Handling of incompatible clauses while applying extended statistics was
a bit confused - while handling a mix of compatible and incompatible
clauses it sometimes incorrectly treated the incompatible clauses as
compatible, resulting in a crash.
Fixed by reworking the code applying the selected statistics object to
make it easier to understand, and adding a proper compatibility check.
Reported-by: David Rowley
Discussion: https://postgr.es/m/CAApHDvpYT10-nkSp8xXe-nbO3jmoaRyRFHbzh-RWMfAJynqgpQ%40mail.gmail.com
Add a lazy_scan_heap() subsidiary function that handles heap pruning and
tuple freezing: lazy_scan_prune(). This is a great deal cleaner. The
code that remains in lazy_scan_heap()'s per-block loop can now be
thought of as code that either comes before or after the call to
lazy_scan_prune(), which is now the clear focal point. This division is
enforced by the way in which we now manage state. lazy_scan_prune()
outputs state (using its own struct) that describes what to do with the
page following pruning and freezing (e.g., visibility map maintenance,
recording free space in the FSM). It doesn't get passed any special
instructional state from the preamble code, though.
Also cleanly separate the logic used by a VACUUM with INDEX_CLEANUP=off
from the logic used by single-heap-pass VACUUMs. The former case is now
structured as the omission of index and heap vacuuming by a two pass
VACUUM. The latter case goes back to being used only when the table
happens to have no indexes (just as it was before commit a96c41fe).
This structure is much more natural, since the whole point of
INDEX_CLEANUP=off is to skip the index and heap vacuuming that would
otherwise take place. The single-heap-pass case doesn't skip any useful
work, though -- it just does heap pruning and heap vacuuming together
when the table happens to have no indexes.
Both of these changes are preparation for an upcoming patch that
generalizes the mechanism used by INDEX_CLEANUP=off. The later patch
will allow VACUUM to give up on index and heap vacuuming dynamically, as
problems emerge (e.g., with wraparound), so that an affected VACUUM
operation can finish up as soon as possible.
Also fix a very old bug in single-pass VACUUM VERBOSE output. We were
reporting the number of tuples deleted via pruning as a direct
substitute for reporting the number of LP_DEAD items removed in a
function that deals with the second pass over the heap. But that
doesn't work at all -- they're two different things.
To fix, start tracking the total number of LP_DEAD items encountered
during pruning, and use that in the report instead. A single pass
VACUUM will always vacuum away whatever LP_DEAD items a heap page has
immediately after it is pruned, so the total number of LP_DEAD items
encountered during pruning equals the total number vacuumed-away.
(They are _not_ equal in the INDEX_CLEANUP=off case, but that's okay
because skipping index vacuuming is now a totally orthogonal concept to
one-pass VACUUM.)
Also stop reporting the count of LP_UNUSED items in VACUUM VERBOSE
output. This makes the output of VACUUM VERBOSE more consistent with
log_autovacuum's output (because it never showed information about
LP_UNUSED items). VACUUM VERBOSE reported LP_UNUSED items left behind
by the last VACUUM, and LP_UNUSED items created via pruning HOT chains
during the current VACUUM (it never included LP_UNUSED items left behind
by the current VACUUM's second pass over the heap). This makes it
useless as an indicator of line pointer bloat, which must have been the
original intention. (Like the first VACUUM VERBOSE issue, this issue was
arguably an oversight in commit 282d2a03, which added the heap-only
tuple optimization.)
Finally, stop reporting empty_pages in VACUUM VERBOSE output, and start
reporting pages_removed instead. This also makes the output of VACUUM
VERBOSE more consistent with log_autovacuum's output (which does not
show empty_pages, but does show pages_removed). An empty page isn't
meaningfully different to a page that is almost empty, or a page that is
empty but for only a small number of remaining LP_UNUSED items.
Author: Peter Geoghegan <pg@bowt.ie>
Reviewed-By: Robert Haas <robertmhaas@gmail.com>
Reviewed-By: Masahiko Sawada <sawada.mshk@gmail.com>
Discussion: https://postgr.es/m/CAH2-WznneCXTzuFmcwx_EyRQgfsfJAAsu+CsqRFmFXCAar=nJw@mail.gmail.com
Andrew Gierth reported that it's possible to crash the backend if no
pg_attrdef record is found to match an attribute that has atthasdef set.
AttrDefaultFetch warns about this situation, but then leaves behind
a relation tupdesc that has null "adbin" pointer(s), which most places
don't guard against.
We considered promoting the warning to an error, but throwing errors
during relcache load is pretty drastic: it effectively locks one out
of using the relation at all. What seems better is to leave the
load-time behavior as a warning, but then throw an error in any code
path that wants to use a default and can't find it. This confines
the error to a subset of INSERT/UPDATE operations on the table, and
in particular will at least allow a pg_dump to succeed.
Also, we should fix AttrDefaultFetch to not leave any null pointers
in the tupdesc, because that just creates an untested bug hazard.
While at it, apply the same philosophy of "warn at load, throw error
only upon use of the known-missing info" to CHECK constraints.
CheckConstraintFetch is very nearly the same logic as AttrDefaultFetch,
but for reasons lost in the mists of time, it was throwing ERROR for
the same cases that AttrDefaultFetch treats as WARNING. Make the two
functions more nearly alike.
In passing, get rid of potentially-O(N^2) loops in equalTupleDesc
by making AttrDefaultFetch sort the entries after fetching them,
so that equalTupleDesc can assume that entries in two equal tupdescs
must be in matching order. (CheckConstraintFetch already was sorting
CHECK constraints, but equalTupleDesc hadn't been told about it.)
There's some argument for back-patching this, but with such a small
number of field reports, I'm content to fix it in HEAD.
Discussion: https://postgr.es/m/87pmzaq4gx.fsf@news-spur.riddles.org.uk
Previously if hot standby was enabled, archive recovery exited with
an error when it found WAL generated with wal_level=minimal.
But if hot standby was disabled, it just reported a warning and
continued in that case. Which could lead to data loss or errors
during normal operation. A warning was emitted, but users could
easily miss that and not notice this serious situation until
they encountered the actual errors.
To improve this situation, this commit changes archive recovery
so that it exits with FATAL error when it finds WAL generated with
wal_level=minimal whatever the setting of hot standby. This enables
users to notice the serious situation soon.
The FATAL error is thrown if archive recovery starts from a base
backup taken before wal_level is changed to minimal. When archive
recovery exits with the error, if users have a base backup taken
after setting wal_level to higher than minimal, they can recover
the database by starting archive recovery from that newer backup.
But note that if such backup doesn't exist, there is no easy way to
complete archive recovery, which may make the database server
unstartable and users may lose whole database. The commit adds
the note about this risk into the document.
Even in the case of unstartable database server, previously by just
disabling hot standby users could avoid the error during archive
recovery, forcibly start up the server and salvage data from it.
But note that this commit makes this procedure unavailable at all.
Author: Takamichi Osumi
Reviewed-by: Laurenz Albe, Kyotaro Horiguchi, David Steele, Fujii Masao
Discussion: https://postgr.es/m/OSBPR01MB4888CBE1DA08818FD2D90ED8EDF90@OSBPR01MB4888.jpnprd01.prod.outlook.com
Adjust the number of events given to WaitEventSetWait() so that it
doesn't exceed the maximum number of events in the WaitEventSet given
to that function (set->nevents_space) in hopes of making the buildfarm
green.
Per valgrind failure report from Tom Lane and the buildfarm.
Author: Etsuro Fujita
Discussion: https://postgr.es/m/3411577.1617289776%40sss.pgh.pa.us
At present, if we want to update publications in a subscription, we
can use SET PUBLICATION. However, it requires supplying all
publications that exists and the new publications. If we want to add
new publications, it's inconvenient. The new syntax only supplies the
new publications. When the refresh is true, it only refreshes the new
publications.
Author: Japin Li <japinli@hotmail.com>
Author: Bharath Rupireddy <bharath.rupireddyforpostgres@gmail.com>
Discussion: https://www.postgresql.org/message-id/flat/MEYP282MB166939D0D6C480B7FBE7EFFBB6BC0@MEYP282MB1669.AUSP282.PROD.OUTLOOK.COM
The previous implementation of EXTRACT mapped internally to
date_part(), which returned type double precision (since it was
implemented long before the numeric type existed). This can lead to
imprecise output in some cases, so returning numeric would be
preferrable. Changing the return type of an existing function is a
bit risky, so instead we do the following: We implement a new set of
functions, which are now called "extract", in parallel to the existing
date_part functions. They work the same way internally but use
numeric instead of float8. The EXTRACT construct is now mapped by the
parser to these new extract functions. That way, dumps of views
etc. from old versions (which would use date_part) continue to work
unchanged, but new uses will map to the new extract functions.
Additionally, the reverse compilation of EXTRACT now reproduces the
original syntax, using the new mechanism introduced in
40c24bfef9.
The following minor changes of behavior result from the new
implementation:
- The column name from an isolated EXTRACT call is now "extract"
instead of "date_part".
- Extract from date now rejects inappropriate field names such as
HOUR. It was previously mapped internally to extract from
timestamp, so it would silently accept everything appropriate for
timestamp.
- Return values when extracting fields with possibly fractional
values, such as second and epoch, now have the full scale that the
value has internally (so, for example, '1.000000' instead of just
'1').
Reported-by: Petr Fedorov <petr.fedorov@phystech.edu>
Reviewed-by: Tom Lane <tgl@sss.pgh.pa.us>
Discussion: https://www.postgresql.org/message-id/flat/42b73d2d-da12-ba9f-570a-420e0cce19d9@phystech.edu
Commit 3e98c0bafb added pg_backend_memory_contexts view to display
the memory contexts of the backend process. However its target process
is limited to the backend that is accessing to the view. So this is
not so convenient when investigating the local memory bloat of other
backend process. To improve this situation, this commit adds
pg_log_backend_memory_contexts() function that requests to log
the memory contexts of the specified backend process.
This information can be also collected by calling
MemoryContextStats(TopMemoryContext) via a debugger. But
this technique cannot be used in some environments because no debugger
is available there. So, pg_log_backend_memory_contexts() allows us to
see the memory contexts of specified backend more easily.
Only superusers are allowed to request to log the memory contexts
because allowing any users to issue this request at an unbounded rate
would cause lots of log messages and which can lead to denial of service.
On receipt of the request, at the next CHECK_FOR_INTERRUPTS(),
the target backend logs its memory contexts at LOG_SERVER_ONLY level,
so that these memory contexts will appear in the server log but not
be sent to the client. It logs one message per memory context.
Because if it buffers all memory contexts into StringInfo to log them
as one message, which may require the buffer to be enlarged very much
and lead to OOM error since there can be a large number of memory
contexts in a backend.
When a backend process is consuming huge memory, logging all its
memory contexts might overrun available disk space. To prevent this,
now this patch limits the number of child contexts to log per parent
to 100. As with MemoryContextStats(), it supposes that practical cases
where the log gets long will typically be huge numbers of siblings
under the same parent context; while the additional debugging value
from seeing details about individual siblings beyond 100 will not be large.
There was another proposed patch to add the function to return
the memory contexts of specified backend as the result sets,
instead of logging them, in the discussion. However that patch is
not included in this commit because it had several issues to address.
Thanks to Tatsuhito Kasahara, Andres Freund, Tom Lane, Tomas Vondra,
Michael Paquier, Kyotaro Horiguchi and Zhihong Yu for the discussion.
Bump catalog version.
Author: Atsushi Torikoshi
Reviewed-by: Kyotaro Horiguchi, Zhihong Yu, Fujii Masao
Discussion: https://postgr.es/m/0271f440ac77f2a4180e0e56ebd944d1@oss.nttdata.com
The output plugin accepts a new parameter (messages) that controls if
logical decoding messages are written into the replication stream. It is
useful for those clients that use pgoutput as an output plugin and needs
to process messages that were written by pg_logical_emit_message().
Although logical streaming replication protocol supports logical
decoding messages now, logical replication does not use this feature yet.
Author: David Pirotte, Euler Taveira
Reviewed-by: Euler Taveira, Andres Freund, Ashutosh Bapat, Amit Kapila
Discussion: https://postgr.es/m/CADK3HHJ-+9SO7KuRLH=9Wa1rAo60Yreq1GFNkH_kd0=CdaWM+A@mail.gmail.com
Instead of using multiple parameters in parse_ouput_parameters function
signature, use the struct PGOutputData that encapsulates all pgoutput
options. It will be useful for future work where we need to add other
options in pgoutput.
Author: Euler Taveira
Reviewed-by: Amit Kapila
Discussion: https://postgr.es/m/CADK3HHJ-+9SO7KuRLH=9Wa1rAo60Yreq1GFNkH_kd0=CdaWM+A@mail.gmail.com
Commit 49f49def took entirely the wrong approach to fixing this issue.
Just allocate a local buffer access strategy in each individual worker
instead of trying to propagate state. This state was never propagated
by parallel VACUUM in the first place.
It looks like the only reason that this worked following commit 40d964ec
was that it involved static global variables, which are initialized to 0
per the C standard.
A more comprehensive fix may be necessary, even on HEAD. This fix
should at least get the buildfarm green once again.
Thanks once again to Thomas Munro for continued off-list assistance with
the issue.
Not much to say here: does what it says on the tin.
We steal a previously-always-zero bit from the nextOffset
field of leaf index tuples in order to track whether there
is a nulls bitmap. Otherwise it works about like included
columns in other index types.
Pavel Borisov, reviewed by Andrey Borodin and Anastasia Lubennikova,
and rather heavily editorialized on by me
Discussion: https://postgr.es/m/CALT9ZEFi-vMp4faht9f9Junb1nO3NOSjhpxTmbm1UGLMsLqiEQ@mail.gmail.com
Parallel VACUUM relied on global variable state from the leader process
being propagated to workers on fork(). Commit b4af70cb removed most
uses of global variables inside vacuumlazy.c, but did not account for
the buffer access strategy state.
To fix, propagate the state through shared memory instead.
Per buildfarm failures on elver, curculio, and morepork.
Many thanks to Thomas Munro for off-list assistance with this issue.
Reorganize the state struct used by VACUUM -- group related items
together to make it easier to understand. Also stop relying on stack
variables inside lazy_scan_heap() -- move those into the state struct
instead. Doing things this way simplifies large groups of related
functions whose function signatures had a lot of unnecessary redundancy.
Switch over to using int64 for the struct fields used to count things
that are reported to the user via log_autovacuum and VACUUM VERBOSE
output. We were using double, but that doesn't seem to have any
advantages. Using int64 makes it possible to add assertions that verify
that the first pass over the heap (pruning) encounters precisely the
same number of LP_DEAD items that get deleted from indexes later on, in
the second pass over the heap. These assertions will be added in later
commits.
Finally, adjust the signatures of functions with IndexBulkDeleteResult
pointer arguments in cases where there was ambiguity about whether or
not the argument relates to a single index or all indexes. Functions
now use the idiom that both ambulkdelete() and amvacuumcleanup() have
always used (where appropriate): accept a mutable IndexBulkDeleteResult
pointer argument, and return a result IndexBulkDeleteResult pointer to
caller.
Author: Peter Geoghegan <pg@bowt.ie>
Reviewed-By: Masahiko Sawada <sawada.mshk@gmail.com>
Reviewed-By: Robert Haas <robertmhaas@gmail.com>
Discussion: https://postgr.es/m/CAH2-WzkeOSYwC6KNckbhk2b1aNnWum6Yyn0NKP9D-Hq1LGTDPw@mail.gmail.com
A commonly requested use-case is to have a role who can run an
unfettered pg_dump without having to explicitly GRANT that user access
to all tables, schemas, et al, without that role being a superuser.
This address that by adding a "pg_read_all_data" role which implicitly
gives any member of this role SELECT rights on all tables, views and
sequences, and USAGE rights on all schemas.
As there may be cases where it's also useful to have a role who has
write access to all objects, pg_write_all_data is also introduced and
gives users implicit INSERT, UPDATE and DELETE rights on all tables,
views and sequences.
These roles can not be logged into directly but instead should be
GRANT'd to a role which is able to log in. As noted in the
documentation, if RLS is being used then an administrator may (or may
not) wish to set BYPASSRLS on the login role which these predefined
roles are GRANT'd to.
Reviewed-by: Georgios Kokolatos
Discussion: https://postgr.es/m/20200828003023.GU29590@tamriel.snowman.net
Maxim Orlov reported that the shutdown of standby server could result in
the following assertion failure. The cause of this issue was that,
when the shutdown caused the startup process to exit, recovery-time
transaction tracking was not shut down even if it's already initialized,
and some locks the tracked transactions were holding could not be released.
At this situation, if other process was invoked and the PGPROC entry that
the startup process used was assigned to it, it found such unreleased locks
and caused the assertion failure, during the initialization of it.
TRAP: FailedAssertion("SHMQueueEmpty(&(MyProc->myProcLocks[i]))"
This commit fixes this issue by making the startup process shut down
transaction tracking and release all locks, at the exit of it.
Back-patch to all supported branches.
Reported-by: Maxim Orlov
Author: Fujii Masao
Reviewed-by: Maxim Orlov
Discussion: https://postgr.es/m/ad4ce692cc1d89a093b471ab1d969b0b@postgrespro.ru
spg_box_quad_leaf_consistent unconditionally returned the leaf
datum as leafValue, even though in its usage for poly_ops that
value is of completely the wrong type.
In versions before 12, that was harmless because the core code did
nothing with leafValue in non-index-only scans ... but since commit
2a6368343, if we were doing a KNN-style scan, spgNewHeapItem would
unconditionally try to copy the value using the wrong datatype
parameters. Said copying is a waste of time and space if we're not
going to return the data, but it accidentally failed to fail until
I fixed the datatype confusion in ac9099fc1.
Hence, change spgNewHeapItem to not copy the datum unless we're
actually going to return it later. This saves cycles and dodges
the question of whether lossy opclasses are returning the right
type. Also change spg_box_quad_leaf_consistent to not return
data that might be of the wrong type, as insurance against
somebody introducing a similar bug into the core code in future.
It seems like a good idea to back-patch these two changes into
v12 and v13, although I'm afraid to change spgNewHeapItem's
mistaken idea of which datatype to use in those branches.
Per buildfarm results from ac9099fc1.
Discussion: https://postgr.es/m/3728741.1617381471@sss.pgh.pa.us
According to the documentation, the attType passed to the opclass
config function (and also relied on by the core code) is the type
of the heap column or expression being indexed. But what was
actually being passed was the type stored for the index column.
This made no difference for user-defined SP-GiST opclasses,
because we weren't allowing the STORAGE clause of CREATE OPCLASS
to be used, so the two types would be the same. But it's silly
not to allow that, seeing that the built-in poly_ops opclass
has a different value for opckeytype than opcintype, and that if you
want to do lossy storage then the types must really be different.
(Thus, user-defined opclasses doing lossy storage had to lie about
what type is in the index.) Hence, remove the restriction, and make
sure that we use the input column type not opckeytype where relevant.
For reasons of backwards compatibility with existing user-defined
opclasses, we can't quite insist that the specified leafType match
the STORAGE clause; instead just add an amvalidate() warning if
they don't match.
Also fix some bugs that would only manifest when trying to return
index entries when attType is different from attLeafType. It's not
too surprising that these have not been reported, because the only
usual reason for such a difference is to store the leaf value
lossily, rendering index-only scans impossible.
Add a src/test/modules module to exercise cases where attType is
different from attLeafType and yet index-only scan is supported.
Discussion: https://postgr.es/m/3728741.1617381471@sss.pgh.pa.us
When calling sort_expanded_ranges() we need to remember the return
value, because the function sorts and also deduplicates the ranges. So
the number of ranges may decrease. brin_minmax_multi_union failed to do
that, which resulted in crashes due to bogus ranges (equal minval/maxval
but not marked as compacted).
Reported-by: Jaime Casanova
Discussion: https://postgr.es/m/20210404052550.GA4376%40ahch-to
The BRIN minmax-multi consistent function incorrectly assumed it can
lookup an operator, and then swap the arguments to get the commutator.
For example <(a,b) would be called as <(b,a) to get >(a,b). This works
when the arguments are of the same type, but with cross-type opclasses
this fails. We can't swap <(float4,float8) arguments, for example.
Fixed by passing arguments in the right order.
Discussion: https://postgr.es/m/CAJKUy5jLZFLCxyxfT%3DMfK5mtPfSzHA1rVLowR-j4RRsFVvKm7A%40mail.gmail.com
The distance calculation ignored the mask, unlike the inet comparator,
which resulted in negative distance in some cases. Fixed by applying the
mask in brin_minmax_multi_distance_inet. I've considered simply calling
inetmi() to calculate the delta, but that does not consider mask either.
Reviewed-by: Zhihong Yu
Discussion: https://postgr.es/m/1a0a7b9d-9bda-e3a2-7fa4-88f15042a051%40enterprisedb.com
The distance calculation for interval type was treating months as having
31 days, which is inconsistent with the interval comparator (using 30
days). Due to this it was possible to get negative distance (b-a) when
(a<b), trigerring an assert.
Fixed by adopting the same logic as interval_cmp_value.
Reported-by: Jaime Casanova
Discussion: https://postgr.es/m/CAJKUy5jKH0Xhneau2mNftNPtTy-BVgQfXc8zQkEvRvBHfeUThQ%40mail.gmail.com
pgstat_report_wait_start() and pgstat_report_wait_end() required two
conditional branches so far. One to check if MyProc is NULL, the other to
check if pgstat_track_activities is set. As wait events are used around
comparatively lightweight operations, and are inlined (reducing branch
predictor effectiveness), that's not great.
The dependency on MyProc has a second disadvantage: Low-level subsystems, like
storage/file/fd.c, report wait events, but architecturally it is preferable
for them to not depend on inter-process subsystems like proc.h (defining
PGPROC). After this change including pgstat.h (nor obviously its
sub-components like backend_status.h, wait_event.h, ...) does not pull in IPC
related headers anymore.
These goals, efficiency and abstraction, are achieved by having
pgstat_report_wait_start/end() not interact with MyProc, but instead a new
my_wait_event_info variable. At backend startup it points to a local variable,
removing the need to check for MyProc being NULL. During process
initialization my_wait_event_info is redirected to MyProc->wait_event_info. At
shutdown this is reversed. Because wait event reporting now does not need to
know about where the wait event is stored, it does not need to know about
PGPROC anymore.
The removal of the branch for checking pgstat_track_activities is simpler:
Don't check anymore. The cost due to the branch are often higher than the
store - and even if not, pgstat_track_activities is rarely disabled.
The main motivator to commit this work now is that removing the (indirect)
pgproc.h include from pgstat.h simplifies a patch to move statistics reporting
to shared memory (which still has a chance to get into 14).
Author: Andres Freund <andres@anarazel.de>
Discussion: https://postgr.es/m/20210402194458.2vu324hkk2djq6ce@alap3.anarazel.de
Backend status (supporting pg_stat_activity) and command
progress (supporting pg_stat_progress*) related code is largely
independent from the rest of pgstat.[ch] (supporting views like
pg_stat_all_tables that accumulate data over time). See also
a333476b92.
This commit doesn't rename the function names to make the distinction
from the rest of pgstat_ clearer - that'd be more invasive and not
clearly beneficial. If we were to decide to do such a rename at some
point, it's better done separately from moving the code as well.
Robert's review was of an earlier version.
Reviewed-By: Robert Haas <robertmhaas@gmail.com>
Discussion: https://postgr.es/m/20210316195440.twxmlov24rr2nxrg@alap3.anarazel.de
Similarly to the cryptohash implementations, this refactors the existing
HMAC code into a single set of APIs that can be plugged with any crypto
libraries PostgreSQL is built with (only OpenSSL currently). If there
is no such libraries, a fallback implementation is available. Those new
APIs are designed similarly to the existing cryptohash layer, so there
is no real new design here, with the same logic around buffer bound
checks and memory handling.
HMAC has a dependency on cryptohashes, so all the cryptohash types
supported by cryptohash{_openssl}.c can be used with HMAC. This
refactoring is an advantage mainly for SCRAM, that included its own
implementation of HMAC with SHA256 without relying on the existing
crypto libraries even if PostgreSQL was built with their support.
This code has been tested on Windows and Linux, with and without
OpenSSL, across all the versions supported on HEAD from 1.1.1 down to
1.0.1. I have also checked that the implementations are working fine
using some sample results, a custom extension of my own, and doing
cross-checks across different major versions with SCRAM with the client
and the backend.
Author: Michael Paquier
Reviewed-by: Bruce Momjian
Discussion: https://postgr.es/m/X9m0nkEJEzIPXjeZ@paquier.xyz
The wait event related code is independent from the rest of the
pgstat.[ch] code, of nontrivial size and changes on a regular
basis. Put it into its own set of files.
As there doesn't seem to be a good pre-existing directory for code
like this, add src/backend/utils/activity.
Reviewed-By: Robert Haas <robertmhaas@gmail.com>
Discussion: https://postgr.es/m/20210316195440.twxmlov24rr2nxrg@alap3.anarazel.de
Testing if an unsigned variable is >= 0 is pretty pointless.
There's likely enough code in remove_cache_entry() to verify the cache
memory accounting is correct in assert enabled builds. These Asserts
were not adding much extra cover, even if they had been checking >= 0 on a
signed variable.
Reported-by: Andres Freund
Discussion: https://postgr.es/m/20210402204734.6mo3nfacnljlicgn@alap3.anarazel.de
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
Commit dd136052b established a policy that error message FILE items
should include only the base name of the reporting source file, for
uniformity and succinctness. We now observe that some Windows compilers
use backslashes in __FILE__ strings, so truncate at backslashes as well.
This is expected to fix some platform variation in the results of the
new libpq_pipeline test module.
Discussion: https://postgr.es/m/3650140.1617372290@sss.pgh.pa.us
The caller of pgstat_report_replslot() passes int64 values to the function.
Also the function stores those values in PgStat_Counter (i.e., int64) fields
of PgStat_MsgReplSlot struct. But previously the function used "int" as
the data types of some arguments for those values, which could lead to
the overflow of values.
To avoid this risk, this commit fixes pgstat_report_replslot() to use
PgStat_Counter type for the arguments. Since they are the statistics counters,
PgStat_Counter, the data type used for counters, is used for them
instead of int64.
Reported-by: Vignesh C
Author: Vignesh C
Reviewed-by: Jeevan Ladhe, Fujii Masao
Discussion: https://postgr.es/m/CALDaNm080OpG=ZwOb0i8EyChH5SyHAMFWJCKaKTXmrfvJLbgaA@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, 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
The existing convention in SP-GiST is that any pass-by-value datatype
is stored in Datum representation, i.e. it's of width sizeof(Datum)
even when typlen is less than that. This is okay, or at least it's
too late to change it, for prefix datums and node-label datums in inner
(upper) tuples. But it's problematic for leaf datums, because we'd
prefer those to be stored in Postgres' standard on-disk representation
so that we can easily extend leaf tuples to carry additional "included"
columns.
I believe, however, that we can get away with just up and changing that.
This would be an unacceptable on-disk-format break, but there are two
big mitigating factors:
1. It seems quite unlikely that there are any SP-GiST opclasses out
there that use pass-by-value leaf datatypes. Certainly none of the
ones in core do, nor has codesearch.debian.net heard of any. Given
what SP-GiST is good for, it's hard to conceive of a use-case where
the leaf-level values would be both small and fixed-width. (As an
example, if you wanted to index text values with the leaf level being
just a byte, then every text string would have to be represented
with one level of inner tuple per preceding byte, which would be
horrendously space-inefficient and slow to access. You always want
to use as few inner-tuple levels as possible, leaving as much as
possible in the leaf values.)
2. Even granting that you have such an index, this change only
breaks things on big-endian machines. On little-endian, the high
order bytes of the Datum format will now just appear to be alignment
padding space.
So, change the code to store pass-by-value leaf datums in their
usual on-disk form. Inner-tuple datums are not touched.
This is extracted from a larger patch that intends to add support for
"included" columns. I'm committing it separately for visibility in
our commit logs.
Pavel Borisov and Tom Lane, reviewed by Andrey Borodin
Discussion: https://postgr.es/m/CALT9ZEFi-vMp4faht9f9Junb1nO3NOSjhpxTmbm1UGLMsLqiEQ@mail.gmail.com
Through various refactorings over time, the extract(timezone_minute
from time with time zone) and extract(timezone_minute from timestamp
with time zone) implementations ended up with two different but
equally nonsensical formulas by using SECS_PER_MINUTE and
MINS_PER_HOUR interchangeably. Since those two are of course both the
same number, the formulas do work, but for readability, fix them to be
semantically correct.
This gives a small performance gain, by reducing the number of calls
to the conversion/verification function, and letting it work with
larger inputs. Also, reorganizing the input pipeline makes it easier
to parallelize the input parsing: after the input has been converted
to the database encoding, the next stage of finding the newlines can
be done in parallel, because there cannot be any newline chars
"embedded" in multi-byte characters in the encodings that we support
as server encodings.
This changes behavior in one corner case: if client and server
encodings are the same single-byte encoding (e.g. latin1), previously
the input would not be checked for zero bytes ('\0'). Any fields
containing zero bytes would be truncated at the zero. But if encoding
conversion was needed, the conversion routine would throw an error on
the zero. After this commit, the input is always checked for zeros.
Reviewed-by: John Naylor
Discussion: https://www.postgresql.org/message-id/e7861509-3960-538a-9025-b75a61188e01%40iki.fi
With the 'noError' argument, you can try to convert a buffer without
knowing the character boundaries beforehand. The functions now need to
return the number of input bytes successfully converted.
This is is a backwards-incompatible change, if you have created a custom
encoding conversion with CREATE CONVERSION. This adds a check to
pg_upgrade for that, refusing the upgrade if there are any user-defined
encoding conversions. Custom conversions are very rare, there are no
commonly used extensions that I know of that uses that feature. No other
objects can depend on conversions, so if you do have one, you can fairly
easily drop it before upgrading, and recreate it after the upgrade with
an updated version.
Add regression tests for built-in encoding conversions. This doesn't cover
every conversion, but it covers all the internal functions in conv.c that
are used to implement the conversions.
Reviewed-by: John Naylor
Discussion: https://www.postgresql.org/message-id/e7861509-3960-538a-9025-b75a61188e01%40iki.fi
It is possible that while decoding a prepared transaction, it gets aborted
concurrently via a ROLLBACK PREPARED command. In that case, we were
skipping all the changes and directly sending Rollback Prepared when we
find the same in WAL. However, the downstream has no idea of the GID of
such a transaction. So, ensure to send prepare even when a concurrent
abort is detected.
Author: Ajin Cherian
Reviewed-by: Markus Wanner, Amit Kapila
Discussion: https://postgr.es/m/f82133c6-6055-b400-7922-97dae9f2b50b@enterprisedb.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
Since a4d75c86b, some buildfarm members have been warning that
Assert(attnum <= MaxAttrNumber);
is useless if attnum is an AttrNumber. I'm not certain how plausible
it is that the value coming out of the bitmap could actually exceed
MaxAttrNumber, but we seem to have thought that that was possible back
in 7300a6995. Revert the intermediate variable to int so that we have
the same overflow protection as before.
Put the remote end's error message into the primary error string,
instead of relegating it to errdetail(). Although this could end up
being awkward if the remote sends us a really long error message,
it seems more in keeping with our message style guidelines, and more
helpful in situations where the errdetail could get dropped.
Peter Smith
Discussion: https://postgr.es/m/CAHut+Ps-Qv2yQceCwobQDP0aJOkfDzRFrOaR6+2Op2K=WHGeWg@mail.gmail.com
According to the comments, when an invalid or dropped column oid is passed
to has_column_privilege(), the intention has always been to return NULL.
However, when the caller had table level privilege the invalid/missing
column was never discovered, because table permissions were checked first.
Fix that by introducing extended versions of pg_attribute_acl(check|mask)
and pg_class_acl(check|mask) which take a new argument, is_missing. When
is_missing is NULL, the old behavior is preserved. But when is_missing is
passed by the caller, no ERROR is thrown for dropped or missing
columns/relations, and is_missing is flipped to true. This in turn allows
has_column_privilege to check for column privileges first, providing the
desired semantics.
Not backpatched since it is a user visible behavioral change with no previous
complaints, and the fix is a bit on the invasive side.
Author: Joe Conway
Reviewed-By: Tom Lane
Reported by: Ian Barwick
Discussion: https://postgr.es/m/flat/9b5f4311-157b-4164-7fe7-077b4fe8ed84%40joeconway.com
This patch makes two closely related sets of changes:
1. For UPDATE, the subplan of the ModifyTable node now only delivers
the new values of the changed columns (i.e., the expressions computed
in the query's SET clause) plus row identity information such as CTID.
ModifyTable must re-fetch the original tuple to merge in the old
values of any unchanged columns. The core advantage of this is that
the changed columns are uniform across all tables of an inherited or
partitioned target relation, whereas the other columns might not be.
A secondary advantage, when the UPDATE involves joins, is that less
data needs to pass through the plan tree. The disadvantage of course
is an extra fetch of each tuple to be updated. However, that seems to
be very nearly free in context; even worst-case tests don't show it to
add more than a couple percent to the total query cost. At some point
it might be interesting to combine the re-fetch with the tuple access
that ModifyTable must do anyway to mark the old tuple dead; but that
would require a good deal of refactoring and it seems it wouldn't buy
all that much, so this patch doesn't attempt it.
2. For inherited UPDATE/DELETE, instead of generating a separate
subplan for each target relation, we now generate a single subplan
that is just exactly like a SELECT's plan, then stick ModifyTable
on top of that. To let ModifyTable know which target relation a
given incoming row refers to, a tableoid junk column is added to
the row identity information. This gets rid of the horrid hack
that was inheritance_planner(), eliminating O(N^2) planning cost
and memory consumption in cases where there were many unprunable
target relations.
Point 2 of course requires point 1, so that there is a uniform
definition of the non-junk columns to be returned by the subplan.
We can't insist on uniform definition of the row identity junk
columns however, if we want to keep the ability to have both
plain and foreign tables in a partitioning hierarchy. Since
it wouldn't scale very far to have every child table have its
own row identity column, this patch includes provisions to merge
similar row identity columns into one column of the subplan result.
In particular, we can merge the whole-row Vars typically used as
row identity by FDWs into one column by pretending they are type
RECORD. (It's still okay for the actual composite Datums to be
labeled with the table's rowtype OID, though.)
There is more that can be done to file down residual inefficiencies
in this patch, but it seems to be committable now.
FDW authors should note several API changes:
* The argument list for AddForeignUpdateTargets() has changed, and so
has the method it must use for adding junk columns to the query. Call
add_row_identity_var() instead of manipulating the parse tree directly.
You might want to reconsider exactly what you're adding, too.
* PlanDirectModify() must now work a little harder to find the
ForeignScan plan node; if the foreign table is part of a partitioning
hierarchy then the ForeignScan might not be the direct child of
ModifyTable. See postgres_fdw for sample code.
* To check whether a relation is a target relation, it's no
longer sufficient to compare its relid to root->parse->resultRelation.
Instead, check it against all_result_relids or leaf_result_relids,
as appropriate.
Amit Langote and Tom Lane
Discussion: https://postgr.es/m/CA+HiwqHpHdqdDn48yCEhynnniahH78rwcrv1rEX65-fsZGBOLQ@mail.gmail.com
This allows something like
SELECT ... FROM t1 JOIN t2 USING (a, b, c) AS x
where x has the columns a, b, c and unlike a regular alias it does not
hide the range variables of the tables being joined t1 and t2.
Per SQL:2016 feature F404 "Range variable for common column names".
Reviewed-by: Vik Fearing <vik.fearing@2ndquadrant.com>
Reviewed-by: Tom Lane <tgl@sss.pgh.pa.us>
Discussion: https://www.postgresql.org/message-id/flat/454638cf-d563-ab76-a585-2564428062af@2ndquadrant.com
Tom Lane
Tomas Vondra
Peter Geoghegan
Fujii Masao
Etsuro Fujita
Peter Eisentraut
Amit Kapila
Stephen Frost
Michael Paquier
Andres Freund
David Rowley
Thomas Munro
Heikki Linnakangas
Joe Conway