different both from that of dynahash and simple dshash
search functions. The most significant differences is that dshash's interfac
always needs a call to dshash_seq_term when scan ends. Another is
locking. Dshash holds partition lock when returning an entry,
dshash_seq_next() also holds lock when returning an entry but callers
shouldn't release it, since the lock is essential to continue a scan. The
seqscan interface allows entry deletion while a scan is in progress using
dshash_delete_current().
Reviewed-By: Andres Freund <andres@anarazel.de>
Author: Kyotaro Horiguchi <horikyoga.ntt@gmail.com>
The code does not expect sh_error() to return, but the patch
that made this header usable in frontend didn't get that memo.
While here, plaster unlikely() on the tests that decide whether
to invoke sh_error(), and add our standard copyright notice.
Noted by Andres Freund. Back-patch to v13 where this frontend
support came in.
Discussion: https://postgr.es/m/0D54435C-1199-4361-9D74-2FBDCF8EA164@anarazel.de
I just got burnt by trying to use pg_malloc instead of pg_malloc0
with this. Save the next hacker some time by not leaving this
API detail undocumented.
This fixes a bug in simplehash.h which caused an incorrect size mask to be
used when the hash table grew to SH_MAX_SIZE (2^32). The code was
incorrectly setting the size mask to 0 when the hash tables reached the
maximum possible number of buckets. This would result always trying to
use the 0th bucket causing an infinite loop of trying to grow the hash
table due to there being too many collisions.
Seemingly it's not that common for simplehash tables to ever grow this big
as this bug dates back to v10 and nobody seems to have noticed it before.
However, probably the most likely place that people would notice it would
be doing a large in-memory Hash Aggregate with something close to at least
2^31 groups.
After this fix, the code now works correctly with up to within 98% of 2^32
groups and will fail with the following error when trying to insert any
more items into the hash table:
ERROR: hash table size exceeded
However, the work_mem (or hash_mem_multiplier in newer versions) settings
will generally cause Hash Aggregates to spill to disk long before reaching
that many groups. The minimal test case I did took a work_mem setting of
over 192GB to hit the bug.
simplehash hash tables are used in a few other places such as Bitmap Index
Scans, however, again the size that the hash table can become there is
also limited to work_mem and it would take a relation of around 16TB
(2^31) pages and a very large work_mem setting to hit this. With smaller
work_mem values the table would become lossy and never grow large enough
to hit the problem.
Author: Yura Sokolov
Reviewed-by: David Rowley, Ranier Vilela
Discussion: https://postgr.es/m/b1f7f32737c3438136f64b26f4852b96@postgrespro.ru
Backpatch-through: 10, where simplehash.h was added
Also "make reformat-dat-files".
The only change worthy of note is that pgindent messed up the formatting
of launcher.c's struct LogicalRepWorkerId, which led me to notice that
that struct wasn't used at all anymore, so I just took it out.
Comment fixes are applied on HEAD, and documentation improvements are
applied on back-branches where needed.
Author: Justin Pryzby
Discussion: https://postgr.es/m/20210408164008.GJ6592@telsasoft.com
Backpatch-through: 9.6
Here we add a new executor node type named "Result Cache". The planner
can include this node type in the plan to have the executor cache the
results from the inner side of parameterized nested loop joins. This
allows caching of tuples for sets of parameters so that in the event that
the node sees the same parameter values again, it can just return the
cached tuples instead of rescanning the inner side of the join all over
again. Internally, result cache uses a hash table in order to quickly
find tuples that have been previously cached.
For certain data sets, this can significantly improve the performance of
joins. The best cases for using this new node type are for join problems
where a large portion of the tuples from the inner side of the join have
no join partner on the outer side of the join. In such cases, hash join
would have to hash values that are never looked up, thus bloating the hash
table and possibly causing it to multi-batch. Merge joins would have to
skip over all of the unmatched rows. If we use a nested loop join with a
result cache, then we only cache tuples that have at least one join
partner on the outer side of the join. The benefits of using a
parameterized nested loop with a result cache increase when there are
fewer distinct values being looked up and the number of lookups of each
value is large. Also, hash probes to lookup the cache can be much faster
than the hash probe in a hash join as it's common that the result cache's
hash table is much smaller than the hash join's due to result cache only
caching useful tuples rather than all tuples from the inner side of the
join. This variation in hash probe performance is more significant when
the hash join's hash table no longer fits into the CPU's L3 cache, but the
result cache's hash table does. The apparent "random" access of hash
buckets with each hash probe can cause a poor L3 cache hit ratio for large
hash tables. Smaller hash tables generally perform better.
The hash table used for the cache limits itself to not exceeding work_mem
* hash_mem_multiplier in size. We maintain a dlist of keys for this cache
and when we're adding new tuples and realize we've exceeded the memory
budget, we evict cache entries starting with the least recently used ones
until we have enough memory to add the new tuples to the cache.
For parameterized nested loop joins, we now consider using one of these
result cache nodes in between the nested loop node and its inner node. We
determine when this might be useful based on cost, which is primarily
driven off of what the expected cache hit ratio will be. Estimating the
cache hit ratio relies on having good distinct estimates on the nested
loop's parameters.
For now, the planner will only consider using a result cache for
parameterized nested loop joins. This works for both normal joins and
also for LATERAL type joins to subqueries. It is possible to use this new
node for other uses in the future. For example, to cache results from
correlated subqueries. However, that's not done here due to some
difficulties obtaining a distinct estimation on the outer plan to
calculate the estimated cache hit ratio. Currently we plan the inner plan
before planning the outer plan so there is no good way to know if a result
cache would be useful or not since we can't estimate the number of times
the subplan will be called until the outer plan is generated.
The functionality being added here is newly introducing a dependency on
the return value of estimate_num_groups() during the join search.
Previously, during the join search, we only ever needed to perform
selectivity estimations. With this commit, we need to use
estimate_num_groups() in order to estimate what the hit ratio on the
result cache will be. In simple terms, if we expect 10 distinct values
and we expect 1000 outer rows, then we'll estimate the hit ratio to be
99%. Since cache hits are very cheap compared to scanning the underlying
nodes on the inner side of the nested loop join, then this will
significantly reduce the planner's cost for the join. However, it's
fairly easy to see here that things will go bad when estimate_num_groups()
incorrectly returns a value that's significantly lower than the actual
number of distinct values. If this happens then that may cause us to make
use of a nested loop join with a result cache instead of some other join
type, such as a merge or hash join. Our distinct estimations have been
known to be a source of trouble in the past, so the extra reliance on them
here could cause the planner to choose slower plans than it did previous
to having this feature. Distinct estimations are also fairly hard to
estimate accurately when several tables have been joined already or when a
WHERE clause filters out a set of values that are correlated to the
expressions we're estimating the number of distinct value for.
For now, the costing we perform during query planning for result caches
does put quite a bit of faith in the distinct estimations being accurate.
When these are accurate then we should generally see faster execution
times for plans containing a result cache. However, in the real world, we
may find that we need to either change the costings to put less trust in
the distinct estimations being accurate or perhaps even disable this
feature by default. There's always an element of risk when we teach the
query planner to do new tricks that it decides to use that new trick at
the wrong time and causes a regression. Users may opt to get the old
behavior by turning the feature off using the enable_resultcache GUC.
Currently, this is enabled by default. It remains to be seen if we'll
maintain that setting for the release.
Additionally, the name "Result Cache" is the best name I could think of
for this new node at the time I started writing the patch. Nobody seems
to strongly dislike the name. A few people did suggest other names but no
other name seemed to dominate in the brief discussion that there was about
names. Let's allow the beta period to see if the current name pleases
enough people. If there's some consensus on a better name, then we can
change it before the release. Please see the 2nd discussion link below
for the discussion on the "Result Cache" name.
Author: David Rowley
Reviewed-by: Andy Fan, Justin Pryzby, Zhihong Yu, Hou Zhijie
Tested-By: Konstantin Knizhnik
Discussion: https://postgr.es/m/CAApHDvrPcQyQdWERGYWx8J%2B2DLUNgXu%2BfOSbQ1UscxrunyXyrQ%40mail.gmail.com
Discussion: https://postgr.es/m/CAApHDvq=yQXr5kqhRviT2RhNKwToaWr9JAN5t+5_PzhuRJ3wvg@mail.gmail.com
This removes "Add Result Cache executor node". It seems that something
weird is going on with the tracking of cache hits and misses as
highlighted by many buildfarm animals. It's not yet clear what the
problem is as other parts of the plan indicate that the cache did work
correctly, it's just the hits and misses that were being reported as 0.
This is especially a bad time to have the buildfarm so broken, so
reverting before too many more animals go red.
Discussion: https://postgr.es/m/CAApHDvq_hydhfovm4=izgWs+C5HqEeRScjMbOgbpC-jRAeK3Yw@mail.gmail.com
Here we add a new executor node type named "Result Cache". The planner
can include this node type in the plan to have the executor cache the
results from the inner side of parameterized nested loop joins. This
allows caching of tuples for sets of parameters so that in the event that
the node sees the same parameter values again, it can just return the
cached tuples instead of rescanning the inner side of the join all over
again. Internally, result cache uses a hash table in order to quickly
find tuples that have been previously cached.
For certain data sets, this can significantly improve the performance of
joins. The best cases for using this new node type are for join problems
where a large portion of the tuples from the inner side of the join have
no join partner on the outer side of the join. In such cases, hash join
would have to hash values that are never looked up, thus bloating the hash
table and possibly causing it to multi-batch. Merge joins would have to
skip over all of the unmatched rows. If we use a nested loop join with a
result cache, then we only cache tuples that have at least one join
partner on the outer side of the join. The benefits of using a
parameterized nested loop with a result cache increase when there are
fewer distinct values being looked up and the number of lookups of each
value is large. Also, hash probes to lookup the cache can be much faster
than the hash probe in a hash join as it's common that the result cache's
hash table is much smaller than the hash join's due to result cache only
caching useful tuples rather than all tuples from the inner side of the
join. This variation in hash probe performance is more significant when
the hash join's hash table no longer fits into the CPU's L3 cache, but the
result cache's hash table does. The apparent "random" access of hash
buckets with each hash probe can cause a poor L3 cache hit ratio for large
hash tables. Smaller hash tables generally perform better.
The hash table used for the cache limits itself to not exceeding work_mem
* hash_mem_multiplier in size. We maintain a dlist of keys for this cache
and when we're adding new tuples and realize we've exceeded the memory
budget, we evict cache entries starting with the least recently used ones
until we have enough memory to add the new tuples to the cache.
For parameterized nested loop joins, we now consider using one of these
result cache nodes in between the nested loop node and its inner node. We
determine when this might be useful based on cost, which is primarily
driven off of what the expected cache hit ratio will be. Estimating the
cache hit ratio relies on having good distinct estimates on the nested
loop's parameters.
For now, the planner will only consider using a result cache for
parameterized nested loop joins. This works for both normal joins and
also for LATERAL type joins to subqueries. It is possible to use this new
node for other uses in the future. For example, to cache results from
correlated subqueries. However, that's not done here due to some
difficulties obtaining a distinct estimation on the outer plan to
calculate the estimated cache hit ratio. Currently we plan the inner plan
before planning the outer plan so there is no good way to know if a result
cache would be useful or not since we can't estimate the number of times
the subplan will be called until the outer plan is generated.
The functionality being added here is newly introducing a dependency on
the return value of estimate_num_groups() during the join search.
Previously, during the join search, we only ever needed to perform
selectivity estimations. With this commit, we need to use
estimate_num_groups() in order to estimate what the hit ratio on the
result cache will be. In simple terms, if we expect 10 distinct values
and we expect 1000 outer rows, then we'll estimate the hit ratio to be
99%. Since cache hits are very cheap compared to scanning the underlying
nodes on the inner side of the nested loop join, then this will
significantly reduce the planner's cost for the join. However, it's
fairly easy to see here that things will go bad when estimate_num_groups()
incorrectly returns a value that's significantly lower than the actual
number of distinct values. If this happens then that may cause us to make
use of a nested loop join with a result cache instead of some other join
type, such as a merge or hash join. Our distinct estimations have been
known to be a source of trouble in the past, so the extra reliance on them
here could cause the planner to choose slower plans than it did previous
to having this feature. Distinct estimations are also fairly hard to
estimate accurately when several tables have been joined already or when a
WHERE clause filters out a set of values that are correlated to the
expressions we're estimating the number of distinct value for.
For now, the costing we perform during query planning for result caches
does put quite a bit of faith in the distinct estimations being accurate.
When these are accurate then we should generally see faster execution
times for plans containing a result cache. However, in the real world, we
may find that we need to either change the costings to put less trust in
the distinct estimations being accurate or perhaps even disable this
feature by default. There's always an element of risk when we teach the
query planner to do new tricks that it decides to use that new trick at
the wrong time and causes a regression. Users may opt to get the old
behavior by turning the feature off using the enable_resultcache GUC.
Currently, this is enabled by default. It remains to be seen if we'll
maintain that setting for the release.
Additionally, the name "Result Cache" is the best name I could think of
for this new node at the time I started writing the patch. Nobody seems
to strongly dislike the name. A few people did suggest other names but no
other name seemed to dominate in the brief discussion that there was about
names. Let's allow the beta period to see if the current name pleases
enough people. If there's some consensus on a better name, then we can
change it before the release. Please see the 2nd discussion link below
for the discussion on the "Result Cache" name.
Author: David Rowley
Reviewed-by: Andy Fan, Justin Pryzby, Zhihong Yu
Tested-By: Konstantin Knizhnik
Discussion: https://postgr.es/m/CAApHDvrPcQyQdWERGYWx8J%2B2DLUNgXu%2BfOSbQ1UscxrunyXyrQ%40mail.gmail.com
Discussion: https://postgr.es/m/CAApHDvq=yQXr5kqhRviT2RhNKwToaWr9JAN5t+5_PzhuRJ3wvg@mail.gmail.com
Previously simplehash.h only exposed a method to perform a hash table
delete using the hash table key. This meant that the delete function had
to perform a hash lookup in order to find the entry to delete. Here we
add a new function so that users of simplehash.h can perform a hash delete
directly using the entry pointer, thus saving the hash lookup.
An upcoming patch that uses simplehash.h already has performed the hash
lookup so already has the entry pointer. This change will allow the
code in that patch to perform the hash delete without the code in
simplehash.h having to perform an additional hash lookup.
Author: David Rowley
Reviewed-by: Andres Freund
Discussion: https://postgr.es/m/CAApHDvqFLXXge153WmPsjke5VGOSt7Ez0yD0c7eBXLfmWxs3Kw@mail.gmail.com
When reading the code it's not obvious when one should prefer dynahash
over simplehash and vice-versa, so, for programmer-friendliness, add
comments to inform that decision.
Show sample simplehash method signatures.
Author: James Coleman <jtc331@gmail.com>
Discussion: https://postgr.es/m/CAAaqYe_dOF39gAJ8rL-a3YO3Qo96MHMRQ2whFjK5ZcU6YvMQSA%40mail.gmail.com
Includes some manual cleanup of places that pgindent messed up,
most of which weren't per project style anyway.
Notably, it seems some people didn't absorb the style rules of
commit c9d297751, because there were a bunch of new occurrences
of function calls with a newline just after the left paren, all
with faulty expectations about how the rest of the call would get
indented.
First pass of modifying various places that obtain the next power of 2 of
a number and make them use the new functions added in pg_bitutils.h
instead.
This also removes the _hash_log2() function. There are no longer any
callers in core. Other users can swap their _hash_log2(n) call to make use
of pg_ceil_log2_32(n).
Author: David Fetter, with some minor adjustments by me
Reviewed-by: John Naylor, Jesse Zhang
Discussion: https://postgr.es/m/20200114173553.GE32763%40fetter.org
Commit 48995040d5 removed the largest
barrier to use of simplehash in frontend code, but there's one more
problem: it uses elog(ERROR, ...) or elog(LOG, ...) in a couple of
places. Work around that by changing those to pg_log_error() and
pg_log_info() when FRONTEND is defined.
Patch by me, reviewed by Andres Freund.
Discussion: http://postgr.es/m/CA+Tgmob8oyh02NrZW=xCScB+5GyJ-jVowE3+TWTUmPF=FsGWTA@mail.gmail.com
If the SH_RAW_ALLOCATOR is defined, it will be used to allocate bytes
for the hash table, and no dependencies on MemoryContext will exist.
This means, in particular, that the SH_CREATE function will not take
a MemoryContext argument.
Patch by me, reviewed by Andres Freund.
Discussion: http://postgr.es/m/CA+Tgmob8oyh02NrZW=xCScB+5GyJ-jVowE3+TWTUmPF=FsGWTA@mail.gmail.com
There's plenty places in frontend code that could benefit from a
string buffer implementation. Some because it yields simpler and
faster code, and some others because of the desire to share code
between backend and frontend.
While there is a string buffer implementation available to frontend
code, libpq's PQExpBuffer, it is clunkier than stringinfo, it
introduces a libpq dependency, doesn't allow for sharing between
frontend and backend code, and has a higher API/ABI stability
requirement due to being exposed via libpq.
Therefore it seems best to just making StringInfo being usable by
frontend code. There's not much to do for that, except for rewriting
two subsequent elog/ereport calls into others types of error
reporting, and deciding on a maximum string length.
For the maximum string size I decided to privately define MaxAllocSize
to the same value as used in the backend. It seems likely that we'll
want to reconsider this for both backend and frontend code in the not
too far away future.
For now I've left stringinfo.h in lib/, rather than common/, to reduce
the likelihood of unnecessary breakage. We could alternatively decide
to provide a redirecting stringinfo.h in lib/, or just not provide
compatibility.
Author: Andres Freund
Reviewed-By: Kyotaro Horiguchi, Daniel Gustafsson
Discussion: https://postgr.es/m/20190920051857.2fhnvhvx4qdddviz@alap3.anarazel.de
Add _lookup_hash and _insert_hash functions for callers that have
already calculated the hash value of the key.
The immediate use case is for hash algorithms that write to disk in
partitions. The hash value can be calculated once, used to perform a
lookup, used to select the partition, then written to the partition
along with the tuple. When the tuple is read back, the hash value does
not need to be recalculated.
Author: Jeff Davis
Reviewed-by: Andres Freund
Discussion: https://postgr.es/m/48abe675e1330f0c264ab2fe0d4ff23eb244f9ef.camel%40j-davis.com
The set is implemented as a B-tree, with a compact representation at leaf
items, using Simple-8b algorithm, so that clusters of nearby values use
less memory.
The IntegerSet isn't used for anything yet, aside from the test code, but
we have two patches in the works that would benefit from this: A patch to
allow GiST vacuum to delete empty pages, and a patch to reduce heap
VACUUM's memory usage, by storing the list of dead TIDs more efficiently
and lifting the 1 GB limit on its size.
This includes a unit test module, in src/test/modules/test_integerset.
It can be used to verify correctness, as a regression test, but if you run
it manully, it can also print memory usage and execution time of some of
the tests.
Author: Heikki Linnakangas, Andrey Borodin
Reviewed-by: Julien Rouhaud
Discussion: https://www.postgresql.org/message-id/b5e82599-1966-5783-733c-1a947ddb729f@iki.fi
The "rb" prefix is used by Ruby, so that our existing code results
in name collisions that break plruby. We discussed ways to prevent
that by adjusting dynamic linker options, but it seems that at best
we'd move the pain to other cases. Renaming to avoid the collision
is the only portable fix anyway. Fortunately, our rbtree code is
not (yet?) widely used --- in core, there's only a single usage
in GIN --- so it seems likely that we can get away with a rename.
I chose to do this basically as s/rb/rbt/g, except for places where
there already was a "t" after "rb". The patch could have been made
smaller by only touching linker-visible symbols, but it would have
resulted in oddly inconsistent-looking code. Better to make it look
like "rbt" was the plan all along.
Back-patch to v10. The rbtree.c code exists back to 9.5, but
rb_iterate() which is the actual immediate source of pain was added
in v10, so it seems like changing the names before that would have
more risk than benefit.
Per report from Pavel Raiskup.
Discussion: https://postgr.es/m/4738198.8KVIIDhgEB@nb.usersys.redhat.com
Fix reference to non-existent file in comment.
Add SH_ prefix to the EMPTY and IN_USE tokens, to reduce likelihood of
collisions with unrelated macros.
Add include guards around the function definitions that are not
"parameterized", so the header can be used again in the same translation
unit.
Undefine SH_EQUAL macro where other "parameter" macros are undefined, for
the same reason.
Author: Thomas Munro
Reviewed-by: Tom Lane
Discussion: https://postgr.es/m/CAEepm%3D1LdXZ3mMTM8tHt_b%3DK1kREit%3Dp8sikesak%3DkzHHM07Nw%40mail.gmail.com
A Bloom filter is a space-efficient, probabilistic data structure that
can be used to test set membership. Callers will sometimes incur false
positives, but never false negatives. The rate of false positives is a
function of the total number of elements and the amount of memory
available for the Bloom filter.
Two classic applications of Bloom filters are cache filtering, and data
synchronization testing. Any user of Bloom filters must accept the
possibility of false positives as a cost worth paying for the benefit in
space efficiency.
This commit adds a test harness extension module, test_bloomfilter. It
can be used to get a sense of how the Bloom filter implementation
performs under varying conditions.
This is infrastructure for the upcoming "heapallindexed" amcheck patch,
which verifies the consistency of a heap relation against one of its
indexes.
Author: Peter Geoghegan
Reviewed-By: Andrey Borodin, Michael Paquier, Thomas Munro, Andres Freund
Discussion: https://postgr.es/m/CAH2-Wzm5VmG7cu1N-H=nnS57wZThoSDQU+F5dewx3o84M+jY=g@mail.gmail.com
For consistency with other code that deals in numbers of buckets, the
macro BUCKETS_PER_PARTITION should produce a value of type size_t.
Also, fix a mention of an obsolete proposed name for dshash.c that
appeared in a comment.
Author: Thomas Munro, based on an observation from Amit Kapila
Discussion: https://postgr.es/m/CAA4eK1%2BBOp5aaW3aHEkg5Bptf8Ga_BkBnmA-%3DXcAXShs0yCiYQ%40mail.gmail.com
Other header files should never #include postgres.h (nor postgres_fe.h,
nor c.h), per project policy. Also, there's no need for any backend .c
file to explicitly include elog.h or palloc.h, because postgres.h pulls
those in already.
Extracted from a larger patch by Kyotaro Horiguchi. The rest of the
removals he suggests require more study, but these are no-brainers.
Discussion: https://postgr.es/m/20180215.200447.209320006.horiguchi.kyotaro@lab.ntt.co.jp
In cases where simplehash tables where filled with either a lot of
conflicting hash-values, or values that hash to consecutive
values (i.e. build "chains") the growth heuristics in
d4c62a6b62 could trigger rather
explosively.
To fix that, address some of the reasons (see previous commit) of why
the growth heuristics where needed, and only allow growth when the
table isn't too empty. While that means there's a few cases of bad
input that can be slower, that seems a lot better than running very
quickly out of memory.
Author: Tomas Vondra and Andres Freund, with additional input by
Thomas Munro, Tom Lane Todd A. Cook
Reported-By: Todd A. Cook, Tomas Vondra, Thomas Munro
Discussion: https://postgr.es/m/20171127185700.1470.20362@wrigleys.postgresql.org
Backpatch: 10, where simplehash was introduced
In a lot of the places having appendBinaryStringInfo() maintain a
trailing NUL byte wasn't actually meaningful, e.g. when appending an
integer which can contain 0 in one of its bytes.
Removing this yields some small speedup, but more importantly will be
more consistent when providing faster variants of pq_sendint etc.
Author: Andres Freund
Discussion: https://postgr.es/m/20170914063418.sckdzgjfrsbekae4@alap3.anarazel.de
This code isn't used, and there's no clear reason why anybody would ever
want to use it. These traversal mechanisms don't yield a visitation order
that is semantically meaningful for any external purpose, nor are they
any faster or simpler than the left-to-right or right-to-left traversals.
(In fact, some rough testing suggests they are slower :-(.) Moreover,
these mechanisms are impossible to test in any arm's-length fashion; doing
so requires knowledge of the red-black tree's internal implementation.
Hence, let's just jettison them.
Discussion: https://postgr.es/m/17735.1505003111@sss.pgh.pa.us
Some compilers complain, not unreasonably, about left-shifting an
int32 "1" and then assigning the result to an int64. In practice
I sure hope that this data structure never gets large enough that
an overflow would actually occur; but let's cast the constant to
the right type to avoid the hazard.
In passing, fix a typo in dshash.h.
Amit Kapila, adjusted as per comment from Thomas Munro.
Discussion: https://postgr.es/m/CAA4eK1+5vfVMYtjK_NX8O3-42yM3o80qdqWnQzGquPrbq6mb+A@mail.gmail.com
Commit 8c0d7bafad introduced dshash with hash
and compare functions like DynaHash's, and also variants that take a user
data pointer instead of size. Simplify the interface by merging them into
a single pair of function pointer types that take both size and a user data
pointer.
Since it is anticipated that memcmp and tag_hash behavior will be a common
requirement, provide wrapper functions dshash_memcmp and dshash_memhash that
conform to the new function types.
Author: Thomas Munro
Reviewed-By: Andres Freund
Discussion: https://postgr.es/m/20170823054644.efuzftxjpfi6wwqs%40alap3.anarazel.de
Add general purpose chaining hash tables for DSA memory. Unlike
DynaHash in shared memory mode, these hash tables can grow as
required, and cope with being mapped into different addresses in
different backends.
There is a wide range of potential users for such a hash table, though
it's very likely the interface will need to evolve as we come to
understand the needs of different kinds of users. E.g support for
iterators and incremental resizing is planned for later commits and
the details of the callback signatures are likely to change.
Author: Thomas Munro
Reviewed-By: John Gorman, Andres Freund, Dilip Kumar, Robert Haas
Discussion:
https://postgr.es/m/CAEepm=3d8o8XdVwYT6O=bHKsKAM2pu2D6sV1S_=4d+jStVCE7w@mail.gmail.comhttps://postgr.es/m/CAEepm=0ZtQ-SpsgCyzzYpsXS6e=kZWqk3g5Ygn3MDV7A8dabUA@mail.gmail.com
Don't move parenthesized lines to the left, even if that means they
flow past the right margin.
By default, BSD indent lines up statement continuation lines that are
within parentheses so that they start just to the right of the preceding
left parenthesis. However, traditionally, if that resulted in the
continuation line extending to the right of the desired right margin,
then indent would push it left just far enough to not overrun the margin,
if it could do so without making the continuation line start to the left of
the current statement indent. That makes for a weird mix of indentations
unless one has been completely rigid about never violating the 80-column
limit.
This behavior has been pretty universally panned by Postgres developers.
Hence, disable it with indent's new -lpl switch, so that parenthesized
lines are always lined up with the preceding left paren.
This patch is much less interesting than the first round of indent
changes, but also bulkier, so I thought it best to separate the effects.
Discussion: https://postgr.es/m/E1dAmxK-0006EE-1r@gemulon.postgresql.org
Discussion: https://postgr.es/m/30527.1495162840@sss.pgh.pa.us
Change pg_bsd_indent to follow upstream rules for placement of comments
to the right of code, and remove pgindent hack that caused comments
following #endif to not obey the general rule.
Commit e3860ffa4d wasn't actually using
the published version of pg_bsd_indent, but a hacked-up version that
tried to minimize the amount of movement of comments to the right of
code. The situation of interest is where such a comment has to be
moved to the right of its default placement at column 33 because there's
code there. BSD indent has always moved right in units of tab stops
in such cases --- but in the previous incarnation, indent was working
in 8-space tab stops, while now it knows we use 4-space tabs. So the
net result is that in about half the cases, such comments are placed
one tab stop left of before. This is better all around: it leaves
more room on the line for comment text, and it means that in such
cases the comment uniformly starts at the next 4-space tab stop after
the code, rather than sometimes one and sometimes two tabs after.
Also, ensure that comments following #endif are indented the same
as comments following other preprocessor commands such as #else.
That inconsistency turns out to have been self-inflicted damage
from a poorly-thought-through post-indent "fixup" in pgindent.
This patch is much less interesting than the first round of indent
changes, but also bulkier, so I thought it best to separate the effects.
Discussion: https://postgr.es/m/E1dAmxK-0006EE-1r@gemulon.postgresql.org
Discussion: https://postgr.es/m/30527.1495162840@sss.pgh.pa.us
The new indent version includes numerous fixes thanks to Piotr Stefaniak.
The main changes visible in this commit are:
* Nicer formatting of function-pointer declarations.
* No longer unexpectedly removes spaces in expressions using casts,
sizeof, or offsetof.
* No longer wants to add a space in "struct structname *varname", as
well as some similar cases for const- or volatile-qualified pointers.
* Declarations using PG_USED_FOR_ASSERTS_ONLY are formatted more nicely.
* Fixes bug where comments following declarations were sometimes placed
with no space separating them from the code.
* Fixes some odd decisions for comments following case labels.
* Fixes some cases where comments following code were indented to less
than the expected column 33.
On the less good side, it now tends to put more whitespace around typedef
names that are not listed in typedefs.list. This might encourage us to
put more effort into typedef name collection; it's not really a bug in
indent itself.
There are more changes coming after this round, having to do with comment
indentation and alignment of lines appearing within parentheses. I wanted
to limit the size of the diffs to something that could be reviewed without
one's eyes completely glazing over, so it seemed better to split up the
changes as much as practical.
Discussion: https://postgr.es/m/E1dAmxK-0006EE-1r@gemulon.postgresql.org
Discussion: https://postgr.es/m/30527.1495162840@sss.pgh.pa.us
This reverts commits fa2fa99552 and 42f50cb8fa.
While the functionality that was intended to be provided by these
commits is desired, the patch didn't actually solve as many of the
problematic situations as we hoped, and it created a bunch of its own
problems. Since we're going to require more extensive changes soon for
other reasons and users have been working around these problems for a
long time already, there is no point in spending effort in fixing this
halfway measure.
Per complaint from Tom Lane.
Discussion: https://postgr.es/m/21407.1484606922@sss.pgh.pa.us
(Commit fa2fa99552 had already been reverted in branches 9.5 as
f858524ee4 and 9.6 as e9e44a0953, so this touches master only.
Commit 42f50cb8fa was not present in the older branches.)
This extends the Aggregate node with two new features: HashAggregate
can now run multiple hashtables concurrently, and a new strategy
MixedAggregate populates hashtables while doing sorted grouping.
The planner will now attempt to save as many sorts as possible when
planning grouping sets queries, while not exceeding work_mem for the
estimated combined sizes of all hashtables used. No SQL-level changes
are required. There should be no user-visible impact other than the
new EXPLAIN output and possible changes to result ordering when ORDER
BY was not used (which affected a few regression tests). The
enable_hashagg option is respected.
Author: Andrew Gierth
Reviewers: Mark Dilger, Andres Freund
Discussion: https://postgr.es/m/87vatszyhj.fsf@news-spur.riddles.org.uk
Increase the size when either the distance between actual and optimal
slot grows too large, or when too many subsequent entries would have
to be moved.
This addresses reports that the simplehash performed, sometimes
considerably, worse than dynahash.
The reason turned out to be that insertions into the hashtable where,
due to the use of parallel query, in effect done from another
hashtable, in hash-value order. If the target hashtable, due to
mis-estimation, was sized a lot smaller than the source table(s) that
lead to very imbalanced tables; a lot of entries in many close-by
buckets from the source tables were inserted into a single, wider,
bucket on the target table. As the growth factor was solely computed
based on the fillfactor, the performance of the table decreased
further and further.
b81b5a96f4 was an attempt to address this problem for hash
aggregates (but not for bitmap scans), but it turns out that the
current method of mixing hash values often actually leaves neighboring
hash-values close to each other, just in different value range. It
might be worth revisiting that independently of the performance issues
addressed in this patch..
To address that problem resize tables in two additional cases: Firstly
when the optimal position for an entry would be far from the actual
position, secondly when many entries would have to be moved to make
space for the new entry (while satisfying the robin hood property).
Due to the additional resizing threshold it seems possible, and
testing confirms that so far, that a higher fillfactor doesn't hurt
performance and saves a bit of memory. It seems better to increase it
now, before a release containing any of this code, rather than wonder
in some later release.
The various boundaries aren't determined in a particularly scientific
manner, they might need some fine-tuning.
In all my tests the new code now, even with parallelism, performs at
least as good as the old code, in several scenarios significantly
better.
Reported-By: Dilip Kumar, Robert Haas, Kuntal Ghosh
Discussion:
https://postgr.es/m/CAFiTN-vagvuAydKG9VnWcoK=ADAhxmOa4ZTrmNsViBBooTnriQ@mail.gmail.comhttps://postgr.es/m/CAGz5QC+=fNTYgzMLTBUNeKt6uaWZFXJbkB5+7oWm-n9DwVxcLA@mail.gmail.com
Even if we don't emit definitions for SH_ALLOCATE and SH_FREE, we
still need prototypes. The user can't define them before including
simplehash.h because SH_TYPE isn't available yet.
For the allocator to be able to access private_data, it needs to
become an argument to SH_CREATE. Previously we relied on callers
to set that after returning from SH_CREATE, but SH_CREATE calls
SH_ALLOCATE before returning.
Dilip Kumar, reviewed by me.
This is infrastructure for a pending patch to allow parallel bitmap
heap scans.
Dilip Kumar, reviewed (in earlier versions) by Andres Freund and
(more recently) by me. Some further renaming by me, also.
Our documentation states that our maximum field size is 1 GB, and that
our maximum row size of 1.6 TB. However, while this might be attainable
in theory with enough contortions, it is not workable in practice; for
starters, pg_dump fails to dump tables containing rows larger than 1 GB,
even if individual columns are well below the limit; and even if one
does manage to manufacture a dump file containing a row that large, the
server refuses to load it anyway.
This commit enables dumping and reloading of such tuples, provided two
conditions are met:
1. no single column is larger than 1 GB (in output size -- for bytea
this includes the formatting overhead)
2. the whole row is not larger than 2 GB
There are three related changes to enable this:
a. StringInfo's API now has two additional functions that allow creating
a string that grows beyond the typical 1GB limit (and "long" string).
ABI compatibility is maintained. We still limit these strings to 2 GB,
though, for reasons explained below.
b. COPY now uses long StringInfos, so that pg_dump doesn't choke
trying to emit rows longer than 1GB.
c. heap_form_tuple now uses the MCXT_ALLOW_HUGE flag in its allocation
for the input tuple, which means that large tuples are accepted on
input. Note that at this point we do not apply any further limit to the
input tuple size.
The main reason to limit to 2 GB is that the FE/BE protocol uses 32 bit
length words to describe each row; and because the documentation is
ambiguous on its signedness and libpq does consider it signed, we cannot
use the highest-order bit. Additionally, the StringInfo API uses "int"
(which is 4 bytes wide in most platforms) in many places, so we'd need
to change that API too in order to improve, which has lots of fallout.
Backpatch to 9.5, which is the oldest that has
MemoryContextAllocExtended, a necessary piece of infrastructure. We
could apply to 9.4 with very minimal additional effort, but any further
than that would require backpatching "huge" allocations too.
This is the largest set of changes we could find that can be
back-patched without breaking compatibility with existing systems.
Fixing a bigger set of problems (for example, dumping tuples bigger than
2GB, or dumping fields bigger than 1GB) would require changing the FE/BE
protocol and/or changing the StringInfo API in an ABI-incompatible way,
neither of which would be back-patchable.
Authors: Daniel Vérité, Álvaro Herrera
Reviewed by: Tomas Vondra
Discussion: https://postgr.es/m/20160229183023.GA286012@alvherre.pgsql
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>
While we don't need multiple iterators at the moment, the interface is
nicer and less dangerous this way.
Aleksander Alekseev, with some changes by me.
Since the distances used in this algorithm are small integers (not more
than the size of the U set, in fact), there is no good reason to use float
arithmetic for them. Use short ints instead: they're smaller, faster, and
require no special portability assumptions.
Per testing by Greg Stark, which disclosed that the code got into an
infinite loop on VAX for lack of IEEE-style float infinities. We don't
really care all that much whether Postgres can run on a VAX anymore,
but there seems sufficient reason to change this code anyway.
In passing, make a few other small adjustments to make the code match
usual Postgres coding style a bit better.
So far we have worked around the fact that some very old compilers do
not support 'inline' functions by only using inline functions
conditionally (or not at all). Since such compilers are very rare by
now, we have decided to rely on inline functions from 9.6 onwards.
To avoid breaking these old compilers inline is defined away when not
supported. That'll cause "function x defined but not used" type of
warnings, but since nobody develops on such compilers anymore that's
ok.
This change in policy will allow us to more easily employ inline
functions.
I chose to remove code previously conditional on PG_USE_INLINE as it
seemed confusing to have code dependent on a define that's always
defined.
Blacklisting of compilers, like in c53f73879f, now has to be done
differently. A platform template can define PG_FORCE_DISABLE_INLINE to
force inline to be defined empty.
Discussion: 20150701161447.GB30708@awork2.anarazel.de
This SQL standard functionality allows to aggregate data by different
GROUP BY clauses at once. Each grouping set returns rows with columns
grouped by in other sets set to NULL.
This could previously be achieved by doing each grouping as a separate
query, conjoined by UNION ALLs. Besides being considerably more concise,
grouping sets will in many cases be faster, requiring only one scan over
the underlying data.
The current implementation of grouping sets only supports using sorting
for input. Individual sets that share a sort order are computed in one
pass. If there are sets that don't share a sort order, additional sort &
aggregation steps are performed. These additional passes are sourced by
the previous sort step; thus avoiding repeated scans of the source data.
The code is structured in a way that adding support for purely using
hash aggregation or a mix of hashing and sorting is possible. Sorting
was chosen to be supported first, as it is the most generic method of
implementation.
Instead of, as in an earlier versions of the patch, representing the
chain of sort and aggregation steps as full blown planner and executor
nodes, all but the first sort are performed inside the aggregation node
itself. This avoids the need to do some unusual gymnastics to handle
having to return aggregated and non-aggregated tuples from underlying
nodes, as well as having to shut down underlying nodes early to limit
memory usage. The optimizer still builds Sort/Agg node to describe each
phase, but they're not part of the plan tree, but instead additional
data for the aggregation node. They're a convenient and preexisting way
to describe aggregation and sorting. The first (and possibly only) sort
step is still performed as a separate execution step. That retains
similarity with existing group by plans, makes rescans fairly simple,
avoids very deep plans (leading to slow explains) and easily allows to
avoid the sorting step if the underlying data is sorted by other means.
A somewhat ugly side of this patch is having to deal with a grammar
ambiguity between the new CUBE keyword and the cube extension/functions
named cube (and rollup). To avoid breaking existing deployments of the
cube extension it has not been renamed, neither has cube been made a
reserved keyword. Instead precedence hacking is used to make GROUP BY
cube(..) refer to the CUBE grouping sets feature, and not the function
cube(). To actually group by a function cube(), unlikely as that might
be, the function name has to be quoted.
Needs a catversion bump because stored rules may change.
Author: Andrew Gierth and Atri Sharma, with contributions from Andres Freund
Reviewed-By: Andres Freund, Noah Misch, Tom Lane, Svenne Krap, Tomas
Vondra, Erik Rijkers, Marti Raudsepp, Pavel Stehule
Discussion: CAOeZVidmVRe2jU6aMk_5qkxnB7dfmPROzM7Ur8JPW5j8Y5X-Lw@mail.gmail.com
This improves on commit bbfd7edae5 by
making two simple changes:
* pg_attribute_noreturn now takes parentheses, ie pg_attribute_noreturn().
Likewise pg_attribute_unused(), pg_attribute_packed(). This reduces
pgindent's tendency to misformat declarations involving them.
* attributes are now always attached to function declarations, not
definitions. Previously some places were taking creative shortcuts,
which were not merely candidates for bad misformatting by pgindent
but often were outright wrong anyway. (It does little good to put a
noreturn annotation where callers can't see it.) In any case, if
we would like to believe that these macros can be used with non-gcc
compilers, we should avoid gratuitous variance in usage patterns.
I also went through and manually improved the formatting of a lot of
declarations, and got rid of excessively repetitive (and now obsolete
anyway) comments informing the reader what pg_attribute_printf is for.
Until now __attribute__() was defined to be empty for all compilers but
gcc. That's problematic because it prevents using it in other compilers;
which is necessary e.g. for atomics portability. It's also just
generally dubious to do so in a header as widely included as c.h.
Instead add pg_attribute_format_arg, pg_attribute_printf,
pg_attribute_noreturn macros which are implemented in the compilers that
understand them. Also add pg_attribute_noreturn and pg_attribute_packed,
but don't provide fallbacks, since they can affect functionality.
This means that external code that, possibly unwittingly, relied on
__attribute__ defined to be empty on !gcc compilers may now run into
warnings or errors on those compilers. But there shouldn't be many
occurances of that and it's hard to work around...
Discussion: 54B58BA3.8040302@ohmu.fi
Author: Oskari Saarenmaa, with some minor changes by me.
After removal, the next_sibling pointer of a node was sometimes incorrectly
left to point to another node in the heap, which meant that a node was
sometimes linked twice into the heap. Surprisingly that didn't cause any
crashes in my testing, but it was clearly wrong and could easily segfault
in other scenarios.
Also always keep the prev_or_parent pointer as NULL on the root node. That
was not a correctness issue AFAICS, but let's be tidy.
Add a debugging function, to dump the contents of a pairing heap as a
string. It's #ifdef'd out, as it's not used for anything in any normal
code, but it was highly useful in debugging this. Let's keep it handy for
further reference.
This commit extends the SortSupport infrastructure to allow operator
classes the option to provide abbreviated representations of Datums;
in the case of text, we abbreviate by taking the first few characters
of the strxfrm() blob. If the abbreviated comparison is insufficent
to resolve the comparison, we fall back on the normal comparator.
This can be much faster than the old way of doing sorting if the
first few bytes of the string are usually sufficient to resolve the
comparison.
There is the potential for a performance regression if all of the
strings to be sorted are identical for the first 8+ characters and
differ only in later positions; therefore, the SortSupport machinery
now provides an infrastructure to abort the use of abbreviation if
it appears that abbreviation is producing comparatively few distinct
keys. HyperLogLog, a streaming cardinality estimator, is included in
this commit and used to make that determination for text.
Peter Geoghegan, reviewed by me.
Currently, a backend will reset it's PGXACT->xmin value when it doesn't
have any registered snapshots left. That covered the common case that a
transaction in read committed mode runs several queries, one after each
other, as there would be no snapshots active between those queries.
However, if you hold cursors across each of the query, we didn't get a
chance to reset xmin.
To make that better, keep all the registered snapshots in a pairing heap,
ordered by xmin so that it's always quick to find the snapshot with the
smallest xmin. That allows us to advance PGXACT->xmin whenever the oldest
snapshot is deregistered, even if there are others still active.
Per discussion originally started by Jeff Davis back in 2009 and more
recently by Robert Haas.
This performs slightly better, uses less memory, and needs slightly less
code in GiST, than the Red-Black tree previously used.
Reviewed by Peter Geoghegan
When we are using a C99-compliant vsnprintf implementation (which should be
most places, these days) it is worth the trouble to make use of its report
of how large the buffer needs to be to succeed. This patch adjusts
stringinfo.c and some miscellaneous usages in pg_dump to do that, relying
on the logic recently added in libpgcommon's psprintf.c. Since these
places want to know the number of bytes written once we succeed, modify the
API of pvsnprintf() to report that.
There remains near-duplicate logic in pqexpbuffer.c, but since that code
is in libpq, psprintf.c's approach of exit()-on-error isn't appropriate
for use there. Also note that I didn't bother touching the multitude
of places that call (v)snprintf without any attempt to provide a resizable
buffer.
Release-note-worthy incompatibility: the API of appendStringInfoVA()
changed. If there's any third-party code that's calling that directly,
it will need tweaking along the same lines as in this patch.
David Rowley and Tom Lane
Failing to do so can cause queries to return wrong data, error out or crash.
This requires adding a new binaryheap_reset() method to binaryheap.c,
but that probably should have been there anyway.
Per bug #8410 from Terje Elde. Diagnosis and patch by Andres Freund.
Previously one had to use slist_delete(), implying an additional scan of
the list, making this infrastructure considerably less efficient than
traditional Lists when deletion of element(s) in a long list is needed.
Modify the slist_foreach_modify() macro to support deleting the current
element in O(1) time, by keeping a "prev" pointer in addition to "cur"
and "next". Although this makes iteration with this macro a bit slower,
no real harm is done, since in any scenario where you're not going to
delete the current list element you might as well just use slist_foreach
instead. Improve the comments about when to use each macro.
Back-patch to 9.3 so that we'll have consistent semantics in all branches
that provide ilist.h. Note this is an ABI break for callers of
slist_foreach_modify().
Andres Freund and Tom Lane
There are probably other places where this can be used, but for now,
this just makes MergeAppend use it, so that this code will have test
coverage. There is other work in the queue that will use this, as
well.
Abhijit Menon-Sen, reviewed by Andres Freund, Robert Haas, Álvaro
Herrera, Tom Lane, and others.
dlist_delete, dlist_insert_after, dlist_insert_before, slist_insert_after
do not need access to the list header, and indeed insisting on that negates
one of the main advantages of a doubly-linked list.
In consequence, revert addition of "cache_bucket" field to CatCTup.
Make foreach macros less syntactically dangerous, and fix some typos in
evidently-never-tested ones. Add missing slist_next_node and
slist_head_node functions. Fix broken dlist_check code. Assorted comment
improvements.
Provide a common implementation of embedded singly-linked and
doubly-linked lists. "Embedded" in the sense that the nodes'
next/previous pointers exist within some larger struct; this design
choice reduces memory allocation overhead.
Most of the implementation uses inlineable functions (where supported),
for performance.
Some existing uses of both types of lists have been converted to the new
code, for demonstration purposes. Other uses can (and probably will) be
converted in the future. Since dllist.c is unused after this conversion,
it has been removed.
Author: Andres Freund
Some tweaks by me
Reviewed by Tom Lane, Peter Geoghegan
Add __attribute__ decorations for printf format checking to the places that
were missing them. Fix the resulting warnings. Add
-Wmissing-format-attribute to the standard set of warnings for GCC, so these
don't happen again.
The warning fixes here are relatively harmless. The one serious problem
discovered by this was already committed earlier in
cf15fb5cab.
