When we first put in collations support, we basically punted on teaching
pg_statistic, ANALYZE, and the planner selectivity functions about that.
They've just used DEFAULT_COLLATION_OID independently of the actual
collation of the data. It's time to improve that, so:
* Add columns to pg_statistic that record the specific collation associated
with each statistics slot.
* Teach ANALYZE to use the column's actual collation when comparing values
for statistical purposes, and record this in the appropriate slot. (Note
that type-specific typanalyze functions are now expected to fill
stats->stacoll with the appropriate collation, too.)
* Teach assorted selectivity functions to use the actual collation of
the stats they are looking at, instead of just assuming it's
DEFAULT_COLLATION_OID.
This should give noticeably better results in selectivity estimates for
columns with nondefault collations, at least for query clauses that use
that same collation (which would be the default behavior in most cases).
It's still true that comparisons with explicit COLLATE clauses different
from the stored data's collation won't be well-estimated, but that's no
worse than before. Also, this patch does make the first step towards
doing better with that, which is that it's now theoretically possible to
collect stats for a collation other than the column's own collation.
Patch by me; thanks to Peter Eisentraut for review.
Discussion: https://postgr.es/m/14706.1544630227@sss.pgh.pa.us
Upcoming work intends to allow pluggable ways to introduce new ways of
storing table data. Accessing those table access methods from the
executor requires TupleTableSlots to be carry tuples in the native
format of such storage methods; otherwise there'll be a significant
conversion overhead.
Different access methods will require different data to store tuples
efficiently (just like virtual, minimal, heap already require fields
in TupleTableSlot). To allow that without requiring additional pointer
indirections, we want to have different structs (embedding
TupleTableSlot) for different types of slots. Thus different types of
slots are needed, which requires adapting creators of slots.
The slot that most efficiently can represent a type of tuple in an
executor node will often depend on the type of slot a child node
uses. Therefore we need to track the type of slot is returned by
nodes, so parent slots can create slots based on that.
Relatedly, JIT compilation of tuple deforming needs to know which type
of slot a certain expression refers to, so it can create an
appropriate deforming function for the type of tuple in the slot.
But not all nodes will only return one type of slot, e.g. an append
node will potentially return different types of slots for each of its
subplans.
Therefore add function that allows to query the type of a node's
result slot, and whether it'll always be the same type (whether it's
fixed). This can be queried using ExecGetResultSlotOps().
The scan, result, inner, outer type of slots are automatically
inferred from ExecInitScanTupleSlot(), ExecInitResultSlot(),
left/right subtrees respectively. If that's not correct for a node,
that can be overwritten using new fields in PlanState.
This commit does not introduce the actually abstracted implementation
of different kind of TupleTableSlots, that will be left for a followup
commit. The different types of slots introduced will, for now, still
use the same backing implementation.
While this already partially invalidates the big comment in
tuptable.h, it seems to make more sense to update it later, when the
different TupleTableSlot implementations actually exist.
Author: Ashutosh Bapat and Andres Freund, with changes by Amit Khandekar
Discussion: https://postgr.es/m/20181105210039.hh4vvi4vwoq5ba2q@alap3.anarazel.de
It's inefficient to use a single slot for mapping between tuple
descriptors for multiple tuples, as previously done when using
ConvertPartitionTupleSlot(), as that means the slot's tuple descriptors
change for every tuple.
Previously we also, via ConvertPartitionTupleSlot(), built new tuples
after the mapping even in cases where we, immediately afterwards,
access individual columns again.
Refactor the code so one slot, on demand, is used for each
partition. That avoids having to change the descriptor (and allows to
use the more efficient "fixed" tuple slots). Then use slot->slot
mapping, to avoid unnecessarily forming a tuple.
As the naming between the tuple and slot mapping functions wasn't
consistent, rename them to execute_attr_map_{tuple,slot}. It's likely
that we'll also rename convert_tuples_by_* to denote that these
functions "only" build a map, but that's left for later.
Author: Amit Khandekar and Amit Langote, editorialized by me
Reviewed-By: Amit Langote, Amit Khandekar, Andres Freund
Discussion:
https://postgr.es/m/CAJ3gD9fR0wRNeAE8VqffNTyONS_UfFPRpqxhnD9Q42vZB+Jvpg@mail.gmail.comhttps://postgr.es/m/e4f9d743-cd4b-efb0-7574-da21d86a7f36%40lab.ntt.co.jp
Backpatch: -
VACUUM and ANALYZE share similar logic when it comes to opening a
relation to work on in terms of how the relation is opened, in which
order locks are tried and how logs should be generated when something
does not work as expected.
This commit refactors things so as both use the same code path to handle
the way a relation is opened, so as the integration of new options
becomes easier.
Author: Michael Paquier
Reviewed-by: Nathan Bossart
Discussion: https://postgr.es/m/20180927075152.GT1659@paquier.xyz
Upcoming changes introduce further types of tuple table slots, in
preparation of making table storage pluggable. New storage methods
will have different representation of tuples, therefore the slot
accessor should refer explicitly to heap tuples.
Instead of just renaming the functions, split it into one function
that accepts heap tuples not residing in buffers, and one accepting
ones in buffers. Previously one function was used for both, but that
was a bit awkward already, and splitting will allow us to represent
slot types for tuples in buffers and normal memory separately.
This is split out from the patch introducing abstract slots, as this
largely consists out of mechanical changes.
Author: Ashutosh Bapat
Reviewed-By: Andres Freund
Discussion: https://postgr.es/m/20180220224318.gw4oe5jadhpmcdnm@alap3.anarazel.de
A caller of VACUUM can perform early lookup obtention which can cause
other sessions to block on the request done, causing potentially DOS
attacks as even a non-privileged user can attempt a vacuum fill of a
critical catalog table to block even all incoming connection attempts.
Contrary to TRUNCATE, a client could attempt a system-wide VACUUM after
building the list of relations to VACUUM, which can cause vacuum_rel()
or analyze_rel() to try to lock the relation but the operation would
just block. When the client specifies a list of relations and the
relation needs to be skipped, ownership checks are done when building
the list of relations to work on, preventing a later lock attempt.
vacuum_rel() already had the sanity checks needed, except that those
were applied too late. This commit refactors the code so as relation
skips are checked beforehand, making it safer to avoid too early locks,
for both manual VACUUM with and without a list of relations specified.
An isolation test is added emulating the fact that early locks do not
happen anymore, issuing a WARNING message earlier if the user calling
VACUUM is not a relation owner.
When a partitioned table is listed in a manual VACUUM or ANALYZE
command, its full list of partitions is fetched, all partitions get
added to the list to work on, and then each one of them is processed one
by one, with ownership checks happening at the later phase of
vacuum_rel() or analyze_rel(). Trying to do early ownership checks for
each partition is proving to be tedious as this would result in deadlock
risks with lock upgrades, and skipping all partitions if the listed
partitioned table is not owned would result in a behavior change
compared to how Postgres 10 has implemented vacuum for partitioned
tables. The original problem reported related to early lock queue for
critical relations is fixed anyway, so priority is given to avoiding a
backward-incompatible behavior.
Reported-by: Lloyd Albin, Jeremy Schneider
Author: Michael Paquier
Reviewed by: Nathan Bossart, Kyotaro Horiguchi
Discussion: https://postgr.es/m/152512087100.19803.12733865831237526317@wrigleys.postgresql.org
Discussion: https://postgr.es/m/20180812222142.GA6097@paquier.xyz
When it comes to SELECT ... FOR or LOCK, NOWAIT means to not wait for
something to happen, and issue an error. SKIP LOCKED means to not wait
for something to happen but to move on without issuing an error. The
internal option of autovacuum and autoanalyze mentioned above, used only
when wraparound is not involved was named NOWAIT, but behaves like SKIP
LOCKED which is confusing.
Author: Nathan Bossart
Discussion: https://postgr.es/m/20180307050345.GA3095@paquier.xyz
Traditionally, include/catalog/pg_foo.h contains extern declarations
for functions in backend/catalog/pg_foo.c, in addition to its function
as the authoritative definition of the pg_foo catalog's rowtype.
In some cases, we'd been forced to split out those extern declarations
into separate pg_foo_fn.h headers so that the catalog definitions
could be #include'd by frontend code. That problem is gone as of
commit 9c0a0de4c, so let's undo the splits to make things less
confusing.
Discussion: https://postgr.es/m/23690.1523031777@sss.pgh.pa.us
Previously, a value was included in the MCV list if its frequency was
25% larger than the estimated average frequency of all nonnull values
in the table. For uniform distributions, that can lead to values
being included in the MCV list and significantly overestimated on the
basis of relatively few (sometimes just 2) instances being seen in the
sample. For non-uniform distributions, it can lead to too few values
being included in the MCV list, since the overall average frequency
may be dominated by a small number of very common values, while the
remaining values may still have a large spread of frequencies, causing
both substantial overestimation and underestimation of the remaining
values. Furthermore, increasing the statistics target may have little
effect because the overall average frequency will remain relatively
unchanged.
Instead, populate the MCV list with the largest set of common values
that are statistically significantly more common than the average
frequency of the remaining values. This takes into account the
variance of the sample counts, which depends on the counts themselves
and on the proportion of the table that was sampled. As a result, it
constrains the relative standard error of estimates based on the
frequencies of values in the list, reducing the chances of too many
values being included. At the same time, it allows more values to be
included, since the MCVs need only be more common than the remaining
non-MCVs, rather than the overall average. Thus it tends to produce
fewer MCVs than the previous code for uniform distributions, and more
for non-uniform distributions, reducing estimation errors in both
cases. In addition, the algorithm responds better to increasing the
statistics target, allowing more values to be included in the MCV list
when more of the table is sampled.
Jeff Janes, substantially modified by me. Reviewed by John Naylor and
Tomas Vondra.
Discussion: https://postgr.es/m/CAMkU=1yvdGvW9TmiLAhz2erFnvnPFYHbOZuO+a=4DVkzpuQ2tw@mail.gmail.com
The existing logic for updating pg_class.reltuples trusted the sampling
results only for the pages ANALYZE actually visited, preferring to
believe the previous tuple density estimate for all the unvisited pages.
While there's some rationale for doing that for VACUUM (first that
VACUUM is likely to visit a very nonrandom subset of pages, and second
that we know for sure that the unvisited pages did not change), there's
no such rationale for ANALYZE: by assumption, it's looked at an unbiased
random sample of the table's pages. Furthermore, in a very large table
ANALYZE will have examined only a tiny fraction of the table's pages,
meaning it cannot slew the overall density estimate very far at all.
In a table that is physically growing, this causes reltuples to increase
nearly proportionally to the change in relpages, regardless of what is
actually happening in the table. This has been observed to cause reltuples
to become so much larger than reality that it effectively shuts off
autovacuum, whose threshold for doing anything is a fraction of reltuples.
(Getting to the point where that would happen seems to require some
additional, not well understood, conditions. But it's undeniable that if
reltuples is seriously off in a large table, ANALYZE alone will not fix it
in any reasonable number of iterations, especially not if the table is
continuing to grow.)
Hence, restrict the use of vac_estimate_reltuples() to VACUUM alone,
and in ANALYZE, just extrapolate from the sample pages on the assumption
that they provide an accurate model of the whole table. If, by very bad
luck, they don't, at least another ANALYZE will fix it; in the old logic
a single bad estimate could cause problems indefinitely.
In HEAD, let's remove vac_estimate_reltuples' is_analyze argument
altogether; it was never used for anything and now it's totally pointless.
But keep it in the back branches, in case any third-party code is calling
this function.
Per bug #15005. Back-patch to all supported branches.
David Gould, reviewed by Alexander Kuzmenkov, cosmetic changes by me
Discussion: https://postgr.es/m/20180117164916.3fdcf2e9@engels
Hopefully, the additional logging will help avoid confusion that
could otherwise result.
Nathan Bossart, reviewed by Michael Paquier, Fabrízio Mello, and me
Remove obsolete references to get_rel_oids(). Avoid listing specific
relkinds in the comments, since we seem unable to keep such things
in sync with the code, and it's not all that helpful anyhow.
Noted by Michael Paquier, though I rewrote the comments a bit more.
Discussion: https://postgr.es/m/CAB7nPqTWiN9zwKTaOrsnKiGDChqRt7C1+CiiDk4N4OMn92rs6A@mail.gmail.com
get_rel_oids used to not take any relation locks at all, but that stopped
being a good idea with commit 3c3bb9933, which inserted a syscache lookup
into the function. A concurrent DROP TABLE could now produce "cache lookup
failed", which we don't want to have happen in normal operation. The best
solution seems to be to transiently take a lock on the relation named by
the RangeVar (which also makes the result of RangeVarGetRelid a lot less
spongy). But we shouldn't hold the lock beyond this function, because we
don't want VACUUM to lock more than one table at a time. (That would not
be a big problem right now, but it will become one after the pending
feature patch to allow multiple tables to be named in VACUUM.)
In passing, adjust vacuum_rel and analyze_rel to document that we don't
trust the passed RangeVar to be accurate, and allow the RangeVar to
possibly be NULL --- which it is anyway for a whole-database VACUUM,
though we accidentally didn't crash for that case.
The passed RangeVar is in fact inaccurate when dealing with a child
partition, as of v10, and it has been wrong for a whole long time in the
case of vacuum_rel() recursing to a TOAST table. None of these things
present visible bugs up to now, because the passed RangeVar is in fact
only consulted for autovacuum logging, and in that particular context it's
always accurate because autovacuum doesn't let vacuum.c expand partitions
nor recurse to toast tables. Still, this seems like trouble waiting to
happen, so let's nail the door at least partly shut. (Further cleanup
is planned, in HEAD only, as part of the pending feature patch.)
Fix some sadly inaccurate/obsolete comments too. Back-patch to v10.
Michael Paquier and Tom Lane
Discussion: https://postgr.es/m/25023.1506107590@sss.pgh.pa.us
Previously, the code didn't think about this case and would just try to
analyze such a column twice. That would fail at the point of inserting
the second version of the pg_statistic row, with obscure error messsages
like "duplicate key value violates unique constraint" or "tuple already
updated by self", depending on context and PG version. We could allow
the case by ignoring duplicate column specifications, but it seems better
to reject it explicitly.
The bogus error messages seem like arguably a bug, so back-patch to
all supported versions.
Nathan Bossart, per a report from Michael Paquier, and whacked
around a bit by me.
Discussion: https://postgr.es/m/E061A8E3-5E3D-494D-94F0-E8A9B312BBFC@amazon.com
It is equivalent in ANSI C to write (*funcptr) () and funcptr(). These
two styles have been applied inconsistently. After discussion, we'll
use the more verbose style for plain function pointer variables, to make
it clear that it's a variable, and the shorter style when the function
pointer is in a struct (s.func() or s->func()), because then it's clear
that it's not a plain function name, and otherwise the excessive
punctuation makes some of those invocations hard to read.
Discussion: https://www.postgresql.org/message-id/f52c16db-14ed-757d-4b48-7ef360b1631d@2ndquadrant.com
This is a mechanical change in preparation for a later commit that
will change the layout of TupleDesc. Introducing a macro to abstract
the details of where attributes are stored will allow us to change
that in separate step and revise it in future.
Author: Thomas Munro, editorialized by Andres Freund
Reviewed-By: Andres Freund
Discussion: https://postgr.es/m/CAEepm=0ZtQ-SpsgCyzzYpsXS6e=kZWqk3g5Ygn3MDV7A8dabUA@mail.gmail.com
Don't move parenthesized lines to the left, even if that means they
flow past the right margin.
By default, BSD indent lines up statement continuation lines that are
within parentheses so that they start just to the right of the preceding
left parenthesis. However, traditionally, if that resulted in the
continuation line extending to the right of the desired right margin,
then indent would push it left just far enough to not overrun the margin,
if it could do so without making the continuation line start to the left of
the current statement indent. That makes for a weird mix of indentations
unless one has been completely rigid about never violating the 80-column
limit.
This behavior has been pretty universally panned by Postgres developers.
Hence, disable it with indent's new -lpl switch, so that parenthesized
lines are always lined up with the preceding left paren.
This patch is much less interesting than the first round of indent
changes, but also bulkier, so I thought it best to separate the effects.
Discussion: https://postgr.es/m/E1dAmxK-0006EE-1r@gemulon.postgresql.org
Discussion: https://postgr.es/m/30527.1495162840@sss.pgh.pa.us
Change pg_bsd_indent to follow upstream rules for placement of comments
to the right of code, and remove pgindent hack that caused comments
following #endif to not obey the general rule.
Commit e3860ffa4d wasn't actually using
the published version of pg_bsd_indent, but a hacked-up version that
tried to minimize the amount of movement of comments to the right of
code. The situation of interest is where such a comment has to be
moved to the right of its default placement at column 33 because there's
code there. BSD indent has always moved right in units of tab stops
in such cases --- but in the previous incarnation, indent was working
in 8-space tab stops, while now it knows we use 4-space tabs. So the
net result is that in about half the cases, such comments are placed
one tab stop left of before. This is better all around: it leaves
more room on the line for comment text, and it means that in such
cases the comment uniformly starts at the next 4-space tab stop after
the code, rather than sometimes one and sometimes two tabs after.
Also, ensure that comments following #endif are indented the same
as comments following other preprocessor commands such as #else.
That inconsistency turns out to have been self-inflicted damage
from a poorly-thought-through post-indent "fixup" in pgindent.
This patch is much less interesting than the first round of indent
changes, but also bulkier, so I thought it best to separate the effects.
Discussion: https://postgr.es/m/E1dAmxK-0006EE-1r@gemulon.postgresql.org
Discussion: https://postgr.es/m/30527.1495162840@sss.pgh.pa.us
This replaces the old, recursive tree-walk based evaluation, with
non-recursive, opcode dispatch based, expression evaluation.
Projection is now implemented as part of expression evaluation.
This both leads to significant performance improvements, and makes
future just-in-time compilation of expressions easier.
The speed gains primarily come from:
- non-recursive implementation reduces stack usage / overhead
- simple sub-expressions are implemented with a single jump, without
function calls
- sharing some state between different sub-expressions
- reduced amount of indirect/hard to predict memory accesses by laying
out operation metadata sequentially; including the avoidance of
nearly all of the previously used linked lists
- more code has been moved to expression initialization, avoiding
constant re-checks at evaluation time
Future just-in-time compilation (JIT) has become easier, as
demonstrated by released patches intended to be merged in a later
release, for primarily two reasons: Firstly, due to a stricter split
between expression initialization and evaluation, less code has to be
handled by the JIT. Secondly, due to the non-recursive nature of the
generated "instructions", less performance-critical code-paths can
easily be shared between interpreted and compiled evaluation.
The new framework allows for significant future optimizations. E.g.:
- basic infrastructure for to later reduce the per executor-startup
overhead of expression evaluation, by caching state in prepared
statements. That'd be helpful in OLTPish scenarios where
initialization overhead is measurable.
- optimizing the generated "code". A number of proposals for potential
work has already been made.
- optimizing the interpreter. Similarly a number of proposals have
been made here too.
The move of logic into the expression initialization step leads to some
backward-incompatible changes:
- Function permission checks are now done during expression
initialization, whereas previously they were done during
execution. In edge cases this can lead to errors being raised that
previously wouldn't have been, e.g. a NULL array being coerced to a
different array type previously didn't perform checks.
- The set of domain constraints to be checked, is now evaluated once
during expression initialization, previously it was re-built
every time a domain check was evaluated. For normal queries this
doesn't change much, but e.g. for plpgsql functions, which caches
ExprStates, the old set could stick around longer. The behavior
around might still change.
Author: Andres Freund, with significant changes by Tom Lane,
changes by Heikki Linnakangas
Reviewed-By: Tom Lane, Heikki Linnakangas
Discussion: https://postgr.es/m/20161206034955.bh33paeralxbtluv@alap3.anarazel.de
Add support for explicitly declared statistic objects (CREATE
STATISTICS), allowing collection of statistics on more complex
combinations that individual table columns. Companion commands DROP
STATISTICS and ALTER STATISTICS ... OWNER TO / SET SCHEMA / RENAME are
added too. All this DDL has been designed so that more statistic types
can be added later on, such as multivariate most-common-values and
multivariate histograms between columns of a single table, leaving room
for permitting columns on multiple tables, too, as well as expressions.
This commit only adds support for collection of n-distinct coefficient
on user-specified sets of columns in a single table. This is useful to
estimate number of distinct groups in GROUP BY and DISTINCT clauses;
estimation errors there can cause over-allocation of memory in hashed
aggregates, for instance, so it's a worthwhile problem to solve. A new
special pseudo-type pg_ndistinct is used.
(num-distinct estimation was deemed sufficiently useful by itself that
this is worthwhile even if no further statistic types are added
immediately; so much so that another version of essentially the same
functionality was submitted by Kyotaro Horiguchi:
https://postgr.es/m/20150828.173334.114731693.horiguchi.kyotaro@lab.ntt.co.jp
though this commit does not use that code.)
Author: Tomas Vondra. Some code rework by Álvaro.
Reviewed-by: Dean Rasheed, David Rowley, Kyotaro Horiguchi, Jeff Janes,
Ideriha Takeshi
Discussion: https://postgr.es/m/543AFA15.4080608@fuzzy.czhttps://postgr.es/m/20170320190220.ixlaueanxegqd5gr@alvherre.pgsql
Also, recursively perform VACUUM and ANALYZE on partitions when the
command is applied to a partitioned table. In passing, some related
documentation updates.
Amit Langote, reviewed by Michael Paquier, Ashutosh Bapat, and by me.
Discussion: http://postgr.es/m/47288cf1-f72c-dfc2-5ff0-4af962ae5c1b@lab.ntt.co.jp
Split the existing CatalogUpdateIndexes into two different routines,
CatalogTupleInsert and CatalogTupleUpdate, which do both the heap
insert/update plus the index update. This removes over 300 lines of
boilerplate code all over src/backend/catalog/ and src/backend/commands.
The resulting code is much more pleasing to the eye.
Also, by encapsulating what happens in detail during an UPDATE, this
facilitates the upcoming WARM patch, which is going to add a few more
lines to the update case making the boilerplate even more boring.
The original CatalogUpdateIndexes is removed; there was only one use
left, and since it's just three lines, we can as well expand it in place
there. We could keep it, but WARM is going to break all the UPDATE
out-of-core callsites anyway, so there seems to be no benefit in doing
so.
Author: Pavan Deolasee
Discussion: https://www.postgr.es/m/CABOikdOcFYSZ4vA2gYfs=M2cdXzXX4qGHeEiW3fu9PCfkHLa2A@mail.gmail.com
Table partitioning is like table inheritance and reuses much of the
existing infrastructure, but there are some important differences.
The parent is called a partitioned table and is always empty; it may
not have indexes or non-inherited constraints, since those make no
sense for a relation with no data of its own. The children are called
partitions and contain all of the actual data. Each partition has an
implicit partitioning constraint. Multiple inheritance is not
allowed, and partitioning and inheritance can't be mixed. Partitions
can't have extra columns and may not allow nulls unless the parent
does. Tuples inserted into the parent are automatically routed to the
correct partition, so tuple-routing ON INSERT triggers are not needed.
Tuple routing isn't yet supported for partitions which are foreign
tables, and it doesn't handle updates that cross partition boundaries.
Currently, tables can be range-partitioned or list-partitioned. List
partitioning is limited to a single column, but range partitioning can
involve multiple columns. A partitioning "column" can be an
expression.
Because table partitioning is less general than table inheritance, it
is hoped that it will be easier to reason about properties of
partitions, and therefore that this will serve as a better foundation
for a variety of possible optimizations, including query planner
optimizations. The tuple routing based which this patch does based on
the implicit partitioning constraints is an example of this, but it
seems likely that many other useful optimizations are also possible.
Amit Langote, reviewed and tested by Robert Haas, Ashutosh Bapat,
Amit Kapila, Rajkumar Raghuwanshi, Corey Huinker, Jaime Casanova,
Rushabh Lathia, Erik Rijkers, among others. Minor revisions by me.
I found that half a dozen (nearly 5%) of our AllocSetContextCreate calls
had typos in the context-sizing parameters. While none of these led to
especially significant problems, they did create minor inefficiencies,
and it's now clear that expecting people to copy-and-paste those calls
accurately is not a great idea. Let's reduce the risk of future errors
by introducing single macros that encapsulate the common use-cases.
Three such macros are enough to cover all but two special-purpose contexts;
those two calls can be left as-is, I think.
While this patch doesn't in itself improve matters for third-party
extensions, it doesn't break anything for them either, and they can
gradually adopt the simplified notation over time.
In passing, change TopMemoryContext to use the default allocation
parameters. Formerly it could only be extended 8K at a time. That was
probably reasonable when this code was written; but nowadays we create
many more contexts than we did then, so that it's not unusual to have a
couple hundred K in TopMemoryContext, even without considering various
dubious code that sticks other things there. There seems no good reason
not to let it use growing blocks like most other contexts.
Back-patch to 9.6, mostly because that's still close enough to HEAD that
it's easy to do so, and keeping the branches in sync can be expected to
avoid some future back-patching pain. The bugs fixed by these changes
don't seem to be significant enough to justify fixing them further back.
Discussion: <21072.1472321324@sss.pgh.pa.us>
If ANALYZE found no repeated non-null entries in its sample, it set the
column's stadistinct value to -1.0, intending to indicate that the entries
are all distinct. But what this value actually means is that the number
of distinct values is 100% of the table's rowcount, and thus it was
overestimating the number of distinct values by however many nulls there
are. This could lead to very poor selectivity estimates, as for example
in a recent report from Andreas Joseph Krogh. We should discount the
stadistinct value by whatever we've estimated the nulls fraction to be.
(That is what will happen if we choose to use a negative stadistinct for
a column that does have repeated entries, so this code path was just
inconsistent.)
In addition to fixing the stadistinct entries stored by several different
ANALYZE code paths, adjust the logic where get_variable_numdistinct()
forces an "all distinct" estimate on the basis of finding a relevant unique
index. Unique indexes don't reject nulls, so there's no reason to assume
that the null fraction doesn't apply.
Back-patch to all supported branches. Back-patching is a bit of a judgment
call, but this problem seems to affect only a few users (else we'd have
identified it long ago), and it's bad enough when it does happen that
destabilizing plan choices in a worse direction seems unlikely.
Patch by me, with documentation wording suggested by Dean Rasheed
Report: <VisenaEmail.26.df42f82acae38a58.156463942b8@tc7-visena>
Discussion: <16143.1470350371@sss.pgh.pa.us>
If we ANALYZE only selected columns of a table, we should not postpone
auto-analyze because of that; other columns may well still need stats
updates. As committed, the counter is left alone if a column list is
given, whether or not it includes all analyzable columns of the table.
Per complaint from Tomasz Ostrowski.
It's been like this a long time, so back-patch to all supported branches.
Report: <ef99c1bd-ff60-5f32-2733-c7b504eb960c@ato.waw.pl>
The reverted changes were intended to force a choice of whether any
newly-added BufferGetPage() calls needed to be accompanied by a
test of the snapshot age, to support the "snapshot too old"
feature. Such an accompanying test is needed in about 7% of the
cases, where the page is being used as part of a scan rather than
positioning for other purposes (such as DML or vacuuming). The
additional effort required for back-patching, and the doubt whether
the intended benefit would really be there, have indicated it is
best just to rely on developers to do the right thing based on
comments and existing usage, as we do with many other conventions.
This change should have little or no effect on generated executable
code.
Motivated by the back-patching pain of Tom Lane and Robert Haas
This patch is a no-op patch which is intended to reduce the chances
of failures of omission once the functional part of the "snapshot
too old" patch goes in. It adds parameters for snapshot, relation,
and an enum to specify whether the snapshot age check needs to be
done for the page at this point. This initial patch passes NULL
for the first two new parameters and BGP_NO_SNAPSHOT_TEST for the
third. The follow-on patch will change the places where the test
needs to be made.
Alex Shulgin complained that the underlying strategy wasn't all that
apparent, particularly not the fact that we intentionally have two
code paths depending on whether we think the column has a limited set
of possible values or not. Try to make it clearer.
On reflection, the pre-existing logic in ANALYZE is specifically meant to
compare the frequency of a candidate MCV against the estimated frequency of
a random distinct value across the whole table. The change to compare it
against the average frequency of values actually seen in the sample doesn't
seem very principled, and if anything it would make us less likely not more
likely to consider a value an MCV. So revert that, but keep the aspect of
considering only nonnull values, which definitely is correct.
In passing, rename the local variables in these stanzas to
"ndistinct_table", to avoid confusion with the "ndistinct" that appears at
an outer scope in compute_scalar_stats.
As with the previous patch, large numbers of null rows could skew this
calculation unfavorably, causing us to discard values that have a
legitimate claim to be MCVs, since our definition of MCV is that it's
most common among the non-null population of the column. Hence, make
the numerator of avgcount be the number of non-null sample values not
the number of sample rows; likewise for maxmincount in the
compute_scalar_stats variant.
Also, make the denominator be the number of distinct values actually
observed in the sample, rather than reversing it back out of the computed
stadistinct. This avoids depending on the accuracy of the Haas-Stokes
approximation, and really it's what we want anyway; the threshold should
depend only on what we see in the sample, not on what we extrapolate
about the contents of the whole column.
Alex Shulgin, reviewed by Tomas Vondra and myself
Previously, we included null rows in the values of n and N that went
into the formula, which amounts to considering null as a value in its
own right; but the d and f1 values do not include nulls. This is
inconsistent, and it contributes to significant underestimation of
ndistinct when the column is mostly nulls. In any case stadistinct
is defined as the number of distinct non-null values, so we should
exclude nulls when doing this computation.
This is an aboriginal bug in our application of the Haas-Stokes formula,
but we'll refrain from back-patching for fear of destabilizing plan
choices in released branches.
While at it, make the code a bit more readable by omitting unnecessary
casts and intermediate variables.
Observation and original patch by Tomas Vondra, adjusted to fix both
uses of the formula by Alex Shulgin, cosmetic improvements by me
The new bit indicates whether every tuple on the page is already frozen.
It is cleared only when the all-visible bit is cleared, and it can be
set only when we vacuum a page and find that every tuple on that page is
both visible to every transaction and in no need of any future
vacuuming.
A future commit will use this new bit to optimize away full-table scans
that would otherwise be triggered by XID wraparound considerations. A
page which is merely all-visible must still be scanned in that case, but
a page which is all-frozen need not be. This commit does not attempt
that optimization, although that optimization is the goal here. It
seems better to get the basic infrastructure in place first.
Per discussion, it's very desirable for pg_upgrade to automatically
migrate existing VM forks from the old format to the new format. That,
too, will be handled in a follow-on patch.
Masahiko Sawada, reviewed by Kyotaro Horiguchi, Fujii Masao, Amit
Kapila, Simon Riggs, Andres Freund, and others, and substantially
revised by me.
Previously, ANALYZE simply ignored columns of datatypes that have neither
a btree nor hash opclass (which means they have no recognized equality
operator). Without a notion of equality, we can't identify most-common
values nor estimate the number of distinct values. But we can still
count nulls and compute the average physical column width, and those
stats might be of value. Moreover there are some tools out there that
don't work so well if rows are missing from pg_statistic. So let's
add suitable logic for this case.
While this is arguably a bug fix, it also has the potential to change
query plans, and the gain seems not worth taking a risk of that in
stable branches. So back-patch into 9.5 but not further.
Oleksandr Shulgin, rewritten a bit by me.
Add a TABLESAMPLE clause to SELECT statements that allows
user to specify random BERNOULLI sampling or block level
SYSTEM sampling. Implementation allows for extensible
sampling functions to be written, using a standard API.
Basic version follows SQLStandard exactly. Usable
concrete use cases for the sampling API follow in later
commits.
Petr Jelinek
Reviewed by Michael Paquier and Simon Riggs
This is useful to control autovacuum log volume, for situations where
monitoring only a set of tables is necessary.
Author: Michael Paquier
Reviewed by: A team led by Naoya Anzai (also including Akira Kurosawa,
Taiki Kondo, Huong Dangminh), Fujii Masao.
Slow functions in index expressions might cause this loop to take long
enough to make it worth being cancellable. Probably it would be enough
to call CHECK_FOR_INTERRUPTS here, but for consistency with other
per-sample-row loops in this file, let's use vacuum_delay_point.
Report and patch by Jeff Janes. Back-patch to all supported branches.
Tom Lane
Andres Freund
Michael Paquier
Teodor Sigaev
Dean Rasheed
Bruce Momjian
Robert Haas
Peter Eisentraut
Alvaro Herrera
Simon Riggs
Kevin Grittner