When an ownership check on extended statistics object failed, the code
was calling aclcheck_error_type to report the failure, which is clearly
wrong, resulting in cache lookup errors. Fix by calling aclcheck_error.
This issue exists since the introduction of extended statistics, so
backpatch all the way back to PostgreSQL 10. It went unnoticed because
there were no tests triggering the error, so add one.
Reported-by: Mark Dilger
Backpatch-through: 10, where extended stats were introduced
Discussion: https://postgr.es/m/1F238937-7CC2-4703-A1B1-6DC225B8978A%40enterprisedb.com
Per our message style guidelines, for human consumption we quote
qualified names as a whole rather than each part separately; but commits
bc085205c8 introduced a deviation for extended statistics and
a4d75c86bf copied it. I don't agree with this policy applying to
names shown by psql, but that's a poor reason to deviate from the
practice only in two obscure corners, so make said corners use the same
style as everywhere else.
Backpatch to 14. The first of these is older, but I'm not sure we want
to destabilize the psql output in the older branches for such a small
thing.
Discussion: https://postgr.es/m/20210828181618.GS26465@telsasoft.com
Commit ad600bba04 added psql command \dX listing extended statistics
objects, but it failed to consider search_path when selecting the
elements so some of the returned elements might be invisible.
The visibility was already considered for tab completion (added by
commit d99d58cdc8), so adding it to the query is fairly simple.
Reported and fix by Justin Pryzby, regression tests by me. Backpatch
to PostgreSQL 14, where \dX was introduced.
Batchpatch-through: 14
Author: Justin Pryzby
Reviewed-by: Tatsuro Yamada
Discussion: https://postgr.es/m/c027a541-5856-75a5-0868-341301e1624b%40nttcom.co.jp_1
Most error messages about a relkind that was not supported or
appropriate for the command was of the pattern
"relation \"%s\" is not a table, foreign table, or materialized view"
This style can become verbose and tedious to maintain. Moreover, it's
not very helpful: If I'm trying to create a comment on a TOAST table,
which is not supported, then the information that I could have created
a comment on a materialized view is pointless.
Instead, write the primary error message shorter and saying more
directly that what was attempted is not possible. Then, in the detail
message, explain that the operation is not supported for the relkind
the object was. To simplify that, add a new function
errdetail_relkind_not_supported() that does this.
In passing, make use of RELKIND_HAS_STORAGE() where appropriate,
instead of listing out the relkinds individually.
Reviewed-by: Michael Paquier <michael@paquier.xyz>
Reviewed-by: Alvaro Herrera <alvherre@alvh.no-ip.org>
Discussion: https://www.postgresql.org/message-id/flat/dc35a398-37d0-75ce-07ea-1dd71d98f8ec@2ndquadrant.com
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
The tests used string concatenation to test statistics on expressions,
but that made the tests locale-dependent, e.g. because the ordering of
'11' and '1X' depends on the collation. This affected both the estimated
and actual row couts, breaking some of the tests.
Fixed by replacing the string concatenation with upper() function call,
so that the text values contain only digits.
Discussion: https://postgr.es/m/b650920b-2767-fbc3-c87a-cb8b5d693cbf%40enterprisedb.com
Allow defining extended statistics on expressions, not just just on
simple column references. With this commit, expressions are supported
by all existing extended statistics kinds, improving the same types of
estimates. A simple example may look like this:
CREATE TABLE t (a int);
CREATE STATISTICS s ON mod(a,10), mod(a,20) FROM t;
ANALYZE t;
The collected statistics are useful e.g. to estimate queries with those
expressions in WHERE or GROUP BY clauses:
SELECT * FROM t WHERE mod(a,10) = 0 AND mod(a,20) = 0;
SELECT 1 FROM t GROUP BY mod(a,10), mod(a,20);
This introduces new internal statistics kind 'e' (expressions) which is
built automatically when the statistics object definition includes any
expressions. This represents single-expression statistics, as if there
was an expression index (but without the index maintenance overhead).
The statistics is stored in pg_statistics_ext_data as an array of
composite types, which is possible thanks to 79f6a942bd.
CREATE STATISTICS allows building statistics on a single expression, in
which case in which case it's not possible to specify statistics kinds.
A new system view pg_stats_ext_exprs can be used to display expression
statistics, similarly to pg_stats and pg_stats_ext views.
ALTER TABLE ... ALTER COLUMN ... TYPE now treats indexes the same way it
treats indexes, i.e. it drops and recreates the statistics. This means
all statistics are reset, and we no longer try to preserve at least the
functional dependencies. This should not be a major issue in practice,
as the functional dependencies actually rely on per-column statistics,
which were always reset anyway.
Author: Tomas Vondra
Reviewed-by: Justin Pryzby, Dean Rasheed, Zhihong Yu
Discussion: https://postgr.es/m/ad7891d2-e90c-b446-9fe2-7419143847d7%40enterprisedb.com
The regression tests of extended statistics were taking a fair amount of
time, due to using fairly large data sets with a couple thousand rows.
So far this was fine, but with tests for statistics on expressions the
duration would get a bit excessive. So reduce the size of some of the
tests that will be used to test expressions, to keep the duration under
control. Done in a separate commit before adding the statistics on
expressions, to make it clear which estimates are expected to change.
Author: Tomas Vondra
Discussion: https://postgr.es/m/ad7891d2-e90c-b446-9fe2-7419143847d7%40enterprisedb.com
When estimating the number of groups using extended statistics, the code
was discarding information about system attributes. This led to strange
situation that
SELECT 1 FROM t GROUP BY ctid;
could have produced higher estimate (equal to pg_class.reltuples) than
SELECT 1 FROM t GROUP BY a, b, ctid;
with extended statistics on (a,b). Fixed by retaining information about
the system attribute.
Backpatch all the way to 10, where extended statistics were introduced.
Author: Tomas Vondra
Backpatch-through: 10
The new command lists extended statistics objects. All past releases
with extended statistics are supported.
This is a simplified version of commit 891a1d0bca, which had to be
reverted due to not considering pg_statistic_ext_data is not accessible
by regular users. Fields requiring access to this catalog were removed.
It's possible to add them, but it'll require changes to core.
Author: Tatsuro Yamada
Reviewed-by: Julien Rouhaud, Alvaro Herrera, Tomas Vondra, Noriyoshi Shinoda
Discussion: https://postgr.es/m/c027a541-5856-75a5-0868-341301e1624b%40nttcom.co.jp_1
The new command lists extended statistics objects, possibly with their
sizes. All past releases with extended statistics are supported.
Author: Tatsuro Yamada
Reviewed-by: Julien Rouhaud, Alvaro Herrera, Tomas Vondra
Discussion: https://postgr.es/m/c027a541-5856-75a5-0868-341301e1624b%40nttcom.co.jp_1
Add a check that CREATE STATISTICS does not add extended statistics on
system catalogs, similarly to indexes etc. It can be overriden using
the allow_system_table_mods GUC.
This bug exists since 7b504eb282, adding the extended statistics, so
backpatch all the way back to PostgreSQL 10.
Author: Tomas Vondra
Reported-by: Dean Rasheed
Backpatch-through: 10
Discussion: https://postgr.es/m/CAEZATCXAPrrOKwEsyZKQ4uzzJQWBCt6QAvOcgqRGdWwT1zb%2BrQ%40mail.gmail.com
Formerly, extended statistics only handled clauses that were
RestrictInfos. However, the restrictinfo machinery doesn't create
sub-AND RestrictInfos for AND clauses underneath OR clauses.
Therefore teach extended statistics to handle bare AND clauses,
looking for compatible RestrictInfo clauses underneath them.
Dean Rasheed, reviewed by Tomas Vondra.
Discussion: https://postgr.es/m/CAEZATCW=J65GUFm50RcPv-iASnS2mTXQbr=CfBvWRVhFLJ_fWA@mail.gmail.com
When estimating an OR clause using multiple extended statistics
objects, treat the estimates for each set of clauses for each
statistics object as independent of one another. The overlap estimates
produced for each statistics object do not apply to clauses covered by
other statistics objects.
Dean Rasheed, reviewed by Tomas Vondra.
Discussion: https://postgr.es/m/CAEZATCW=J65GUFm50RcPv-iASnS2mTXQbr=CfBvWRVhFLJ_fWA@mail.gmail.com
Formerly we only applied extended statistics to an OR clause as part
of the clauselist_selectivity() code path for an OR clause appearing
in an implicitly-ANDed list of clauses. This meant that it could only
use extended statistics if all sub-clauses of the OR clause were
covered by a single extended statistics object.
Instead, teach clause_selectivity() how to apply extended statistics
to an OR clause by handling its ORed list of sub-clauses in a similar
manner to an implicitly-ANDed list of sub-clauses, but with different
combination rules. This allows one or more extended statistics objects
to be used to estimate all or part of the list of sub-clauses. Any
remaining sub-clauses are then treated as if they are independent.
Additionally, to avoid double-application of extended statistics, this
introduces "extended" versions of clause_selectivity() and
clauselist_selectivity(), which include an option to ignore extended
statistics. This replaces the old clauselist_selectivity_simple()
function which failed to completely ignore extended statistics when
called from the extended statistics code.
A known limitation of the current infrastructure is that an AND clause
under an OR clause is not treated as compatible with extended
statistics (because we don't build RestrictInfos for such sub-AND
clauses). Thus, for example, "(a=1 AND b=1) OR (a=2 AND b=2)" will
currently be treated as two independent AND clauses (each of which may
be estimated using extended statistics), but extended statistics will
not currently be used to account for any possible overlap between
those clauses. Improving that is left as a task for the future.
Original patch by Tomas Vondra, with additional improvements by me.
Discussion: https://postgr.es/m/20200113230008.g67iyk4cs3xbnjju@development
The stats target can be set since commit d06215d03, but wasn't shown by
psql.
Author: Justin Pryzby <justin@telsasoft.com>
Discussion: https://postgr.es/m/20200831050047.GG5450@telsasoft.com
Reviewed-by: Georgios Kokolatos <gkokolatos@protonmail.com>
Reviewed-by: Tatsuro Yamada <tatsuro.yamada.tf@nttcom.co.jp>
The stats_ext test is not expecting that autovacuum will touch
any of its tables; an expectation falsified by commit b07642dbc.
Although I'm suspicious that there's something else going on that
makes extended stats estimates not 100% reproducible, it's pretty
easy to demonstrate that there are places in this test that fail
if an autovacuum updates the table's stats unexpectedly.
Hence, revert the band-aid changes made by 2dc16efed and 24566b359
in favor of summarily disabling autovacuum for all the tables that
this test checks estimated rowcounts for.
Also remove an evidently obsolete comment at the head of the test.
Discussion: https://postgr.es/m/15012.1585623298@sss.pgh.pa.us
Following up on 2dc16efed, petalura has suffered some additional
failures in stats_ext which again appear to be around the timing of an
autovacuum during the test, causing instability in the row estimates.
Again, let's fix this by explicitly performing a VACUUM on the table
and not leave it to happen by chance of an autovacuum pass.
Discussion: https://postgr.es/m/CAApHDvok5hmXr%2BbUbJe7%2B2sQzWo4B_QzSk7RKFR9fP6BjYXx5g%40mail.gmail.com
b07642dbc added code to trigger autovacuums based on the number of
inserts into a table. This seems to have caused some regression test
results to destabilize. I suspect this is due to autovacuum triggering a
vacuum sometime after the test's ANALYZE run and perhaps reltuples is
ending up being set to a slightly different value as a result.
Attempt to resolve this by running a VACUUM ANALYZE on the affected table
instead of just ANALYZE. pg_class.reltuples will still get set to whatever
ANALYZE chooses but we should no longer get the proceeding autovacuum
overriding that.
The overhead this adds to each test's runtime seems small enough not to
worry about. I measure 3-4% on stats_ext and can't measure any change in
partition_aggregate.
I'm unable to recreate the issue locally, so this is a bit of a blind
fix.
Discussion: https://postgr.es/m/CAApHDvpWmpqYrKwwDQyeDq8dAyK7GMNaxDhrG69CkSuXoEg%2BVg%40mail.gmail.com
Formerly we applied a functional dependency "a => b with dependency
degree f" using the formula
P(a,b) = P(a) * [f + (1-f)*P(b)]
This leads to the possibility that the combined selectivity P(a,b)
could exceed P(b), which is not ideal. The addition of support for IN
and OR clauses (commits 8f321bd16c and ccaa3569f5) would seem to make
this more likely, since the user-supplied values in such clauses are
not necessarily compatible with the functional dependency.
Mitigate this by using the formula
P(a,b) = f * Min(P(a), P(b)) + (1-f) * P(a) * P(b)
instead, which guarantees that the combined selectivity is less than
each column's individual selectivity. Logically, this is modifies the
part of the formula that accounts for dependent rows to handle cases
where P(a) > P(b), whilst not changing the second term which accounts
for independent rows.
Additionally, this refactors the way that functional dependencies are
applied, so now dependencies_clauselist_selectivity() estimates both
the implying clauses and the implied clauses for each functional
dependency (formerly only the implied clauses were estimated), and now
all clauses for each attribute are taken into account (formerly only
one clause for each implied attribute was estimated). This removes the
previously built-in assumption that only equality clauses will be
seen, which is no longer true, and opens up the possibility of
applying functional dependencies to more general clauses.
Patch by me, reviewed by Tomas Vondra.
Discussion: https://postgr.es/m/CAEZATCXaNFZyOhR4XXAfkvj1tibRBEjje6ZbXwqWUB_tqbH%3Drw%40mail.gmail.com
Discussion: https://postgr.es/m/20200318002946.6dvblukm3cfmgir2%40development
Since commit 8f321bd16c functional dependencies can handle IN clauses,
which however introduced a possible (and surprising) inconsistency,
because IN clauses may be expressed as an OR clause, which are still
considered incompatible. For example
a IN (1, 2, 3)
may be rewritten as
(a = 1 OR a = 2 OR a = 3)
The IN clause will work fine with functional dependencies, but the OR
clause will force the estimation to fall back to plain per-column
estimates, possibly introducing significant estimation errors.
This commit recognizes OR clauses equivalent to an IN clause (when all
arugments are compatible and reference the same attribute) as a special
case, compatible with functional dependencies. This allows applying
functional dependencies, just like for IN clauses.
This does not eliminate the difference in estimating the clause itself,
i.e. IN clause and OR clause still use different formulas. It would be
possible to change that (for these special OR clauses), but that's not
really about extended statistics - it was always like this. Moreover the
errors are usually much smaller compared to ignoring dependencies.
Author: Tomas Vondra
Reviewed-by: Dean Rasheed
Discussion: https://www.postgresql.org/message-id/flat/13902317.Eha0YfKkKy%40pierred-pdoc
The regression tests for extended statistics were not testing a couple
of important cases for the MCV lists:
* IS NOT NULL clauses - We did have queries with IS NULL clauses, but
not the negative case.
* clauses with variable on the right - All the clauses had the Var on
the left, i.e. (Var op Const), so this adds (Const op Var) too.
* columns with fixed-length types passed by reference - All columns
were using either by-value or varlena types, so add a test with
UUID columns too. This matters for (de)serialization.
* NULL-only dimension - When one of the columns contains only NULL
values, we treat it a a special case during (de)serialization.
* arrays containing NULL - When the constant parameter contains NULL
value, we need to handle it correctly during estimation, for all
IN, ANY and ALL clauses.
Discussion: https://www.postgresql.org/message-id/flat/20200113230008.g67iyk4cs3xbnjju@development
Author: Tomas Vondra
The regression tests for functional dependencies were only using clauses
of the form (Var op Const), i.e. with Var on the left side. This adds
a couple of queries with Var on the right, to test other code paths.
It also prints one of the functional dependencies, to test the data type
output function. The functional dependencies are "perfect" with degree
of 1.0 so this should be stable.
Discussion: https://www.postgresql.org/message-id/flat/20200113230008.g67iyk4cs3xbnjju@development
Author: Tomas Vondra
Commit 8f321bd16c added support for estimating ScalarArrayOpExpr clauses
(IN/ANY) clauses using functional dependencies. There's no good reason
not to support estimation of these clauses using multi-variate MCV lists
too, so this commits implements that. That makes the behavior consistent
and MCV lists can estimate all variants (ANY/ALL, inequalities, ...).
Author: Tomas Vondra
Review: Dean Rasheed
Discussion: https://www.postgresql.org/message-id/flat/13902317.Eha0YfKkKy%40pierred-pdoc
Until now functional dependencies supported only simple equality clauses
and clauses that can be trivially translated to equalities. This commit
allows estimation of some ScalarArrayOpExpr (IN/ANY) clauses.
For IN clauses we can do this thanks to using operator with equality
semantics, which means an IN clause
WHERE c IN (1, 2, ..., N)
can be translated to
WHERE (c = 1 OR c = 2 OR ... OR c = N)
IN clauses are now considered compatible with functional dependencies,
and rely on the same assumption of consistency of queries with data
(which is an assumption we already used for simple equality clauses).
This applies also to ALL clauses with an equality operator, which can be
considered equivalent to IN clause.
ALL clauses are still considered incompatible, although there's some
discussion about maybe relaxing this in the future.
Author: Pierre Ducroquet
Reviewed-by: Tomas Vondra, Dean Rasheed
Discussion: https://www.postgresql.org/message-id/flat/13902317.Eha0YfKkKy%40pierred-pdoc
Until now we've only used a single multivariate MCV list per relation,
covering the largest number of clauses. So for example given a query
SELECT * FROM t WHERE a = 1 AND b =1 AND c = 1 AND d = 1
and extended statistics on (a,b) and (c,d), we'd only pick and use one
of them. This commit improves this by repeatedly picking and applying
the best statistics (matching the largest number of remaining clauses)
until no additional statistics is applicable.
This greedy algorithm is simple, but may not be optimal. A different
choice of statistics may leave fewer clauses unestimated and/or give
better estimates for some other reason.
This can however happen only when there are overlapping statistics, and
selecting one makes it impossible to use the other. E.g. with statistics
on (a,b), (c,d), (b,c,d), we may pick either (a,b) and (c,d) or (b,c,d).
But it's not clear which option is the best one.
We however assume cases like this are rare, and the easiest solution is
to define statistics covering the whole group of correlated columns. In
the future we might support overlapping stats, using some of the clauses
as conditions (in conditional probability sense).
Author: Tomas Vondra
Reviewed-by: Mark Dilger, Kyotaro Horiguchi
Discussion: https://postgr.es/m/20191028152048.jc6pqv5hb7j77ocp@development
When considering functional dependencies during selectivity estimation,
it's not necessary to bother with selecting the best extended statistic
object and then use just dependencies from it. We can simply consider
all applicable functional dependencies at once.
This means we need to deserialie all (applicable) dependencies before
applying them to the clauses. This is a bit more expensive than picking
the best statistics and deserializing dependencies for it. To minimize
the additional cost, we ignore statistics that are not applicable.
Author: Tomas Vondra
Reviewed-by: Mark Dilger
Discussion: https://postgr.es/m/20191028152048.jc6pqv5hb7j77ocp@development
When picking the best extended statistics object for a list of clauses,
it's not enough to look at attnums extracted from the clause list as a
whole. Consider for example this query with OR clauses:
SELECT * FROM t WHERE (t.a = 1) OR (t.b = 1) OR (t.c = 1)
with a statistics defined on columns (a,b). Relying on attnums extracted
from the whole OR clause, we'd consider the statistics usable. That does
not work, as we see the conditions as a single OR-clause, referencing an
attribute not covered by the statistic, leading to empty list of clauses
to be estimated using the statistics and an assert failure.
This changes choose_best_statistics to check which clauses are actually
covered, and only using attributes from the fully covered ones. For the
previous example this means the statistics object will not be considered
as compatible with the OR-clause.
Backpatch to 12, where MCVs were introduced. The issue does not affect
older versions because functional dependencies don't handle OR clauses.
Author: Tomas Vondra
Reviewed-by: Dean Rasheed
Reported-By: Manuel Rigger
Discussion: https://postgr.es/m/CA+u7OA7H5rcE2=8f263w4NZD6ipO_XOrYB816nuLXbmSTH9pQQ@mail.gmail.com
Backpatch-through: 12
When estimating number of distinct groups, we failed to ignore system
attributes when matching the group expressions to mvdistinct stats,
causing failures like
ERROR: negative bitmapset member not allowed
Fix that by simply skipping anything that is not a regular attribute.
Backpatch to PostgreSQL 10, where the extended stats were introduced.
Bug: #16111
Reported-by: Tuomas Leikola
Author: Tomas Vondra
Backpatch-through: 10
Discussion: https://postgr.es/m/16111-687799584c3a7e73@postgresql.org
Commit d7f8d26d9 added new tests to the stats_ext regression test that
included creating a view in the public schema, without realising that
the stats_ext test runs in the same parallel group as the rules test,
which makes doing that unsafe.
This led to intermittent failures of the rules test on the buildfarm,
although I wasn't able to reproduce that locally. Fix by creating the
view in a different schema.
Tomas Vondra and Dean Rasheed, report and diagnosis by Thomas Munro.
Discussion: https://postgr.es/m/CA+hUKGKX9hFZrYA7rQzAMRE07L4hziCc-nO_b3taJpiuKyLLxg@mail.gmail.com
When building statistics, we need to decide how many rows to sample and
how accurate the resulting statistics should be. Until now, it was not
possible to explicitly define statistics target for extended statistics
objects, the value was always computed from the per-attribute targets
with a fallback to the system-wide default statistics target.
That's a bit inconvenient, as it ties together the statistics target set
for per-column and extended statistics. In some cases it may be useful
to require larger sample / higher accuracy for extended statics (or the
other way around), but with this approach that's not possible.
So this commit introduces a new command, allowing to specify statistics
target for individual extended statistics objects, overriding the value
derived from per-attribute targets (and the system default).
ALTER STATISTICS stat_name SET STATISTICS target_value;
When determining statistics target for an extended statistics object we
first look at this explicitly set value. When this value is -1, we fall
back to the old formula, looking at the per-attribute targets first and
then the system default. This means the behavior is backwards compatible
with older PostgreSQL releases.
Author: Tomas Vondra
Discussion: https://postgr.es/m/20190618213357.vli3i23vpkset2xd@development
Reviewed-by: Kirk Jamison, Dean Rasheed
When performing ANALYZE on inheritance trees, we collect two samples for
each relation - one for the relation alone, and one for the inheritance
subtree (relation and its child relations). And then we build statistics
on each sample, so for each relation we get two sets of statistics.
For regular (per-column) statistics this works fine, because the catalog
includes a flag differentiating statistics built from those two samples.
But we don't have such flag in the extended statistics catalogs, and we
ended up updating the same row twice, triggering this error:
ERROR: tuple already updated by self
The simplest solution is to disable extended statistics on inheritance
trees, which is what this commit is doing. In the future we may need to
do something similar to per-column statistics, but that requires adding a
flag to the catalog - and that's not backpatchable. Moreover, the current
selectivity estimation code only works with individual relations, so
building statistics on inheritance trees would be pointless anyway.
Author: Tomas Vondra
Backpatch-to: 10-
Discussion: https://postgr.es/m/20190618231233.GA27470@telsasoft.com
Reported-by: Justin Pryzby
There were two issues in how the extended statistics handled NULL values
in opclauses. Firstly, the code was oblivious to the possibility that
Const may be NULL (constisnull=true) in which case the constvalue is
undefined. We need to treat this as a mismatch, and not call the proc.
Secondly, the MCV item itself may contain NULL values too - the code
already did check that, and updated the match bitmap accordingly, but
failed to ensure we won't call the operator procedure anyway. It did
work for AND-clauses, because in that case false in the bitmap stops
evaluation of further clauses. But for OR-clauses ir was not easy to
get incorrect estimates or even trigger a crash.
This fixes both issues by extending the existing check so that it looks
at constisnull too, and making sure it skips calling the procedure.
Discussion: https://postgr.es/m/8736jdhbhc.fsf%40ansel.ydns.eu
The function pg_mcv_list_items() returns values stored in MCV items. The
items may contain columns with different data types, so the function was
generating text array-like representation, but in an ad-hoc way without
properly escaping various characters etc.
Fixed by simply building a text[] array, which also makes it easier to
use from queries etc.
Requires changes to pg_proc entry, so bump catversion.
Backpatch to 12, where multi-column MCV lists were introduced.
Author: Tomas Vondra
Reviewed-by: Dean Rasheed
Discussion: https://postgr.es/m/20190618205920.qtlzcu73whfpfqne@development
Commit d7f8d26d9 added a test case that created a user, but forgot
to drop it again. This is no good; for one thing, it causes repeated
"make installcheck" runs to fail.
The multivariate MCV estimation code may run user-defined operators on
the values in the MCV list, which means that those operators may
potentially leak the values from the MCV list. Guard against leaking
data to unprivileged users by checking that the user has SELECT
privileges on the table or all of the columns referred to by the
statistics.
Additionally, if there are any securityQuals on the RTE (either due to
RLS policies on the table, or accessing the table via a security
barrier view), not all rows may be visible to the current user, even
if they have table or column privileges. Thus we further insist that
the operator be leakproof in this case.
Dean Rasheed, reviewed by Tomas Vondra.
Discussion: https://postgr.es/m/CAEZATCUhT9rt7Ui=Vdx4N==VV5XOK5dsXfnGgVOz_JhAicB=ZA@mail.gmail.com
Since extended statistic got introduced in PostgreSQL 10, there was a
single catalog pg_statistic_ext storing both the definitions and built
statistic. That's however problematic when a user is supposed to have
access only to the definitions, but not to user data.
Consider for example pg_dump on a database with RLS enabled - if the
pg_statistic_ext catalog respects RLS (which it should, if it contains
user data), pg_dump would not see any records and the result would not
define any extended statistics. That would be a surprising behavior.
Until now this was not a pressing issue, because the existing types of
extended statistic (functional dependencies and ndistinct coefficients)
do not include any user data directly. This changed with introduction
of MCV lists, which do include most common combinations of values.
The easiest way to fix this is to split the pg_statistic_ext catalog
into two - one for definitions, one for the built statistic values.
The new catalog is called pg_statistic_ext_data, and we're maintaining
a 1:1 relationship with the old catalog - either there are matching
records in both catalogs, or neither of them.
Bumped CATVERSION due to changing system catalog definitions.
Author: Dean Rasheed, with improvements by me
Reviewed-by: Dean Rasheed, John Naylor
Discussion: https://postgr.es/m/CAEZATCUhT9rt7Ui%3DVdx4N%3D%3DVV5XOK5dsXfnGgVOz_JhAicB%3DZA%40mail.gmail.com
The regression tests added in commit 7300a69950 test cardinality
estimates using a function that extracts the interesting pieces
from the EXPLAIN output, instead of testing the whole plan. That
seems both easier to understand and less fragile, so this applies
the same approach to pre-existing tests of ndistinct coefficients
and functional dependencies.
Discussion: https://postgr.es/m/dfdac334-9cf2-2597-fb27-f0fb3753f435@2ndquadrant.com
The memcpy() was copying type OIDs in the wrong direction, so the
deserialized MCV list always had them as 0. This is mostly harmless
except when printing the data in pg_mcv_list_items(), in which case
it reported
ERROR: cache lookup failed for type 0
Also added a simple regression test for pg_mcv_list_items() function,
printing a single-item MCV list.
Reported-By: Dean Rasheed
Discussion: https://postgr.es/m/CAEZATCX6T0iDTTZrqyec4Cd6b4yuL7euu4=rQRXaVBAVrUi1Cg@mail.gmail.com
Introduce a third extended statistic type, supported by the CREATE
STATISTICS command - MCV lists, a generalization of the statistic
already built and used for individual columns.
Compared to the already supported types (n-distinct coefficients and
functional dependencies), MCV lists are more complex, include column
values and allow estimation of much wider range of common clauses
(equality and inequality conditions, IS NULL, IS NOT NULL etc.).
Similarly to the other types, a new pseudo-type (pg_mcv_list) is used.
Author: Tomas Vondra
Reviewed-by: Dean Rasheed, David Rowley, Mark Dilger, Alvaro Herrera
Discussion: https://postgr.es/m/dfdac334-9cf2-2597-fb27-f0fb3753f435@2ndquadrant.com
Now that the ordering of DROP messages ought to be stable everywhere,
we should not need these kluges of hiding DETAIL output just to avoid
unstable ordering. Hiding it's not great for test coverage, so
let's undo that where possible.
In a small number of places, it's necessary to leave it in, for
example because the output might include a variable pg_temp_nnn
schema name. I also left things alone in places where the details
would depend on other regression test scripts, e.g. plpython_drop.sql.
Perhaps buildfarm experience will show this to be a bad idea,
but if so I'd like to know why.
Discussion: https://postgr.es/m/E1h6eep-0001Mw-Vd@gemulon.postgresql.org
DROP CASCADE doesn't currently promise to visit dependent objects in
a fixed order, so when the regression tests use it, we typically need
to suppress the details of which objects get dropped in order to have
predictable test output. Traditionally we've done that by setting
client_min_messages higher than NOTICE, but there's a better way:
we can "\set VERBOSITY terse" in psql. That suppresses the DETAIL
message with the object list, but we still get the basic notice telling
how many objects were dropped. So at least the test case can verify
that the expected number of objects were dropped.
The VERBOSITY method was already in use in a few places, but run
around and use it wherever it makes sense.
Discussion: https://postgr.es/m/10766.1501608885@sss.pgh.pa.us
I misplaced the IF NOT EXISTS clause in commit 7b504eb282, before the
word STATISTICS. Put it where it belongs.
Patch written independently by Amit Langote and myself. I adopted his
submitted test case with a slight edit also.
Reported-by: Bruno Wolff III
Discussion: https://postgr.es/m/20170621004237.GB8337@wolff.to
ALTER COLUMN TYPE on a column used by a statistics object fails since
commit 928c4de30, because the relevant switch in ATExecAlterColumnType
is unprepared for columns to have dependencies from OCLASS_STATISTIC_EXT
objects.
Although the existing types of extended statistics don't actually need us
to do any work for a column type change, it seems completely indefensible
that that assumption is hidden behind the failure of an unrelated module
to contain any code for the case. Hence, create and call an API function
in statscmds.c where the assumption can be explained, and where we could
add code to deal with the problem when it inevitably becomes real.
Also, the reason this wasn't handled before, neither for extended stats
nor for the last half-dozen new OCLASS kinds :-(, is that the default:
in that switch suppresses compiler warnings, allowing people to miss the
need to consider it when adding an OCLASS. We don't really need a default
because surely getObjectClass should only return valid values of the enum;
so remove it, and add the missed OCLASS entries where they should be.
Discussion: https://postgr.es/m/20170512221010.nglatgt5azzdxjlj@alvherre.pgsql
Consistently refer to such an entry as a "statistics object", not just
"statistics" or "extended statistics". Previously we had a mismash of
terms, accompanied by utter confusion as to whether the term was
singular or plural. That's not only grating (at least to the ear of
a native English speaker) but could be outright misleading, eg in error
messages that seemed to be referring to multiple objects where only one
could be meant.
This commit fixes the code and a lot of comments (though I may have
missed a few). I also renamed two new SQL functions,
pg_get_statisticsextdef -> pg_get_statisticsobjdef
pg_statistic_ext_is_visible -> pg_statistics_obj_is_visible
to conform better with this terminology.
I have not touched the SGML docs other than fixing those function
names; the docs certainly need work but it seems like a separable task.
Discussion: https://postgr.es/m/22676.1494557205@sss.pgh.pa.us
A stats object ought to have a dependency on each individual column
it reads, not the entire table. Doing this honestly lets us get rid
of the hard-wired logic in RemoveStatisticsExt, which seems to have
been misguidedly modeled on RemoveStatistics; and it will be far easier
to extend to multiple tables later.
Also, add overlooked dependency on owner, and make the dependency on
schema be NORMAL like every other such dependency.
There remains some unfinished work here, which is to allow statistics
objects to be extension members. That takes more effort than just
adding the dependency call, though, so I left it out for now.
initdb forced because this changes the set of pg_depend records that
should exist for a statistics object.
Discussion: https://postgr.es/m/22676.1494557205@sss.pgh.pa.us
Tomas Vondra
Alvaro Herrera
Peter Eisentraut
Dean Rasheed
Heikki Linnakangas
Tom Lane
David Rowley
Noah Misch
Peter Eisentraut