The following parameters have been imprecise, or incorrect, about their
description (PGC_POSTMASTER or PGC_SIGHUP):
- autovacuum_work_mem (docs, as of 9.6~)
- huge_page_size (docs, as of 14~)
- max_logical_replication_workers (docs, as of 10~)
- max_sync_workers_per_subscription (docs, as of 10~)
- min_dynamic_shared_memory (docs, as of 14~)
- recovery_init_sync_method (postgresql.conf.sample, as of 14~)
- remove_temp_files_after_crash (docs, as of 14~)
- restart_after_crash (docs, as of 9.6~)
- ssl_min_protocol_version (docs, as of 12~)
- ssl_max_protocol_version (docs, as of 12~)
This commit adjusts the description of all these parameters to be more
consistent with the practice used for the others.
Revewed-by: Justin Pryzby
Discussion: https://postgr.es/m/YK2ltuLpe+FbRXzA@paquier.xyz
Backpatch-through: 9.6
Allowing only on/off meant that all either all existing configuration
guides would become obsolete if we disabled it by default, or that we
would have to accept a performance loss in the default config if we
enabled it by default. By allowing 'auto' as a middle ground, the
performance cost is only paid by those who enable pg_stat_statements and
similar modules.
I only edited the release notes to comment-out a paragraph that is now
factually wrong; further edits are probably needed to describe the
related change in more detail.
Author: Julien Rouhaud <rjuju123@gmail.com>
Reviewed-by: Justin Pryzby <pryzby@telsasoft.com>
Discussion: https://postgr.es/m/20210513002623.eugftm4nk2lvvks3@nol
This set of commits has some bugs with known fixes, but at this late
stage in the release cycle it seems best to revert and resubmit next
time, along with some new automated test coverage for this whole area.
Commits reverted:
dc88460c: Doc: Review for "Optionally prefetch referenced data in recovery."
1d257577: Optionally prefetch referenced data in recovery.
f003d9f8: Add circular WAL decoding buffer.
323cbe7c: Remove read_page callback from XLogReader.
Remove the new GUC group WAL_RECOVERY recently added by a55a9847, as the
corresponding section of config.sgml is now reverted.
Discussion: https://postgr.es/m/CAOuzzgrn7iKnFRsB4MHp3UisEQAGgZMbk_ViTN4HV4-Ksq8zCg%40mail.gmail.com
It seems that various people have moved GUCs around in the config.sgml
listing without bothering to make the code agree. Ensure that the
config_group codes assigned to GUCs match where they are listed in
config.sgml. Likewise ensure that postgresql.conf.sample lists GUCs
in the same sub-section and same ordering as they appear in config.sgml.
(I've got some doubts about some of these choices, but for the purposes
of this patch, we'll treat config.sgml as gospel.)
Notably, this requires adding a WAL_RECOVERY config_group value,
because 1d257577e didn't. As long as we're renumbering that enum
anyway, let's take out the values corresponding to major groups
that are divided into sub-groups. No GUC should be assigned to the
major group itself, so those values just create a temptation to
do the wrong thing, while adding work for translators.
In passing, adjust the short_desc strings for PRESET_OPTIONS GUCs
to uniformly use the phrasing "Shows XYZ.", removing the impression
some of these strings left that you can set the value.
While some of these errors are old, no back-patch, as changing the
contents of the pg_settings view in stable branches seems more likely
to be seen as a compatibility break than anything helpful.
Bharath Rupireddy, Justin Pryzby, Tom Lane
Discussion: https://postgr.es/m/16997-ff16127f6e0d1390@postgresql.org
Discussion: https://postgr.es/m/20210413123139.GE6091@telsasoft.com
This GUC has always been classified as a planner option since its
introduction in 7c944bd, and was listed in postgresql.conf.sample. As
this parameter exists for testing purposes, move it to the section
dedicated to developer parameters and hence remove it from
postgresql.conf.sample. This will avoid any temptation to play with it
on production servers for users that should never really have to touch
this parameter.
The general description used for developer options is reworded a bit, to
take into account the inclusion of force_parallel_mode, per a suggestion
from Tom Lane.
Per discussion between Tom Lane, Bruce Momjian, Justin Pryzby, Bharath
Rupireddy and me.
Author: Justin Pryzby, Tom Lane
Discussion: https://postgr.es/m/20210403152402.GA8049@momjian.us
This GUC has already been classified as LOGGING_WHAT, but its location
in postgresql.conf.sample and the documentation did not reflect that, so
fix those inconsistencies.
Author: Justin Pryzby
Discussion: https://postgr.es/m/20210404012546.GK6592@telsasoft.com
Introduce a new GUC recovery_prefetch, disabled by default. When
enabled, look ahead in the WAL and try to initiate asynchronous reading
of referenced data blocks that are not yet cached in our buffer pool.
For now, this is done with posix_fadvise(), which has several caveats.
Better mechanisms will follow in later work on the I/O subsystem.
The GUC maintenance_io_concurrency is used to limit the number of
concurrent I/Os we allow ourselves to initiate, based on pessimistic
heuristics used to infer that I/Os have begun and completed.
The GUC wal_decode_buffer_size is used to limit the maximum distance we
are prepared to read ahead in the WAL to find uncached blocks.
Reviewed-by: Alvaro Herrera <alvherre@2ndquadrant.com> (parts)
Reviewed-by: Andres Freund <andres@anarazel.de> (parts)
Reviewed-by: Tomas Vondra <tomas.vondra@2ndquadrant.com> (parts)
Tested-by: Tomas Vondra <tomas.vondra@2ndquadrant.com>
Tested-by: Jakub Wartak <Jakub.Wartak@tomtom.com>
Tested-by: Dmitry Dolgov <9erthalion6@gmail.com>
Tested-by: Sait Talha Nisanci <Sait.Nisanci@microsoft.com>
Discussion: https://postgr.es/m/CA%2BhUKGJ4VJN8ttxScUFM8dOKX0BrBiboo5uz1cq%3DAovOddfHpA%40mail.gmail.com
Add a failsafe mechanism that is triggered by VACUUM when it notices
that the table's relfrozenxid and/or relminmxid are dangerously far in
the past. VACUUM checks the age of the table dynamically, at regular
intervals.
When the failsafe triggers, VACUUM takes extraordinary measures to
finish as quickly as possible so that relfrozenxid and/or relminmxid can
be advanced. VACUUM will stop applying any cost-based delay that may be
in effect. VACUUM will also bypass any further index vacuuming and heap
vacuuming -- it only completes whatever remaining pruning and freezing
is required. Bypassing index/heap vacuuming is enabled by commit
8523492d, which made it possible to dynamically trigger the mechanism
already used within VACUUM when it is run with INDEX_CLEANUP off.
It is expected that the failsafe will almost always trigger within an
autovacuum to prevent wraparound, long after the autovacuum began.
However, the failsafe mechanism can trigger in any VACUUM operation.
Even in a non-aggressive VACUUM, where we're likely to not advance
relfrozenxid, it still seems like a good idea to finish off remaining
pruning and freezing. An aggressive/anti-wraparound VACUUM will be
launched immediately afterwards. Note that the anti-wraparound VACUUM
that follows will itself trigger the failsafe, usually before it even
begins its first (and only) pass over the heap.
The failsafe is controlled by two new GUCs: vacuum_failsafe_age, and
vacuum_multixact_failsafe_age. There are no equivalent reloptions,
since that isn't expected to be useful. The GUCs have rather high
defaults (both default to 1.6 billion), and are expected to generally
only be used to make the failsafe trigger sooner/more frequently.
Author: Masahiko Sawada <sawada.mshk@gmail.com>
Author: Peter Geoghegan <pg@bowt.ie>
Discussion: https://postgr.es/m/CAD21AoD0SkE11fMw4jD4RENAwBMcw1wasVnwpJVw3tVqPOQgAw@mail.gmail.com
Discussion: https://postgr.es/m/CAH2-WzmgH3ySGYeC-m-eOBsa2=sDwa292-CFghV4rESYo39FsQ@mail.gmail.com
Use the in-core query id computation for pg_stat_activity,
log_line_prefix, and EXPLAIN VERBOSE.
Similar to other fields in pg_stat_activity, only the queryid from the
top level statements are exposed, and if the backends status isn't
active then the queryid from the last executed statements is displayed.
Add a %Q placeholder to include the queryid in log_line_prefix, which
will also only expose top level statements.
For EXPLAIN VERBOSE, if a query identifier has been computed, either by
enabling compute_query_id or using a third-party module, display it.
Bump catalog version.
Discussion: https://postgr.es/m/20210407125726.tkvjdbw76hxnpwfi@nol
Author: Julien Rouhaud
Reviewed-by: Alvaro Herrera, Nitin Jadhav, Zhihong Yu
Add compute_query_id GUC to control whether a query identifier should be
computed by the core (off by default). It's thefore now possible to
disable core queryid computation and use pg_stat_statements with a
different algorithm to compute the query identifier by using a
third-party module.
To ensure that a single source of query identifier can be used and is
well defined, modules that calculate a query identifier should throw an
error if compute_query_id specified to compute a query id and if a query
idenfitier was already calculated.
Discussion: https://postgr.es/m/20210407125726.tkvjdbw76hxnpwfi@nol
Author: Julien Rouhaud
Reviewed-by: Alvaro Herrera, Nitin Jadhav, Zhihong Yu
Provide a new GUC check_client_connection_interval that can be used to
check whether the client connection has gone away, while running very
long queries. It is disabled by default.
For now this uses a non-standard Linux extension (also adopted by at
least one other OS). POLLRDHUP is not defined by POSIX, and other OSes
don't have a reliable way to know if a connection was closed without
actually trying to read or write.
In future we might consider trying to send a no-op/heartbeat message
instead, but that could require protocol changes.
Author: Sergey Cherkashin <s.cherkashin@postgrespro.ru>
Author: Thomas Munro <thomas.munro@gmail.com>
Reviewed-by: Thomas Munro <thomas.munro@gmail.com>
Reviewed-by: Tatsuo Ishii <ishii@sraoss.co.jp>
Reviewed-by: Konstantin Knizhnik <k.knizhnik@postgrespro.ru>
Reviewed-by: Zhihong Yu <zyu@yugabyte.com>
Reviewed-by: Andres Freund <andres@anarazel.de>
Reviewed-by: Maksim Milyutin <milyutinma@gmail.com>
Reviewed-by: Tsunakawa, Takayuki/綱川 貴之 <tsunakawa.takay@fujitsu.com>
Reviewed-by: Tom Lane <tgl@sss.pgh.pa.us> (much earlier version)
Discussion: https://postgr.es/m/77def86b27e41f0efcba411460e929ae%40postgrespro.ru
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
This implements asynchronous execution, which runs multiple parts of a
non-parallel-aware Append concurrently rather than serially to improve
performance when possible. Currently, the only node type that can be
run concurrently is a ForeignScan that is an immediate child of such an
Append. In the case where such ForeignScans access data on different
remote servers, this would run those ForeignScans concurrently, and
overlap the remote operations to be performed simultaneously, so it'll
improve the performance especially when the operations involve
time-consuming ones such as remote join and remote aggregation.
We may extend this to other node types such as joins or aggregates over
ForeignScans in the future.
This also adds the support for postgres_fdw, which is enabled by the
table-level/server-level option "async_capable". The default is false.
Robert Haas, Kyotaro Horiguchi, Thomas Munro, and myself. This commit
is mostly based on the patch proposed by Robert Haas, but also uses
stuff from the patch proposed by Kyotaro Horiguchi and from the patch
proposed by Thomas Munro. Reviewed by Kyotaro Horiguchi, Konstantin
Knizhnik, Andrey Lepikhov, Movead Li, Thomas Munro, Justin Pryzby, and
others.
Discussion: https://postgr.es/m/CA%2BTgmoaXQEt4tZ03FtQhnzeDEMzBck%2BLrni0UWHVVgOTnA6C1w%40mail.gmail.com
Discussion: https://postgr.es/m/CA%2BhUKGLBRyu0rHrDCMC4%3DRn3252gogyp1SjOgG8SEKKZv%3DFwfQ%40mail.gmail.com
Discussion: https://postgr.es/m/20200228.170650.667613673625155850.horikyota.ntt%40gmail.com
Common recommendations are that the checkpoint should be spread out as
much as possible, provided we avoid having it take too long. This
change updates the default to 0.9 (from 0.5) to match that
recommendation.
There was some debate about possibly removing the option entirely but it
seems there may be some corner-cases where having it set much lower to
try to force the checkpoint to be as fast as possible could result in
fewer periods of time of reduced performance due to kernel flushing.
General agreement is that the "spread more" is the preferred approach
though and those who need to tune away from that value are much less
common.
Reviewed-By: Michael Paquier, Peter Eisentraut, Tom Lane, David Steele,
Nathan Bossart
Discussion: https://postgr.es/m/20201207175329.GM16415%40tamriel.snowman.net
To allow inserts in parallel-mode this feature has to ensure that all the
constraints, triggers, etc. are parallel-safe for the partition hierarchy
which is costly and we need to find a better way to do that. Additionally,
we could have used existing cached information in some cases like indexes,
domains, etc. to determine the parallel-safety.
List of commits reverted, in reverse chronological order:
ed62d3737c Doc: Update description for parallel insert reloption.
c8f78b6161 Add a new GUC and a reloption to enable inserts in parallel-mode.
c5be48f092 Improve FK trigger parallel-safety check added by 05c8482f7f.
e2cda3c20a Fix use of relcache TriggerDesc field introduced by commit 05c8482f7f.
e4e87a32cc Fix valgrind issue in commit 05c8482f7f.
05c8482f7f Enable parallel SELECT for "INSERT INTO ... SELECT ...".
Discussion: https://postgr.es/m/E1lMiB9-0001c3-SY@gemulon.postgresql.org
Since commit 2ce439f3 we have opened every file in the data directory
and called fsync() at the start of crash recovery. This can be very
slow if there are many files, leading to field complaints of systems
taking minutes or even hours to begin crash recovery.
Provide an alternative method, for Linux only, where we call syncfs() on
every possibly different filesystem under the data directory. This is
equivalent, but avoids faulting in potentially many inodes from
potentially slow storage.
The new mode comes with some caveats, described in the documentation, so
the default value for the new setting is "fsync", preserving the older
behavior.
Reported-by: Michael Brown <michael.brown@discourse.org>
Reviewed-by: Fujii Masao <masao.fujii@oss.nttdata.com>
Reviewed-by: Paul Guo <guopa@vmware.com>
Reviewed-by: Bruce Momjian <bruce@momjian.us>
Reviewed-by: Justin Pryzby <pryzby@telsasoft.com>
Reviewed-by: David Steele <david@pgmasters.net>
Discussion: https://postgr.es/m/11bc2bb7-ecb5-3ad0-b39f-df632734cd81%40discourse.org
Discussion: https://postgr.es/m/CAEET0ZHGnbXmi8yF3ywsDZvb3m9CbdsGZgfTXscQ6agcbzcZAw%40mail.gmail.com
There is now a per-column COMPRESSION option which can be set to pglz
(the default, and the only option in up until now) or lz4. Or, if you
like, you can set the new default_toast_compression GUC to lz4, and
then that will be the default for new table columns for which no value
is specified. We don't have lz4 support in the PostgreSQL code, so
to use lz4 compression, PostgreSQL must be built --with-lz4.
In general, TOAST compression means compression of individual column
values, not the whole tuple, and those values can either be compressed
inline within the tuple or compressed and then stored externally in
the TOAST table, so those properties also apply to this feature.
Prior to this commit, a TOAST pointer has two unused bits as part of
the va_extsize field, and a compessed datum has two unused bits as
part of the va_rawsize field. These bits are unused because the length
of a varlena is limited to 1GB; we now use them to indicate the
compression type that was used. This means we only have bit space for
2 more built-in compresison types, but we could work around that
problem, if necessary, by introducing a new vartag_external value for
any further types we end up wanting to add. Hopefully, it won't be
too important to offer a wide selection of algorithms here, since
each one we add not only takes more coding but also adds a build
dependency for every packager. Nevertheless, it seems worth doing
at least this much, because LZ4 gets better compression than PGLZ
with less CPU usage.
It's possible for LZ4-compressed datums to leak into composite type
values stored on disk, just as it is for PGLZ. It's also possible for
LZ4-compressed attributes to be copied into a different table via SQL
commands such as CREATE TABLE AS or INSERT .. SELECT. It would be
expensive to force such values to be decompressed, so PostgreSQL has
never done so. For the same reasons, we also don't force recompression
of already-compressed values even if the target table prefers a
different compression method than was used for the source data. These
architectural decisions are perhaps arguable but revisiting them is
well beyond the scope of what seemed possible to do as part of this
project. However, it's relatively cheap to recompress as part of
VACUUM FULL or CLUSTER, so this commit adjusts those commands to do
so, if the configured compression method of the table happens not to
match what was used for some column value stored therein.
Dilip Kumar. The original patches on which this work was based were
written by Ildus Kurbangaliev, and those were patches were based on
even earlier work by Nikita Glukhov, but the design has since changed
very substantially, since allow a potentially large number of
compression methods that could be added and dropped on a running
system proved too problematic given some of the architectural issues
mentioned above; the choice of which specific compression method to
add first is now different; and a lot of the code has been heavily
refactored. More recently, Justin Przyby helped quite a bit with
testing and reviewing and this version also includes some code
contributions from him. Other design input and review from Tomas
Vondra, Álvaro Herrera, Andres Freund, Oleg Bartunov, Alexander
Korotkov, and me.
Discussion: http://postgr.es/m/20170907194236.4cefce96%40wp.localdomain
Discussion: http://postgr.es/m/CAFiTN-uUpX3ck%3DK0mLEk-G_kUQY%3DSNOTeqdaNRR9FMdQrHKebw%40mail.gmail.com
After a crash of a backend using temporary files, the files used to be
left behind, on the basis that it might be useful for debugging. But we
don't have any reports of anyone actually doing that, and it means the
disk usage may grow over time due to repeated backend failures (possibly
even hitting ENOSPC). So this behavior is a bit unfortunate, and fixing
it required either manual cleanup (deleting files, which is error-prone)
or restart of the instance (i.e. service disruption).
This implements automatic cleanup of temporary files, controled by a new
GUC remove_temp_files_after_crash. By default the files are removed, but
it can be disabled to restore the old behavior if needed.
Author: Euler Taveira
Reviewed-by: Tomas Vondra, Michael Paquier, Anastasia Lubennikova, Thomas Munro
Discussion: https://postgr.es/m/CAH503wDKdYzyq7U-QJqGn%3DGm6XmoK%2B6_6xTJ-Yn5WSvoHLY1Ww%40mail.gmail.com
Commit 05c8482f7f added the implementation of parallel SELECT for
"INSERT INTO ... SELECT ..." which may incur non-negligible overhead in
the additional parallel-safety checks that it performs, even when, in the
end, those checks determine that parallelism can't be used. This is
normally only ever a problem in the case of when the target table has a
large number of partitions.
A new GUC option "enable_parallel_insert" is added, to allow insert in
parallel-mode. The default is on.
In addition to the GUC option, the user may want a mechanism to allow
inserts in parallel-mode with finer granularity at table level. The new
table option "parallel_insert_enabled" allows this. The default is true.
Author: "Hou, Zhijie"
Reviewed-by: Greg Nancarrow, Amit Langote, Takayuki Tsunakawa, Amit Kapila
Discussion: https://postgr.es/m/CAA4eK1K-cW7svLC2D7DHoGHxdAdg3P37BLgebqBOC2ZLc9a6QQ%40mail.gmail.com
Discussion: https://postgr.es/m/CAJcOf-cXnB5cnMKqWEp2E2z7Mvcd04iLVmV=qpFJrR3AcrTS3g@mail.gmail.com
Remove the entire idea of "stale stats" within nbtree VACUUM (stop
caring about stats involving the number of inserted tuples). Also
remove the vacuum_cleanup_index_scale_factor GUC/param on the master
branch (though just disable them on postgres 13).
The vacuum_cleanup_index_scale_factor/stats interface made the nbtree AM
partially responsible for deciding when pg_class.reltuples stats needed
to be updated. This seems contrary to the spirit of the index AM API,
though -- it is not actually necessary for an index AM's bulk delete and
cleanup callbacks to provide accurate stats when it happens to be
inconvenient. The core code owns that. (Index AMs have the authority
to perform or not perform certain kinds of deferred cleanup based on
their own considerations, such as page deletion and recycling, but that
has little to do with pg_class.reltuples/num_index_tuples.)
This issue was fairly harmless until the introduction of the
autovacuum_vacuum_insert_threshold feature by commit b07642db, which had
an undesirable interaction with the vacuum_cleanup_index_scale_factor
mechanism: it made insert-driven autovacuums perform full index scans,
even though there is no real benefit to doing so. This has been tied to
a regression with an append-only insert benchmark [1].
Also have remaining cases that perform a full scan of an index during a
cleanup-only nbtree VACUUM indicate that the final tuple count is only
an estimate. This prevents vacuumlazy.c from setting the index's
pg_class.reltuples in those cases (it will now only update pg_class when
vacuumlazy.c had TIDs for nbtree to bulk delete). This arguably fixes
an oversight in deduplication-related bugfix commit 48e12913.
[1] https://smalldatum.blogspot.com/2021/01/insert-benchmark-postgres-is-still.html
Author: Peter Geoghegan <pg@bowt.ie>
Reviewed-By: Masahiko Sawada <sawada.mshk@gmail.com>
Discussion: https://postgr.es/m/CAD21AoA4WHthN5uU6+WScZ7+J_RcEjmcuH94qcoUPuB42ShXzg@mail.gmail.com
Backpatch: 13-, where autovacuum_vacuum_insert_threshold was added.
This commit adds new GUC track_wal_io_timing. When this is enabled,
the total amounts of time XLogWrite writes and issue_xlog_fsync syncs
WAL data to disk are counted in pg_stat_wal. This information would be
useful to check how much WAL write and sync affect the performance.
Enabling track_wal_io_timing will make the server query the operating
system for the current time every time WAL is written or synced,
which may cause significant overhead on some platforms. To avoid such
additional overhead in the server with track_io_timing enabled,
this commit introduces track_wal_io_timing as a separate parameter from
track_io_timing.
Note that WAL write and sync activity by walreceiver has not been tracked yet.
This commit makes the server also track the numbers of times XLogWrite
writes and issue_xlog_fsync syncs WAL data to disk, in pg_stat_wal,
regardless of the setting of track_wal_io_timing. This counters can be
used to calculate the WAL write and sync time per request, for example.
Bump PGSTAT_FILE_FORMAT_ID.
Bump catalog version.
Author: Masahiro Ikeda
Reviewed-By: Japin Li, Hayato Kuroda, Masahiko Sawada, David Johnston, Fujii Masao
Discussion: https://postgr.es/m/0509ad67b585a5b86a83d445dfa75392@oss.nttdata.com
Add another method to specify CRLs, hashed directory method, for both
server and client side. This offers a means for server or libpq to
load only CRLs that are required to verify a certificate. The CRL
directory is specifed by separate GUC variables or connection options
ssl_crl_dir and sslcrldir, alongside the existing ssl_crl_file and
sslcrl, so both methods can be used at the same time.
Author: Kyotaro Horiguchi <horikyota.ntt@gmail.com>
Discussion: https://www.postgresql.org/message-id/flat/20200731.173911.904649928639357911.horikyota.ntt@gmail.com
FreeBSD 13 gained O_DSYNC, which would normally cause wal_sync_method to
choose open_datasync as its default value. That may not be a good
choice for all systems, and performs worse than fdatasync in some
scenarios. Let's preserve the existing default behavior for now.
Like commit 576477e73c4, which did the same for Linux, back-patch to all
supported releases.
Discussion: https://postgr.es/m/CA%2BhUKGLsAMXBQrCxCXoW-JsUYmdOL8ALYvaX%3DCrHqWxm-nWbGA%40mail.gmail.com
When commit f425b605 introduced cost based vacuum delays back in 2004,
the defaults reflected then-current trends in hardware, as well as
certain historical limitations in PostgreSQL. There have been enormous
improvements in both areas since that time. The cost limit GUC defaults
finally became much more representative of current trends following
commit cbccac37, which decreased autovacuum_vacuum_cost_delay's default
by 10x for PostgreSQL 12 (it went from 20ms to only 2ms).
The relative costs have shifted too. This should also be accounted for
by the defaults. More specifically, the relative importance of avoiding
dirtying pages within VACUUM has greatly increased, primarily due to
main memory capacity scaling and trends in flash storage. Within
Postgres itself, improvements like sequential access during index
vacuuming (at least in nbtree and GiST indexes) have also been
contributing factors.
To reflect all this, decrease the default of vacuum_cost_page_miss to 2.
Since the default of vacuum_cost_page_dirty remains 20, dirtying a page
is now considered 10x "costlier" than a page miss by default.
Author: Peter Geoghegan <pg@bowt.ie>
Discussion: https://postgr.es/m/CAH2-WzmLPFnkWT8xMjmcsm7YS3+_Qi3iRWAb2+_Bc8UhVyHfuA@mail.gmail.com
This commit adds GUC log_recovery_conflict_waits that controls whether
a log message is produced when the startup process is waiting longer than
deadlock_timeout for recovery conflicts. This is useful in determining
if recovery conflicts prevent the recovery from applying WAL.
Note that currently a log message is produced only when recovery conflict
has not been resolved yet even after deadlock_timeout passes, i.e.,
only when the startup process is still waiting for recovery conflict
even after deadlock_timeout.
Author: Bertrand Drouvot, Masahiko Sawada
Reviewed-by: Alvaro Herrera, Kyotaro Horiguchi, Fujii Masao
Discussion: https://postgr.es/m/9a60178c-a853-1440-2cdc-c3af916cff59@amazon.com
This GUC variable works much like idle_in_transaction_session_timeout,
in that it kills sessions that have waited too long for a new client
query. But it applies when we're not in a transaction, rather than
when we are.
Li Japin, reviewed by David Johnston and Hayato Kuroda, some
fixes by me
Discussion: https://postgr.es/m/763A0689-F189-459E-946F-F0EC4458980B@hotmail.com
secure_open_gssapi() installed the krb_server_keyfile setting as
KRB5_KTNAME unconditionally, so long as it's not empty. However,
pg_GSS_recvauth() only installed it if KRB5_KTNAME wasn't set already,
leading to a troubling inconsistency: in theory, clients could see
different sets of server principal names depending on whether they
use GSSAPI encryption. Always using krb_server_keyfile seems like
the right thing, so make both places do that. Also fix up
secure_open_gssapi()'s lack of a check for setenv() failure ---
it's unlikely, surely, but security-critical actions are no place
to be sloppy.
Also improve the associated documentation.
This patch does nothing about secure_open_gssapi()'s use of setenv(),
and indeed causes pg_GSS_recvauth() to use it too. That's nominally
against project portability rules, but since this code is only built
with --with-gssapi, I do not feel a need to do something about this
in the back branches. A fix will be forthcoming for HEAD though.
Back-patch to v12 where GSSAPI encryption was introduced. The
dubious behavior in pg_GSS_recvauth() goes back further, but it
didn't have anything to be inconsistent with, so let it be.
Discussion: https://postgr.es/m/2187460.1609263156@sss.pgh.pa.us
The patch needs test cases, reorganization, and cfbot testing.
Technically reverts commits 5c31afc49d..e35b2bad1a (exclusive/inclusive)
and 08db7c63f3..ccbe34139b.
Reported-by: Tom Lane, Michael Paquier
Discussion: https://postgr.es/m/E1ktAAG-0002V2-VB@gemulon.postgresql.org
This adds a key management system that stores (currently) two data
encryption keys of length 128, 192, or 256 bits. The data keys are
AES256 encrypted using a key encryption key, and validated via GCM
cipher mode. A command to obtain the key encryption key must be
specified at initdb time, and will be run at every database server
start. New parameters allow a file descriptor open to the terminal to
be passed. pg_upgrade support has also been added.
Discussion: https://postgr.es/m/CA+fd4k7q5o6Nc_AaX6BcYM9yqTbC6_pnH-6nSD=54Zp6NBQTCQ@mail.gmail.com
Discussion: https://postgr.es/m/20201202213814.GG20285@momjian.us
Author: Masahiko Sawada, me, Stephen Frost
This GUC was always intended as a temporary solution to help with
finding 9.4-to-9.5 migration issues. Now that all pre-9.5 branches
are out of support, and 9.5 will be too before v14 is released,
it seems like it's okay to drop it. Doing so allows removal of
several hundred lines of poorly-tested code in parse_expr.c,
which have been a fertile source of bugs when people did use this.
Discussion: https://postgr.es/m/2234320.1607117945@sss.pgh.pa.us
This commit changes restore_command from PGC_POSTMASTER to PGC_SIGHUP.
As the side effect of this commit, restore_command can be reset to
empty during archive recovery. In this setting, archive recovery
tries to replay only WAL files available in pg_wal directory. This is
the same behavior as when the command that always fails is specified
in restore_command.
Note that restore_command still must be specified (not empty) when
starting archive recovery, even after applying this commit. This is
necessary as the safeguard to prevent users from forgetting to
specify restore_command and starting archive recovery.
Thanks to Peter Eisentraut, Michael Paquier, Andres Freund,
Robert Haas and Anastasia Lubennikova for discussion.
Author: Sergei Kornilov
Reviewed-by: Kyotaro Horiguchi, Fujii Masao
Discussion: https://postgr.es/m/2317771549527294@sas2-985f744271ca.qloud-c.yandex.net
This is useful for monitoring purposes with log parsing. Similarly to
pg_stat_activity, the leader's PID is shown only for active parallel
workers, minimizing the log footprint for the leaders as the equivalent
shared memory field is set as long as a backend is alive.
Author: Justin Pryzby
Reviewed-by: Álvaro Herrera, Michael Paquier, Julien Rouhaud, Tom Lane
Discussion: https://postgr.es/m/20200315111831.GA21492@telsasoft.com
Create an optional region in the main shared memory segment that can be
used to acquire and release "fast" DSM segments, and can benefit from
huge pages allocated at cluster startup time, if configured. Fall back
to the existing mechanisms when that space is full. The size is
controlled by a new GUC min_dynamic_shared_memory, defaulting to 0.
Main region DSM segments initially contain whatever garbage the memory
held last time they were used, rather than zeroes. That change revealed
that DSA areas failed to initialize themselves correctly in memory that
wasn't zeroed first, so fix that problem.
Discussion: https://postgr.es/m/CA%2BhUKGLAE2QBv-WgGp%2BD9P_J-%3Dyne3zof9nfMaqq1h3EGHFXYQ%40mail.gmail.com
Add a GUC that acts as a multiplier on work_mem. It gets applied when
sizing executor node hash tables that were previously size constrained
using work_mem alone.
The new GUC can be used to preferentially give hash-based nodes more
memory than the generic work_mem limit. It is intended to enable admin
tuning of the executor's memory usage. Overall system throughput and
system responsiveness can be improved by giving hash-based executor
nodes more memory (especially over sort-based alternatives, which are
often much less sensitive to being memory constrained).
The default value for hash_mem_multiplier is 1.0, which is also the
minimum valid value. This means that hash-based nodes continue to apply
work_mem in the traditional way by default.
hash_mem_multiplier is generally useful. However, it is being added now
due to concerns about hash aggregate performance stability for users
that upgrade to Postgres 13 (which added disk-based hash aggregation in
commit 1f39bce0). While the old hash aggregate behavior risked
out-of-memory errors, it is nevertheless likely that many users actually
benefited. Hash agg's previous indifference to work_mem during query
execution was not just faster; it also accidentally made aggregation
resilient to grouping estimate problems (at least in cases where this
didn't create destabilizing memory pressure).
hash_mem_multiplier can provide a certain kind of continuity with the
behavior of Postgres 12 hash aggregates in cases where the planner
incorrectly estimates that all groups (plus related allocations) will
fit in work_mem/hash_mem. This seems necessary because hash-based
aggregation is usually much slower when only a small fraction of all
groups can fit. Even when it isn't possible to totally avoid hash
aggregates that spill, giving hash aggregation more memory will reliably
improve performance (the same cannot be said for external sort
operations, which appear to be almost unaffected by memory availability
provided it's at least possible to get a single merge pass).
The PostgreSQL 13 release notes should advise users that increasing
hash_mem_multiplier can help with performance regressions associated
with hash aggregation. That can be taken care of by a later commit.
Author: Peter Geoghegan
Reviewed-By: Álvaro Herrera, Jeff Davis
Discussion: https://postgr.es/m/20200625203629.7m6yvut7eqblgmfo@alap3.anarazel.de
Discussion: https://postgr.es/m/CAH2-WzmD%2Bi1pG6rc1%2BCjc4V6EaFJ_qSuKCCHVnH%3DoruqD-zqow%40mail.gmail.com
Backpatch: 13-, where disk-based hash aggregation was introduced.
max_slot_wal_keep_size that was added in v13 and wal_keep_segments are
the GUC parameters to specify how much WAL files to retain for
the standby servers. While max_slot_wal_keep_size accepts the number of
bytes of WAL files, wal_keep_segments accepts the number of WAL files.
This difference of setting units between those similar parameters could
be confusing to users.
To alleviate this situation, this commit renames wal_keep_segments to
wal_keep_size, and make users specify the WAL size in it instead of
the number of WAL files.
There was also the idea to rename max_slot_wal_keep_size to
max_slot_wal_keep_segments, in the discussion. But we have been moving
away from measuring in segments, for example, checkpoint_segments was
replaced by max_wal_size. So we concluded to rename wal_keep_segments
to wal_keep_size.
Back-patch to v13 where max_slot_wal_keep_size was added.
Author: Fujii Masao
Reviewed-by: Álvaro Herrera, Kyotaro Horiguchi, David Steele
Discussion: https://postgr.es/m/574b4ea3-e0f9-b175-ead2-ebea7faea855@oss.nttdata.com
Replication slots are useful to retain data that may be needed by a
replication system. But experience has shown that allowing them to
retain excessive data can lead to the primary failing because of running
out of space. This new feature allows the user to configure a maximum
amount of space to be reserved using the new option
max_slot_wal_keep_size. Slots that overrun that space are invalidated
at checkpoint time, enabling the storage to be released.
Author: Kyotaro HORIGUCHI <horiguchi.kyotaro@lab.ntt.co.jp>
Reviewed-by: Masahiko Sawada <sawada.mshk@gmail.com>
Reviewed-by: Jehan-Guillaume de Rorthais <jgdr@dalibo.com>
Reviewed-by: Álvaro Herrera <alvherre@alvh.no-ip.org>
Discussion: https://postgr.es/m/20170228.122736.123383594.horiguchi.kyotaro@lab.ntt.co.jp
Incremental Sort is an optimized variant of multikey sort for cases when
the input is already sorted by a prefix of the requested sort keys. For
example when the relation is already sorted by (key1, key2) and we need
to sort it by (key1, key2, key3) we can simply split the input rows into
groups having equal values in (key1, key2), and only sort/compare the
remaining column key3.
This has a number of benefits:
- Reduced memory consumption, because only a single group (determined by
values in the sorted prefix) needs to be kept in memory. This may also
eliminate the need to spill to disk.
- Lower startup cost, because Incremental Sort produce results after each
prefix group, which is beneficial for plans where startup cost matters
(like for example queries with LIMIT clause).
We consider both Sort and Incremental Sort, and decide based on costing.
The implemented algorithm operates in two different modes:
- Fetching a minimum number of tuples without check of equality on the
prefix keys, and sorting on all columns when safe.
- Fetching all tuples for a single prefix group and then sorting by
comparing only the remaining (non-prefix) keys.
We always start in the first mode, and employ a heuristic to switch into
the second mode if we believe it's beneficial - the goal is to minimize
the number of unnecessary comparions while keeping memory consumption
below work_mem.
This is a very old patch series. The idea was originally proposed by
Alexander Korotkov back in 2013, and then revived in 2017. In 2018 the
patch was taken over by James Coleman, who wrote and rewrote most of the
current code.
There were many reviewers/contributors since 2013 - I've done my best to
pick the most active ones, and listed them in this commit message.
Author: James Coleman, Alexander Korotkov
Reviewed-by: Tomas Vondra, Andreas Karlsson, Marti Raudsepp, Peter Geoghegan, Robert Haas, Thomas Munro, Antonin Houska, Andres Freund, Alexander Kuzmenkov
Discussion: https://postgr.es/m/CAPpHfdscOX5an71nHd8WSUH6GNOCf=V7wgDaTXdDd9=goN-gfA@mail.gmail.com
Discussion: https://postgr.es/m/CAPpHfds1waRZ=NOmueYq0sx1ZSCnt+5QJvizT8ndT2=etZEeAQ@mail.gmail.com
Until now, only selected bulk operations (e.g. COPY) did this. If a
given relfilenode received both a WAL-skipping COPY and a WAL-logged
operation (e.g. INSERT), recovery could lose tuples from the COPY. See
src/backend/access/transam/README section "Skipping WAL for New
RelFileNode" for the new coding rules. Maintainers of table access
methods should examine that section.
To maintain data durability, just before commit, we choose between an
fsync of the relfilenode and copying its contents to WAL. A new GUC,
wal_skip_threshold, guides that choice. If this change slows a workload
that creates small, permanent relfilenodes under wal_level=minimal, try
adjusting wal_skip_threshold. Users setting a timeout on COMMIT may
need to adjust that timeout, and log_min_duration_statement analysis
will reflect time consumption moving to COMMIT from commands like COPY.
Internally, this requires a reliable determination of whether
RollbackAndReleaseCurrentSubTransaction() would unlink a relation's
current relfilenode. Introduce rd_firstRelfilenodeSubid. Amend the
specification of rd_createSubid such that the field is zero when a new
rel has an old rd_node. Make relcache.c retain entries for certain
dropped relations until end of transaction.
Bump XLOG_PAGE_MAGIC, since this introduces XLOG_GIST_ASSIGN_LSN.
Future servers accept older WAL, so this bump is discretionary.
Kyotaro Horiguchi, reviewed (in earlier, similar versions) by Robert
Haas. Heikki Linnakangas and Michael Paquier implemented earlier
designs that materially clarified the problem. Reviewed, in earlier
designs, by Andrew Dunstan, Andres Freund, Alvaro Herrera, Tom Lane,
Fujii Masao, and Simon Riggs. Reported by Martijn van Oosterhout.
Discussion: https://postgr.es/m/20150702220524.GA9392@svana.org
This patch replaces the boolean GUC log_parameters_on_error introduced
by commit ba79cb5dc with an integer log_parameter_max_length_on_error,
adding the ability to specify how many bytes to trim each logged
parameter value to. (The previous coding hard-wired that choice at
64 bytes.)
In addition, add a new parameter log_parameter_max_length that provides
similar control over truncation of query parameters that are logged in
response to statement-logging options, as opposed to errors. Previous
releases always logged such parameters in full, possibly causing log
bloat.
For backwards compatibility with prior releases,
log_parameter_max_length defaults to -1 (log in full), while
log_parameter_max_length_on_error defaults to 0 (no logging).
Per discussion, log_parameter_max_length is SUSET since the DBA should
control routine logging behavior, but log_parameter_max_length_on_error
is USERSET because it also affects errcontext data sent back to the
client.
Alexey Bashtanov, editorialized a little by me
Discussion: https://postgr.es/m/b10493cc-a399-a03a-67c7-068f2791ee50@imap.cc
Traditionally autovacuum has only ever invoked a worker based on the
estimated number of dead tuples in a table and for anti-wraparound
purposes. For the latter, with certain classes of tables such as
insert-only tables, anti-wraparound vacuums could be the first vacuum that
the table ever receives. This could often lead to autovacuum workers being
busy for extended periods of time due to having to potentially freeze
every page in the table. This could be particularly bad for very large
tables. New clusters, or recently pg_restored clusters could suffer even
more as many large tables may have the same relfrozenxid, which could
result in large numbers of tables requiring an anti-wraparound vacuum all
at once.
Here we aim to reduce the work required by anti-wraparound and aggressive
vacuums in general, by triggering autovacuum when the table has received
enough INSERTs. This is controlled by adding two new GUCs and reloptions;
autovacuum_vacuum_insert_threshold and
autovacuum_vacuum_insert_scale_factor. These work exactly the same as the
existing scale factor and threshold controls, only base themselves off the
number of inserts since the last vacuum, rather than the number of dead
tuples. New controls were added rather than reusing the existing
controls, to allow these new vacuums to be tuned independently and perhaps
even completely disabled altogether, which can be done by setting
autovacuum_vacuum_insert_threshold to -1.
We make no attempt to skip index cleanup operations on these vacuums as
they may trigger for an insert-mostly table which continually doesn't have
enough dead tuples to trigger an autovacuum for the purpose of removing
those dead tuples. If we were to skip cleaning the indexes in this case,
then it is possible for the index(es) to become bloated over time.
There are additional benefits to triggering autovacuums based on inserts,
as tables which never contain enough dead tuples to trigger an autovacuum
are now more likely to receive a vacuum, which can mark more of the table
as "allvisible" and encourage the query planner to make use of Index Only
Scans.
Currently, we still obey vacuum_freeze_min_age when triggering these new
autovacuums based on INSERTs. For large insert-only tables, it may be
beneficial to lower the table's autovacuum_freeze_min_age so that tuples
are eligible to be frozen sooner. Here we've opted not to zero that for
these types of vacuums, since the table may just be insert-mostly and we
may otherwise freeze tuples that are still destined to be updated or
removed in the near future.
There was some debate to what exactly the new scale factor and threshold
should default to. For now, these are set to 0.2 and 1000, respectively.
There may be some motivation to adjust these before the release.
Author: Laurenz Albe, Darafei Praliaskouski
Reviewed-by: Alvaro Herrera, Masahiko Sawada, Chris Travers, Andres Freund, Justin Pryzby
Discussion: https://postgr.es/m/CAC8Q8t%2Bj36G_bLF%3D%2B0iMo6jGNWnLnWb1tujXuJr-%2Bx8ZCCTqoQ%40mail.gmail.com
