In commit 19a541143a09c067 I did not make PathTarget a subtype of Node,
and embedded a RelOptInfo's reltarget directly into it rather than having
a separately-allocated Node. In hindsight that was misguided
micro-optimization, enabled by the fact that at that point we didn't have
any Paths with custom PathTargets. Now that PathTarget processing has
been fleshed out some more, it's easier to see that it's better to have
PathTarget as an indepedent Node type, even if it does cost us one more
palloc to create a RelOptInfo. So change it while we still can.
This commit just changes the representation, without doing anything more
interesting than that.
It is frequently useful for volatile, set-returning, or expensive functions
in a SELECT's targetlist to be postponed till after ORDER BY and LIMIT are
done. Otherwise, the functions might be executed for every row of the
table despite the presence of LIMIT, and/or be executed in an unexpected
order. For example, in
SELECT x, nextval('seq') FROM tab ORDER BY x LIMIT 10;
it's probably desirable that the nextval() values are ordered the same
as x, and that nextval() is not run more than 10 times.
In the past, Postgres was inconsistent in this area: you would get the
desirable behavior if the ordering were performed via an indexscan, but
not if it had to be done by an explicit sort step. Getting the desired
behavior reliably required contortions like
SELECT x, nextval('seq')
FROM (SELECT x FROM tab ORDER BY x) ss LIMIT 10;
This patch conditionally postpones evaluation of pure-output target
expressions (that is, those that are not used as DISTINCT, ORDER BY, or
GROUP BY columns) so that they effectively occur after sorting, even if an
explicit sort step is necessary. Volatile expressions and set-returning
expressions are always postponed, so as to provide consistent semantics.
Expensive expressions (costing more than 10 times typical operator cost,
which by default would include any user-defined function) are postponed
if there is a LIMIT or if there are expressions that must be postponed.
We could be more aggressive and postpone any nontrivial expression, but
there are costs associated with doing so: it requires an extra Result plan
node which adds some overhead, and postponement changes the volume of data
going through the sort step, perhaps for the worse. Since we tend not to
have very good estimates of the output width of nontrivial expressions,
it's hard to have much confidence in our ability to predict whether
postponement would increase or decrease the cost of the sort; therefore
this patch doesn't attempt to make decisions conditionally on that.
Between these factors and a general desire not to change query behavior
when there's not a demonstrable benefit, it seems best to be conservative
about applying postponement. We might tweak the decision rules in the
future, though.
Konstantin Knizhnik, heavily rewritten by me
Teach make_group_input_target() and make_window_input_target() to work
entirely with the PathTarget representation of tlists, rather than
constructing a tlist and immediately deconstructing it into PathTarget
format. In itself this only saves a few palloc's; the bigger picture is
that it opens the door for sharing cost_qual_eval work across all of
planner.c's constructions of PathTargets. I'll come back to that later.
In support of this, flesh out tlist.c's infrastructure for PathTargets
a bit more.
All along, this function should have treated WindowFuncs in a manner
similar to Aggrefs, ie with an option whether or not to recurse into them.
By not considering the case, it was always recursing, which is OK for most
callers (although I suspect that the case in prepare_sort_from_pathkeys
might represent a bug). But now we need return-without-recursing behavior
as well. There are also more than a few callers that should never see a
WindowFunc, and now we'll get some error checking on that.
In commit 1d97c19a0f748e94 and later c1d9579dd8bf3c92, we extended
pull_var_clause's API by adding enum-type arguments. That's sort of a pain
to maintain, though, because it means every time we add a new behavior we
must touch every last one of the call sites, even if there's a reasonable
default behavior that most of them could use. Let's switch over to using a
bitmask of flags, instead; that seems more maintainable and might save a
nanosecond or two as well. This commit changes no behavior in itself,
though I'm going to follow it up with one that does add a new behavior.
In passing, remove flatten_tlist(), which has not been used since 9.1
and would otherwise need the same API changes.
Removing these enums means that optimizer/tlist.h no longer needs to
depend on optimizer/var.h. Changing that caused a number of C files to
need addition of #include "optimizer/var.h" (probably we can thank old
runs of pgrminclude for that); but on balance it seems like a good change
anyway.
Refactor so that the internal APIs in planner.c deal in PathTargets not
targetlists, and establish a more regular structure for deriving the
targets needed for successive steps.
There is more that could be done here; calculating the eval costs of each
successive target independently is both inefficient and wrong in detail,
since we won't actually recompute values available from the input node's
tlist. But it's no worse than what happened before the pathification
rewrite. In any case this seems like a good starting point for considering
how to handle Konstantin Knizhnik's function-evaluation-postponement patch.
Instead of having planner.c compute a groupColIdx array and store it in
GroupingSetsPaths, make create_groupingsets_plan() find the grouping
columns by searching in the child plan node's tlist. Although that's
probably a bit slower for create_groupingsets_plan(), it's more like
the way every other plan node type does this, and it provides positive
confirmation that we know which child output columns we're supposed to be
grouping on. (Indeed, looking at this now, I'm not at all sure that it
wasn't broken before, because create_groupingsets_plan() isn't demanding
an exact tlist match from its child node.) Also, this allows substantial
simplification in planner.c, because it no longer needs to compute the
groupColIdx array at all; no other cases were using it.
I'd intended to put off this refactoring until later (like 9.7), but
in view of the likely bug fix and the need to rationalize planner.c's
tlist handling so we can do something sane with Konstantin Knizhnik's
function-evaluation-postponement patch, I think it can't wait.
This patch removes some redundant cost calculations that I left for later
cleanup in commit 3fc6e2d7f5b652b4. There's now a uniform policy that the
make_foo() convenience functions don't do any cost calculations. Most of
their callers copy costs from the source Path node, and for those that
don't, the calculation in the make_foo() function wasn't necessarily right
anyhow. (make_result() was particularly a mess, as it was serving multiple
callers using cost calcs designed for only the first one or two that had
ever existed.) Aside from saving a few cycles, this ensures that what
EXPLAIN prints matches the costs we used for planning purposes. It does
not change any planner decisions, since the decisions are already made.
I've been saying we needed to do this for more than five years, and here it
finally is. This patch removes the ever-growing tangle of spaghetti logic
that grouping_planner() used to use to try to identify the best plan for
post-scan/join query steps. Now, there is (nearly) independent
consideration of each execution step, and entirely separate construction of
Paths to represent each of the possible ways to do that step. We choose
the best Path or set of Paths using the same add_path() logic that's been
used inside query_planner() for years.
In addition, this patch removes the old restriction that subquery_planner()
could return only a single Plan. It now returns a RelOptInfo containing a
set of Paths, just as query_planner() does, and the parent query level can
use each of those Paths as the basis of a SubqueryScanPath at its level.
This allows finding some optimizations that we missed before, wherein a
subquery was capable of returning presorted data and thereby avoiding a
sort in the parent level, making the overall cost cheaper even though
delivering sorted output was not the cheapest plan for the subquery in
isolation. (A couple of regression test outputs change in consequence of
that. However, there is very little change in visible planner behavior
overall, because the point of this patch is not to get immediate planning
benefits but to create the infrastructure for future improvements.)
There is a great deal left to do here. This patch unblocks a lot of
planner work that was basically impractical in the old code structure,
such as allowing FDWs to implement remote aggregation, or rewriting
plan_set_operations() to allow consideration of multiple implementation
orders for set operations. (The latter will likely require a full
rewrite of plan_set_operations(); what I've done here is only to fix it
to return Paths not Plans.) I have also left unfinished some localized
refactoring in createplan.c and planner.c, because it was not necessary
to get this patch to a working state.
Thanks to Robert Haas, David Rowley, and Amit Kapila for review.
Up to now, there's been an assumption that all Paths for a given relation
compute the same output column set (targetlist). However, there are good
reasons to remove that assumption. For example, an indexscan on an
expression index might be able to return the value of an expensive function
"for free". While we have the ability to generate such a plan today in
simple cases, we don't have a way to model that it's cheaper than a plan
that computes the function from scratch, nor a way to create such a plan
in join cases (where the function computation would normally happen at
the topmost join node). Also, we need this so that we can have Paths
representing post-scan/join steps, where the targetlist may well change
from one step to the next. Therefore, invent a "struct PathTarget"
representing the columns we expect a plan step to emit. It's convenient
to include the output tuple width and tlist evaluation cost in this struct,
and there will likely be additional fields in future.
While Path nodes that actually do have custom outputs will need their own
PathTargets, it will still be true that most Paths for a given relation
will compute the same tlist. To reduce the overhead added by this patch,
keep a "default PathTarget" in RelOptInfo, and allow Paths that compute
that column set to just point to their parent RelOptInfo's reltarget.
(In the patch as committed, actually every Path is like that, since we
do not yet have any cases of custom PathTargets.)
I took this opportunity to provide some more-honest costing of
PlaceHolderVar evaluation. Up to now, the assumption that "scan/join
reltargetlists have cost zero" was applied not only to Vars, where it's
reasonable, but also PlaceHolderVars where it isn't. Now, we add the eval
cost of a PlaceHolderVar's expression to the first plan level where it can
be computed, by including it in the PathTarget cost field and adding that
to the cost estimates for Paths. This isn't perfect yet but it's much
better than before, and there is a way forward to improve it more. This
costing change affects the join order chosen for a couple of the regression
tests, changing expected row ordering.
If a GROUP BY clause includes all columns of a non-deferred primary key,
as well as other columns of the same relation, those other columns are
redundant and can be dropped from the grouping; the pkey is enough to
ensure that each row of the table corresponds to a separate group.
Getting rid of the excess columns will reduce the cost of the sorting or
hashing needed to implement GROUP BY, and can indeed remove the need for
a sort step altogether.
This seems worth testing for since many query authors are not aware of
the GROUP-BY-primary-key exception to the rule about queries not being
allowed to reference non-grouped-by columns in their targetlists or
HAVING clauses. Thus, redundant GROUP BY items are not uncommon. Also,
we can make the test pretty cheap in most queries where it won't help
by not looking up a rel's primary key until we've found that at least
two of its columns are in GROUP BY.
David Rowley, reviewed by Julien Rouhaud
In 61444bfb we started to allow HAVING clauses to be fully pushed down
into WHERE, even when grouping sets are in use. That turns out not to
work correctly, because grouping sets can "produce" NULLs, meaning that
filtering in WHERE and HAVING can have different results, even when no
aggregates or volatile functions are involved.
Instead only allow pushdown of empty grouping sets.
It'd be nice to do better, but the exact mechanics of deciding which
cases are safe are still being debated. It's important to give correct
results till we find a good solution, and such a solution might not be
appropriate for backpatching anyway.
Bug: #13863
Reported-By: 'wrb'
Diagnosed-By: Dean Rasheed
Author: Andrew Gierth
Reviewed-By: Dean Rasheed and Andres Freund
Discussion: 20160113183558.12989.56904@wrigleys.postgresql.org
Backpatch: 9.5, where grouping sets were introduced
When force_parallel_mode = true, we enable the parallel mode restrictions
for all queries for which this is believed to be safe. For the subset of
those queries believed to be safe to run entirely within a worker, we spin
up a worker and run the query there instead of running it in the
original process. When force_parallel_mode = regress, make additional
changes to allow the regression tests to run cleanly even though parallel
workers have been injected under the hood.
Taken together, this facilitates both better user testing and better
regression testing of the parallelism code.
Robert Haas, with help from Amit Kapila and Rushabh Lathia.
Previously, the foreign join pushdown infrastructure left the question
of security entirely up to individual FDWs, but it would be easy for
a foreign data wrapper to inadvertently open up subtle security holes
that way. So, make it the core code's job to determine which user
mapping OID is relevant, and don't attempt join pushdown unless it's
the same for all relevant relations.
Per a suggestion from Tom Lane. Shigeru Hanada and Ashutosh Bapat,
reviewed by Etsuro Fujita and KaiGai Kohei, with some further
changes by me.
Aggregate nodes now have two new modes: a "partial" mode where they
output the unfinalized transition state, and a "finalize" mode where
they accept unfinalized transition states rather than individual
values as input.
These new modes are not used anywhere yet, but they will be necessary
for parallel aggregation. The infrastructure also figures to be
useful for cases where we want to aggregate local data and remote
data via the FDW interface, and want to bring back partial aggregates
from the remote side that can then be combined with locally generated
partial aggregates to produce the final value. It may also be useful
even when neither FDWs nor parallelism are in play, as explained in
the comments in nodeAgg.c.
David Rowley and Simon Riggs, reviewed by KaiGai Kohei, Heikki
Linnakangas, Haribabu Kommi, and me.
There's no good reason for stomping on the input data; it makes the logic
in this function no simpler, in fact probably the reverse. And it makes
it impossible to separate path generation from plan generation, as I'm
working towards doing; that will require more than one traversal of these
lists.
Improve comments and make it a shade less messy. I think we might want
to move all of this somewhere else later, but it needs to be more
readable first.
In passing, re-pgindent the file, affecting some recently-added comments
concerning parallel query planning.
Once upon a time it was necessary for grouping_planner() to determine
the tlist it wanted from the scan/join plan subtree before it called
query_planner(), because query_planner() would actually make a Plan using
that. But we refactored things a long time ago to delay construction of
the Plan tree till later, so there's no need to build that tlist until
(and indeed unless) we're ready to plaster it onto the Plan. The only
thing query_planner() cares about is what Vars are going to be needed for
the tlist, and it can perfectly well get that by looking at the real tlist
rather than some masticated version.
Well, actually, there is one minor glitch in that argument, which is that
make_subplanTargetList also adds Vars appearing only in HAVING to the
tlist it produces. So now we have to account for HAVING explicitly in
build_base_rel_tlists. But that just adds a few lines of code, and
I doubt it moves the needle much on processing time; we might be doing
pull_var_clause() twice on the havingQual, but before we had it scanning
dummy tlist entries instead.
This is a very small down payment on rationalizing grouping_planner
enough so it can be refactored.
We carry around information about if a given query has row security or
not to allow the plancache to use that information to invalidate a
planned query in the event that the environment changes.
Previously, the flag of one of the subqueries was simply being copied
into place to indicate if the query overall included RLS components.
That's wrong as we need the global OR of all subqueries. Fix by
changing the code to match how fireRIRules works, which is results
in OR'ing all of the flags.
Noted by Tom.
Back-patch to 9.5 where RLS was introduced.
I originally modeled this data structure on SpecialJoinInfo, but after
commit acfcd45cacb6df23 that looks like a pretty poor decision.
All we really need is relid sets identifying laterally-referenced rels;
and most of the time, what we want to know about includes indirect lateral
references, a case the LateralJoinInfo data was unsuited to compute with
any efficiency. The previous commit redefined RelOptInfo.lateral_relids
as the transitive closure of lateral references, so that it easily supports
checking indirect references. For the places where we really do want just
direct references, add a new RelOptInfo field direct_lateral_relids, which
is easily set up as a copy of lateral_relids before we perform the
transitive closure calculation. Then we can just drop lateral_info_list
and LateralJoinInfo and the supporting code. This makes the planner's
handling of lateral references noticeably more efficient, and shorter too.
Such a change can't be back-patched into stable branches for fear of
breaking extensions that might be looking at the planner's data structures;
but it seems not too late to push it into 9.5, so I've done so.
Add a new flag, consider_parallel, to each RelOptInfo, indicating
whether a plan for that relation could conceivably be run inside of
a parallel worker. Right now, we're pretty conservative: for example,
it might be possible to defer applying a parallel-restricted qual
in a worker, and later do it in the leader, but right now we just
don't try to parallelize access to that relation. That's probably
the right decision in most cases, anyway.
Using the new flag, generate parallel sequential scan plans for plain
baserels, meaning that we now have parallel sequential scan in
PostgreSQL. The logic here is pretty unsophisticated right now: the
costing model probably isn't right in detail, and we can't push joins
beneath Gather nodes, so the number of plans that can actually benefit
from this is pretty limited right now. Lots more work is needed.
Nevertheless, it seems time to enable this functionality so that all
this code can actually be tested easily by users and developers.
Note that, if you wish to test this functionality, it will be
necessary to set max_parallel_degree to a value greater than the
default of 0. Once a few more loose ends have been tidied up here, we
might want to consider changing the default value of this GUC, but
I'm leaving it alone for now.
Along the way, fix a bug in cost_gather: the previous coding thought
that a Gather node's transfer overhead should be costed on the basis of
the relation size rather than the number of tuples that actually need
to be passed off to the leader.
Patch by me, reviewed in earlier versions by Amit Kapila.
In addition, this path fills in a number of missing bits and pieces in
the parallel infrastructure. Paths and plans now have a parallel_aware
flag indicating whether whatever parallel-aware logic they have should
be engaged. It is believed that we will need this flag for a number of
path/plan types, not just sequential scans, which is why the flag is
generic rather than part of the SeqScan structures specifically.
Also, execParallel.c now gives parallel nodes a chance to initialize
their PlanState nodes from the DSM during parallel worker startup.
Amit Kapila, with a fair amount of adjustment by me. Review of previous
patch versions by Haribabu Kommi and others.
In order for this to be safe, the code which hands true serializability
will need to taught that the SIRead locks taken by a parallel worker
pertain to the same transaction as those taken by the parallel leader.
Some further changes may be needed as well. Until the necessary
adaptations are made, don't generate parallel plans in serializable
mode, and if a previously-generated parallel plan is used after
serializable mode has been activated, run it serially.
This fixes a bug in commit 7aea8e4f2daa4b39ca9d1309a0c4aadb0f7ed81b.
This code provides infrastructure for a parallel leader to start up
parallel workers to execute subtrees of the plan tree being executed
in the master. User-supplied parameters from ParamListInfo are passed
down, but PARAM_EXEC parameters are not. Various other constructs,
such as initplans, subplans, and CTEs, are also not currently shared.
Nevertheless, there's enough here to support a basic implementation of
parallel query, and we can lift some of the current restrictions as
needed.
Amit Kapila and Robert Haas
Commit 924bcf4f16d54c55310b28f77686608684734f42 introduced a framework
for parallel computation in PostgreSQL that makes most but not all
built-in functions safe to execute in parallel mode. In order to have
parallel query, we'll need to be able to determine whether that query
contains functions (either built-in or user-defined) that cannot be
safely executed in parallel mode. This requires those functions to be
labeled, so this patch introduces an infrastructure for that. Some
functions currently labeled as safe may need to be revised depending on
how pending issues related to heavyweight locking under paralllelism
are resolved.
Parallel plans can't be used except for the case where the query will
run to completion. If portal execution were suspended, the parallel
mode restrictions would need to remain in effect during that time, but
that might make other queries fail. Therefore, this patch introduces
a framework that enables consideration of parallel plans only when it
is known that the plan will be run to completion. This probably needs
some refinement; for example, at bind time, we do not know whether a
query run via the extended protocol will be execution to completion or
run with a limited fetch count. Having the client indicate its
intentions at bind time would constitute a wire protocol break. Some
contexts in which parallel mode would be safe are not adjusted by this
patch; the default is not to try parallel plans except from call sites
that have been updated to say that such plans are OK.
This commit doesn't introduce any parallel paths or plans; it just
provides a way to determine whether they could potentially be used.
I'm committing it on the theory that the remaining parallel sequential
scan patches will also get committed to this release, hopefully in the
not-too-distant future.
Robert Haas and Amit Kapila. Reviewed (in earlier versions) by Noah
Misch.
Until now we computed these Param ID sets at the end of subquery_planner,
but that approach depends on subquery_planner returning a concrete Plan
tree. We would like to switch over to returning one or more Paths for a
subquery, and in that representation the necessary details aren't fully
fleshed out (not to mention that we don't really want to do this work for
Paths that end up getting discarded). Hence, refactor so that we can
compute the param ID sets at the end of planning, just before
set_plan_references is run.
The main change necessary to make this work is that we need to capture
the set of outer-level Param IDs available to the current query level
before exiting subquery_planner, since the outer levels' plan_params lists
are transient. (That's not going to pose a problem for returning Paths,
since all the work involved in producing that data is part of expression
preprocessing, which will continue to happen before Paths are produced.)
On the plus side, this change gets rid of several existing kluges.
Eventually I'd like to get rid of SS_finalize_plan altogether in favor of
doing this work during set_plan_references, but that will require some
complex rejiggering because SS_finalize_plan needs to visit subplans and
initplans before the main plan. So leave that idea for another day.
Although I think on all modern machines floating division by zero
results in Infinity not SIGFPE, we still don't want infinities
running around in the planner's costing estimates; too much risk
of that leading to insane behavior.
grouping_planner() failed to consider the possibility that final_rel
might be known dummy and hence have zero rowcount. (I wonder if it
would be better to set a rows estimate of 1 for dummy relations?
But at least in the back branches, changing this convention seems
like a bad idea, so I'll leave that for another day.)
Make certain that get_variable_numdistinct() produces a nonzero result.
The case that can be shown to be broken is with stadistinct < 0.0 and
small ntuples; we did not prevent the result from rounding to zero.
For good luck I applied clamp_row_est() to all the nonconstant return
values.
In ExecChooseHashTableSize(), Assert that we compute positive nbuckets
and nbatch. I know of no reason to think this isn't the case, but it
seems like a good safety check.
Per reports from Piotr Stefaniak. Back-patch to all active branches.
Previously we disallowed pushing down quals to WHERE in the presence of
grouping sets. That's overly restrictive.
We now instead copy quals to WHERE if applicable, leaving the
one in HAVING in place. That's because, at that stage of the planning
process, it's nontrivial to determine if it's safe to remove the one in
HAVING.
Author: Andrew Gierth
Discussion: 874mkt3l59.fsf@news-spur.riddles.org.uk
Backpatch: 9.5, where grouping sets were introduced. This isn't exactly
a bugfix, but it seems better to keep the branches in sync at this point.
The previous coding frequently failed to fail because for one it's
unusual to have rollup clauses with one column, and for another
sometimes the wrong mapping didn't cause obvious problems.
Author: Jeevan Chalke
Reviewed-By: Andrew Gierth
Discussion: CAM2+6=W=9=hQOipH0HAPbkun3Z3TFWij_EiHue0_6UX=oR=1kw@mail.gmail.com
Backpatch: 9.5, where grouping sets were introduced
The original implementation of TABLESAMPLE modeled the tablesample method
API on index access methods, which wasn't a good choice because, without
specialized DDL commands, there's no way to build an extension that can
implement a TSM. (Raw inserts into system catalogs are not an acceptable
thing to do, because we can't undo them during DROP EXTENSION, nor will
pg_upgrade behave sanely.) Instead adopt an API more like procedural
language handlers or foreign data wrappers, wherein the only SQL-level
support object needed is a single handler function identified by having
a special return type. This lets us get rid of the supporting catalog
altogether, so that no custom DDL support is needed for the feature.
Adjust the API so that it can support non-constant tablesample arguments
(the original coding assumed we could evaluate the argument expressions at
ExecInitSampleScan time, which is undesirable even if it weren't outright
unsafe), and discourage sampling methods from looking at invisible tuples.
Make sure that the BERNOULLI and SYSTEM methods are genuinely repeatable
within and across queries, as required by the SQL standard, and deal more
honestly with methods that can't support that requirement.
Make a full code-review pass over the tablesample additions, and fix
assorted bugs, omissions, infelicities, and cosmetic issues (such as
failure to put the added code stanzas in a consistent ordering).
Improve EXPLAIN's output of tablesample plans, too.
Back-patch to 9.5 so that we don't have to support the original API
in production.
Commit c03ad5602f529787968fa3201b35c119bbc6d782 introduced a planner
performance regression for UPDATE/DELETE on large inheritance sets.
It required copying the append_rel_list (which is of size proportional to
the number of inherited tables) once for each inherited table, thus
resulting in O(N^2) time and memory consumption. While it's difficult to
avoid that in general, the extra work only has to be done for
append_rel_list entries that actually reference subquery RTEs, which
inheritance-set entries will not. So we can buy back essentially all of
the loss in cases without subqueries in FROM; and even for those, the added
work is mainly proportional to the number of UNION ALL subqueries.
Back-patch to 9.2, like the previous commit.
Tom Lane and Dean Rasheed, per a complaint from Thomas Munro.
Fix some places where pgindent did silly stuff, often because project
style wasn't followed to begin with. (I've not touched the atomics
headers, though.)
Previously, INSERT with ON CONFLICT DO UPDATE specified used a new
command tag -- UPSERT. It was introduced out of concern that INSERT as
a command tag would be a misrepresentation for ON CONFLICT DO UPDATE, as
some affected rows may actually have been updated.
Alvaro Herrera noticed that the implementation of that new command tag
was incomplete; in subsequent discussion we concluded that having it
doesn't provide benefits that are in line with the compatibility breaks
it requires.
Catversion bump due to the removal of PlannedStmt->isUpsert.
Author: Peter Geoghegan
Discussion: 20150520215816.GI5885@postgresql.org
This SQL standard functionality allows to aggregate data by different
GROUP BY clauses at once. Each grouping set returns rows with columns
grouped by in other sets set to NULL.
This could previously be achieved by doing each grouping as a separate
query, conjoined by UNION ALLs. Besides being considerably more concise,
grouping sets will in many cases be faster, requiring only one scan over
the underlying data.
The current implementation of grouping sets only supports using sorting
for input. Individual sets that share a sort order are computed in one
pass. If there are sets that don't share a sort order, additional sort &
aggregation steps are performed. These additional passes are sourced by
the previous sort step; thus avoiding repeated scans of the source data.
The code is structured in a way that adding support for purely using
hash aggregation or a mix of hashing and sorting is possible. Sorting
was chosen to be supported first, as it is the most generic method of
implementation.
Instead of, as in an earlier versions of the patch, representing the
chain of sort and aggregation steps as full blown planner and executor
nodes, all but the first sort are performed inside the aggregation node
itself. This avoids the need to do some unusual gymnastics to handle
having to return aggregated and non-aggregated tuples from underlying
nodes, as well as having to shut down underlying nodes early to limit
memory usage. The optimizer still builds Sort/Agg node to describe each
phase, but they're not part of the plan tree, but instead additional
data for the aggregation node. They're a convenient and preexisting way
to describe aggregation and sorting. The first (and possibly only) sort
step is still performed as a separate execution step. That retains
similarity with existing group by plans, makes rescans fairly simple,
avoids very deep plans (leading to slow explains) and easily allows to
avoid the sorting step if the underlying data is sorted by other means.
A somewhat ugly side of this patch is having to deal with a grammar
ambiguity between the new CUBE keyword and the cube extension/functions
named cube (and rollup). To avoid breaking existing deployments of the
cube extension it has not been renamed, neither has cube been made a
reserved keyword. Instead precedence hacking is used to make GROUP BY
cube(..) refer to the CUBE grouping sets feature, and not the function
cube(). To actually group by a function cube(), unlikely as that might
be, the function name has to be quoted.
Needs a catversion bump because stored rules may change.
Author: Andrew Gierth and Atri Sharma, with contributions from Andres Freund
Reviewed-By: Andres Freund, Noah Misch, Tom Lane, Svenne Krap, Tomas
Vondra, Erik Rijkers, Marti Raudsepp, Pavel Stehule
Discussion: CAOeZVidmVRe2jU6aMk_5qkxnB7dfmPROzM7Ur8JPW5j8Y5X-Lw@mail.gmail.com
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
Previously, FDWs could only do "early row locking", that is lock a row as
soon as it's fetched, even though local restriction/join conditions might
discard the row later. This patch adds callbacks that allow FDWs to do
late locking in the same way that it's done for regular tables.
To make use of this feature, an FDW must support the "ctid" column as a
unique row identifier. Currently, since ctid has to be of type TID,
the feature is of limited use, though in principle it could be used by
postgres_fdw. We may eventually allow FDWs to specify another data type
for ctid, which would make it possible for more FDWs to use this feature.
This commit does not modify postgres_fdw to use late locking. We've
tested some prototype code for that, but it's not in committable shape,
and besides it's quite unclear whether it actually makes sense to do late
locking against a remote server. The extra round trips required are likely
to outweigh any benefit from improved concurrency.
Etsuro Fujita, reviewed by Ashutosh Bapat, and hacked up a lot by me
The newly added ON CONFLICT clause allows to specify an alternative to
raising a unique or exclusion constraint violation error when inserting.
ON CONFLICT refers to constraints that can either be specified using a
inference clause (by specifying the columns of a unique constraint) or
by naming a unique or exclusion constraint. DO NOTHING avoids the
constraint violation, without touching the pre-existing row. DO UPDATE
SET ... [WHERE ...] updates the pre-existing tuple, and has access to
both the tuple proposed for insertion and the existing tuple; the
optional WHERE clause can be used to prevent an update from being
executed. The UPDATE SET and WHERE clauses have access to the tuple
proposed for insertion using the "magic" EXCLUDED alias, and to the
pre-existing tuple using the table name or its alias.
This feature is often referred to as upsert.
This is implemented using a new infrastructure called "speculative
insertion". It is an optimistic variant of regular insertion that first
does a pre-check for existing tuples and then attempts an insert. If a
violating tuple was inserted concurrently, the speculatively inserted
tuple is deleted and a new attempt is made. If the pre-check finds a
matching tuple the alternative DO NOTHING or DO UPDATE action is taken.
If the insertion succeeds without detecting a conflict, the tuple is
deemed inserted.
To handle the possible ambiguity between the excluded alias and a table
named excluded, and for convenience with long relation names, INSERT
INTO now can alias its target table.
Bumps catversion as stored rules change.
Author: Peter Geoghegan, with significant contributions from Heikki
Linnakangas and Andres Freund. Testing infrastructure by Jeff Janes.
Reviewed-By: Heikki Linnakangas, Andres Freund, Robert Haas, Simon Riggs,
Dean Rasheed, Stephen Frost and many others.
In prepend_row_security_policies(), defaultDeny was always true, so if
there were any hook policies, the RLS policies on the table would just
get discarded. Fixed to start off with defaultDeny as false and then
properly set later if we detect that only the default deny policy exists
for the internal policies.
The infinite recursion detection in fireRIRrules() didn't properly
manage the activeRIRs list in the case of WCOs, so it would incorrectly
report infinite recusion if the same relation with RLS appeared more
than once in the rtable, for example "UPDATE t ... FROM t ...".
Further, the RLS expansion code in fireRIRrules() was handling RLS in
the main loop through the rtable, which lead to RTEs being visited twice
if they contained sublink subqueries, which
prepend_row_security_policies() attempted to handle by exiting early if
the RTE already had securityQuals. That doesn't work, however, since
if the query involved a security barrier view on top of a table with
RLS, the RTE would already have securityQuals (from the view) by the
time fireRIRrules() was invoked, and so the table's RLS policies would
be ignored. This is fixed in fireRIRrules() by handling RLS in a
separate loop at the end, after dealing with any other sublink
subqueries, thus ensuring that each RTE is only visited once for RLS
expansion.
The inheritance planner code didn't correctly handle non-target
relations with RLS, which would get turned into subqueries during
planning. Thus an update of the form "UPDATE t1 ... FROM t2 ..." where
t1 has inheritance and t2 has RLS quals would fail. Fix by making sure
to copy in and update the securityQuals when they exist for non-target
relations.
process_policies() was adding WCOs to non-target relations, which is
unnecessary, and could lead to a lot of wasted time in the rewriter and
the planner. Fix by only adding WCO policies when working on the result
relation. Also in process_policies, we should be copying the USING
policies to the WITH CHECK policies on a per-policy basis, fix by moving
the copying up into the per-policy loop.
Lastly, as noted by Dean, we were simply adding policies returned by the
hook provided to the list of quals being AND'd, meaning that they would
actually restrict records returned and there was no option to have
internal policies and hook-based policies work together permissively (as
all internal policies currently work). Instead, explicitly add support
for both permissive and restrictive policies by having a hook for each
and combining the results appropriately. To ensure this is all done
correctly, add a new test module (test_rls_hooks) to test the various
combinations of internal, permissive, and restrictive hook policies.
Largely from Dean Rasheed (thanks!):
CAEZATCVmFUfUOwwhnBTcgi6AquyjQ0-1fyKd0T3xBWJvn+xsFA@mail.gmail.com
Author: Dean Rasheed, though I added the new hooks and test module.
Foreign tables can now be inheritance children, or parents. Much of the
system was already ready for this, but we had to fix a few things of
course, mostly in the area of planner and executor handling of row locks.
As side effects of this, allow foreign tables to have NOT VALID CHECK
constraints (and hence to accept ALTER ... VALIDATE CONSTRAINT), and to
accept ALTER SET STORAGE and ALTER SET WITH/WITHOUT OIDS. Continuing to
disallow these things would've required bizarre and inconsistent special
cases in inheritance behavior. Since foreign tables don't enforce CHECK
constraints anyway, a NOT VALID one is a complete no-op, but that doesn't
mean we shouldn't allow it. And it's possible that some FDWs might have
use for SET STORAGE or SET WITH OIDS, though doubtless they will be no-ops
for most.
An additional change in support of this is that when a ModifyTable node
has multiple target tables, they will all now be explicitly identified
in EXPLAIN output, for example:
Update on pt1 (cost=0.00..321.05 rows=3541 width=46)
Update on pt1
Foreign Update on ft1
Foreign Update on ft2
Update on child3
-> Seq Scan on pt1 (cost=0.00..0.00 rows=1 width=46)
-> Foreign Scan on ft1 (cost=100.00..148.03 rows=1170 width=46)
-> Foreign Scan on ft2 (cost=100.00..148.03 rows=1170 width=46)
-> Seq Scan on child3 (cost=0.00..25.00 rows=1200 width=46)
This was done mainly to provide an unambiguous place to attach "Remote SQL"
fields, but it is useful for inherited updates even when no foreign tables
are involved.
Shigeru Hanada and Etsuro Fujita, reviewed by Ashutosh Bapat and Kyotaro
Horiguchi, some additional hacking by me
This patch fixes two inadequacies of the PlanRowMark representation.
First, that the original LockingClauseStrength isn't stored (and cannot be
inferred for foreign tables, which always get ROW_MARK_COPY). Since some
PlanRowMarks are created out of whole cloth and don't actually have an
ancestral RowMarkClause, this requires adding a dummy LCS_NONE value to
enum LockingClauseStrength, which is fairly annoying but the alternatives
seem worse. This fix allows getting rid of the use of get_parse_rowmark()
in FDWs (as per the discussion around commits 462bd95705a0c23b and
8ec8760fc87ecde0), and it simplifies some things elsewhere.
Second, that the representation assumed that all child tables in an
inheritance hierarchy would use the same RowMarkType. That's true today
but will soon not be true. We add an "allMarkTypes" field that identifies
the union of mark types used in all a parent table's children, and use
that where appropriate (currently, only in preprocess_targetlist()).
In passing fix a couple of minor infelicities left over from the SKIP
LOCKED patch, notably that _outPlanRowMark still thought waitPolicy
is a bool.
Catversion bump is required because the numeric values of enum
LockingClauseStrength can appear in on-disk rules.
Extracted from a much larger patch to support foreign table inheritance;
it seemed worth breaking this out, since it's a separable concern.
Shigeru Hanada and Etsuro Fujita, somewhat modified by me
We can't handle this in the general case due to limitations of the
planner's data representations; but we can allow it in many useful cases,
by being careful to flatten only when we are pulling a single-row subquery
up into a FROM (or, equivalently, inner JOIN) node that will still have at
least one remaining relation child. Per discussion of an example from
Kyotaro Horiguchi.
This requires changing quite a few places that were depending on
sizeof(HeapTupleHeaderData), but it seems for the best.
Michael Paquier, some adjustments by me
The previous coding in EXPLAIN always labeled a ModifyTable node with the
name of the target table affected by its first child plan. When originally
written, this was necessarily the parent table of the inheritance tree,
so everything was unconfusing. But when we added NO INHERIT constraints,
it became possible for the parent table to be deleted from the plan by
constraint exclusion while still leaving child tables present. This led to
the ModifyTable plan node being labeled with the first surviving child,
which was deemed confusing. Fix it by retaining the parent table's RT
index in a new field in ModifyTable.
Etsuro Fujita, reviewed by Ashutosh Bapat and myself
As pointed out by Robert, we should really have named pg_rowsecurity
pg_policy, as the objects stored in that catalog are policies. This
patch fixes that and updates the column names to start with 'pol' to
match the new catalog name.
The security consideration for COPY with row level security, also
pointed out by Robert, has also been addressed by remembering and
re-checking the OID of the relation initially referenced during COPY
processing, to make sure it hasn't changed under us by the time we
finish planning out the query which has been built.
Robert and Alvaro also commented on missing OCLASS and OBJECT entries
for POLICY (formerly ROWSECURITY or POLICY, depending) in various
places. This patch fixes that too, which also happens to add the
ability to COMMENT on policies.
In passing, attempt to improve the consistency of messages, comments,
and documentation as well. This removes various incarnations of
'row-security', 'row-level security', 'Row-security', etc, in favor
of 'policy', 'row level security' or 'row_security' as appropriate.
Happy Thanksgiving!
This clause changes the behavior of SELECT locking clauses in the
presence of locked rows: instead of causing a process to block waiting
for the locks held by other processes (or raise an error, with NOWAIT),
SKIP LOCKED makes the new reader skip over such rows. While this is not
appropriate behavior for general purposes, there are some cases in which
it is useful, such as queue-like tables.
Catalog version bumped because this patch changes the representation of
stored rules.
Reviewed by Craig Ringer (based on a previous attempt at an
implementation by Simon Riggs, who also provided input on the syntax
used in the current patch), David Rowley, and Álvaro Herrera.
Author: Thomas Munro
