This terminology provoked widespread complaints. So, instead, rename
the GUC max_parallel_degree to max_parallel_workers_per_gather
(leaving room for a possible future GUC max_parallel_workers that acts
as a system-wide limit), and rename the parallel_degree reloption to
parallel_workers. Rename structure members to match.
These changes create a dump/restore hazard for users of PostgreSQL
9.6beta1 who have set the reloption (or applied the GUC using ALTER
USER or ALTER DATABASE).
This commit reverts 137805f89 as well as the associated commits 015e88942,
5306df283, and 68d704edb. We found multiple bugs in this feature, and
there was concern about possible planner slowdown (though to be fair,
exhibiting a very large slowdown proved difficult). The way forward
requires a considerable rewrite, which may or may not be possible to
accomplish in time for beta2. In my judgment reviewing the rewrite will
be easier to accomplish starting from a clean slate, so let's temporarily
revert what's there now. This also leaves us in a safe state if it turns
out to be necessary to postpone the rewrite to the next development cycle.
Discussion: <20160429102531.GA13701@huehner.biz>
Discussion is still underway as to whether to revert the entire patch
that added this function, but that discussion may not conclude before
beta1. So, in the meantime, let's do at least this much.
David Rowley
Change max_parallel_degree default from 0 to 2. It is possible that
this is not a good idea, or that we should go with 1 worker rather
than 2, but we won't find out without trying it. Along the way,
reword the documentation for max_parallel_degree a little bit to
hopefully make it more clear.
Discussion: 20160420174631.3qjjhpwsvvx5bau5@alap3.anarazel.de
We still use replacement selection for the first run of the sort only
and only when the number of tuples is relatively small. Otherwise,
the first run, and subsequent runs in all cases, are produced using
quicksort. This tends to be faster except perhaps for very small
amounts of working memory.
Peter Geoghegan, reviewed by Tomas Vondra, Jeff Janes, Mithun Cy,
Greg Stark, and me.
In cases where joins use multiple columns we currently assess each join
separately causing gross mis-estimates for join cardinality.
This patch adds use of FK information for the first time into the
planner. When FKs are present and we have multi-column join information,
plan estimates will be drastically improved. Cases with multiple FKs
are handled, though partial matches are ignored currently.
Net effect is substantial performance improvements for joins in many
common cases. Additional planning time is isolated to cases that are
currently performing poorly, measured at 0.08 - 0.15 ms.
Please watch for planner performance regressions; circumstances seem
unlikely but the law of unintended consequences may apply somewhen.
Additional complex tests welcome to prove this before release.
Tests can be performed using SET enable_fkey_estimates = on | off
using scripts provided during Hackers discussions, message id:
552335D9.3090707@2ndquadrant.com
Authors: Tomas Vondra and David Rowley
Reviewed and tested by Simon Riggs, adding comments only
Previously, the planner would reject an index-only scan if any restriction
clause for its table used a column not available from the index, even
if that restriction clause would later be dropped from the plan entirely
because it's implied by the index's predicate. This is a fairly common
situation for partial indexes because predicates using columns not included
in the index are often the most useful kind of predicate, and we have to
duplicate (or at least imply) the predicate in the WHERE clause in order
to get the index to be considered at all. So index-only scans were
essentially unavailable with such partial indexes.
To fix, we have to do detection of implied-by-predicate clauses much
earlier in the planner. This patch puts it in check_index_predicates
(nee check_partial_indexes), meaning it gets done for every partial index,
whereas we previously only considered this issue at createplan time,
so that the work was only done for an index actually selected for use.
That could result in a noticeable planning slowdown for queries against
tables with many partial indexes. However, testing suggested that there
isn't really a significant cost, especially not with reasonable numbers
of partial indexes. We do get a small additional benefit, which is that
cost_index is more accurate since it correctly discounts the evaluation
cost of clauses that will be removed. We can also avoid considering such
clauses as potential indexquals, which saves useless matching cycles in
the case where the predicate columns aren't in the index, and prevents
generating bogus plans that double-count the clause's selectivity when
the columns are in the index.
Tomas Vondra and Kyotaro Horiguchi, reviewed by Kevin Grittner and
Konstantin Knizhnik, and whacked around a little by me
cost_subplan() supposed that the given subplan must have plan_rows > 0,
which as far as I can tell was true until recent refactoring of the
code in createplan.c; but now that code allows the Result for a provably
empty subquery to have plan_rows = 0. Rather than undo that change,
put in a clamp to prevent zero divide.
get_cheapest_fractional_path() likewise supposed that best_path->rows > 0.
This assumption has been wrong for longer. It's actually harmless given
IEEE float math, because a positive value divided by zero gives +Infinity
and compare_fractional_path_costs() will do the right thing with that.
Still, best not to assume that.
final_cost_nestloop() also seems to have some risks in this area, so
borrow the clamping logic already present in the mergejoin cost functions.
Lastly, remove unnecessary clamp_row_est() in planner.c's calls to
get_number_of_groups(). The only thing that function does with path_rows
is pass it to estimate_num_groups() which already has an internal clamp,
so we don't need the extra call; and if we did, the callers are arguably
the wrong place for it anyway.
First two items reported by Piotr Stefaniak, the others are products
of my nosing around for similar problems. No back-patch since there's
no evidence that problems arise in the back branches.
Parallel workers can now partially aggregate the data and pass the
transition values back to the leader, which can combine the partial
results to produce the final answer.
David Rowley, based on earlier work by Haribabu Kommi. Reviewed by
Álvaro Herrera, Tomas Vondra, Amit Kapila, James Sewell, and me.
In commit 19a541143a 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.
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.
The core innovation of this patch is the introduction of the concept
of a partial path; that is, a path which if executed in parallel will
generate a subset of the output rows in each process. Gathering a
partial path produces an ordinary (complete) path. This allows us to
generate paths for parallel joins by joining a partial path for one
side (which at the baserel level is currently always a Partial Seq
Scan) to an ordinary path on the other side. This is subject to
various restrictions at present, especially that this strategy seems
unlikely to be sensible for merge joins, so only nested loops and
hash joins paths are generated.
This also allows an Append node to be pushed below a Gather node in
the case of a partitioned table.
Testing revealed that early versions of this patch made poor decisions
in some cases, which turned out to be caused by the fact that the
original cost model for Parallel Seq Scan wasn't very good. So this
patch tries to make some modest improvements in that area.
There is much more to be done in the area of generating good parallel
plans in all cases, but this seems like a useful step forward.
Patch by me, reviewed by Dilip Kumar and Amit Kapila.
This patch reduces pg_am to just two columns, a name and a handler
function. All the data formerly obtained from pg_am is now provided
in a C struct returned by the handler function. This is similar to
the designs we've adopted for FDWs and tablesample methods. There
are multiple advantages. For one, the index AM's support functions
are now simple C functions, making them faster to call and much less
error-prone, since the C compiler can now check function signatures.
For another, this will make it far more practical to define index access
methods in installable extensions.
A disadvantage is that SQL-level code can no longer see attributes
of index AMs; in particular, some of the crosschecks in the opr_sanity
regression test are no longer possible from SQL. We've addressed that
by adding a facility for the index AM to perform such checks instead.
(Much more could be done in that line, but for now we're content if the
amvalidate functions more or less replace what opr_sanity used to do.)
We might also want to expose some sort of reporting functionality, but
this patch doesn't do that.
Alexander Korotkov, reviewed by Petr Jelínek, and rather heavily
editorialized on by me.
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.
A Gather executor node runs any number of copies of a plan in an equal
number of workers and merges all of the results into a single tuple
stream. It can also run the plan itself, if the workers are
unavailable or haven't started up yet. It is intended to work with
the Partial Seq Scan node which will be added in future commits.
It could also be used to implement parallel query of a different sort
by itself, without help from Partial Seq Scan, if the single_copy mode
is used. In that mode, a worker executes the plan, and the parallel
leader does not, merely collecting the worker's results. So, a Gather
node could be inserted into a plan to split the execution of that plan
across two processes. Nested Gather nodes aren't currently supported,
but we might want to add support for that in the future.
There's nothing in the planner to actually generate Gather nodes yet,
so it's not quite time to break out the champagne. But we're getting
close.
Amit Kapila. Some designs suggestions were provided by me, and I also
reviewed the patch. Single-copy mode, documentation, and other minor
changes also by me.
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.
When the inner side of a nestloop SEMI or ANTI join is an indexscan that
uses all the join clauses as indexquals, it can be presumed that both
matched and unmatched outer rows will be processed very quickly: for
matched rows, we'll stop after fetching one row from the indexscan, while
for unmatched rows we'll have an indexscan that finds no matching index
entries, which should also be quick. The planner already knew about this,
but it was nonetheless charging for at least one full run of the inner
indexscan, as a consequence of concerns about the behavior of materialized
inner scans --- but those concerns don't apply in the fast case. If the
inner side has low cardinality (many matching rows) this could make an
indexscan plan look far more expensive than it actually is. To fix,
rearrange the work in initial_cost_nestloop/final_cost_nestloop so that we
don't add the inner scan cost until we've inspected the indexquals, and
then we can add either the full-run cost or just the first tuple's cost as
appropriate.
Experimentation with this fix uncovered another problem: add_path and
friends were coded to disregard cheap startup cost when considering
parameterized paths. That's usually okay (and desirable, because it thins
the path herd faster); but in this fast case for SEMI/ANTI joins, it could
result in throwing away the desired plain indexscan path in favor of a
bitmap scan path before we ever get to the join costing logic. In the
many-matching-rows cases of interest here, a bitmap scan will do a lot more
work than required, so this is a problem. To fix, add a per-relation flag
consider_param_startup that works like the existing consider_startup flag,
but applies to parameterized paths, and set it for relations that are the
inside of a SEMI or ANTI join.
To make this patch reasonably safe to back-patch, care has been taken to
avoid changing the planner's behavior except in the very narrow case of
SEMI/ANTI joins with inner indexscans. There are places in
compare_path_costs_fuzzily and add_path_precheck that are not terribly
consistent with the new approach, but changing them will affect planner
decisions at the margins in other cases, so we'll leave that for a
HEAD-only fix.
Back-patch to 9.3; before that, the consider_startup flag didn't exist,
meaning that the second aspect of the patch would be too invasive.
Per a complaint from Peter Holzer and analysis by Tomas Vondra.
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
If we have a semijoin, say
SELECT * FROM x WHERE x1 IN (SELECT y1 FROM y)
and we're estimating the cost of a parameterized indexscan on x, the number
of repetitions of the indexscan should not be taken as the size of y; it'll
really only be the number of distinct values of y1, because the only valid
plan with y on the outside of a nestloop would require y to be unique-ified
before joining it to x. Most of the time this doesn't make that much
difference, but sometimes it can lead to drastically underestimating the
cost of the indexscan and hence choosing a bad plan, as pointed out by
David Kubečka.
Fixing this is a bit difficult because parameterized indexscans are costed
out quite early in the planning process, before we have the information
that would be needed to call estimate_num_groups() and thereby estimate the
number of distinct values of the join column(s). However we can move the
code that extracts a semijoin RHS's unique-ification columns, so that it's
done in initsplan.c rather than on-the-fly in create_unique_path(). That
shouldn't make any difference speed-wise and it's really a bit cleaner too.
The other bit of information we need is the size of the semijoin RHS,
which is easy if it's a single relation (we make those estimates before
considering indexscan costs) but problematic if it's a join relation.
The solution adopted here is just to use the product of the sizes of the
join component rels. That will generally be an overestimate, but since
estimate_num_groups() only uses this input as a clamp, an overestimate
shouldn't hurt us too badly. In any case we don't allow this new logic
to produce a value larger than we would have chosen before, so that at
worst an overestimate leaves us no wiser than we were before.
This code relied on pointer equality to identify which restriction clauses
also appear in the indexquals (and, therefore, don't need to be applied as
simple filter conditions). That was okay once upon a time, years ago,
before we introduced the equivalence-class machinery. Now there's about a
50-50 chance that an equality clause appearing in the indexquals will be
the mirror image (commutator) of its mate in the restriction list. When
that happens, we'd erroneously think that the clause would be re-evaluated
at each visited row, and therefore inflate the cost estimate for the
indexscan by the clause's cost.
Add some logic to catch this case. It seems to me that it continues not to
be worthwhile to expend the extra predicate-proof work that createplan.c
will do on the finally-selected plan, but this case is common enough and
cheap enough to handle that we should do so.
This will make a small difference (about one cpu_operator_cost per row)
in simple cases; but in situations where there's an expensive function in
the indexquals, it can make a very large difference, as seen in recent
example from Jeff Janes.
This is a long-standing bug, but I'm hesitant to back-patch because of the
possibility of destabilizing plan choices that people may be happy with.
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
This allows extension modules to define their own methods for
scanning a relation, and get the core code to use them. It's
unclear as yet how much use this capability will find, but we
won't find out if we never commit it.
KaiGai Kohei, reviewed at various times and in various levels
of detail by Shigeru Hanada, Tom Lane, Andres Freund, Álvaro
Herrera, and myself.
This reverts commit ee1e5662d8, as well as
a remarkably large number of followup commits, which were mostly concerned
with the fact that the implementation didn't work terribly well. It still
doesn't: we probably need some rather basic work in the GUC infrastructure
if we want to fully support GUCs whose default varies depending on the
value of another GUC. Meanwhile, it also emerged that there wasn't really
consensus in favor of the definition the patch tried to implement (ie,
effective_cache_size should default to 4 times shared_buffers). So whack
it all back to where it was. In a followup commit, I'll do what was
recently agreed to, which is to simply change the default to a higher
value.
The previous method was overly complex and underly correct; in particular,
by assigning the default value with PGC_S_OVERRIDE, it prevented later
attempts to change the setting in postgresql.conf, as noted by Jeff Janes.
We should just assign the default value with source PGC_S_DYNAMIC_DEFAULT,
which will have the desired priority relative to the boot_val as well as
user-set values.
There is still a gap in this method: if there's an explicit assignment of
effective_cache_size = -1 in the postgresql.conf file, and that assignment
appears before shared_buffers is assigned, the code will substitute 4 times
the bootstrap default for shared_buffers, and that value will then persist
(since it will have source PGC_S_FILE). I don't see any very nice way
to avoid that though, and it's not a case to be expected in practice.
The existing comments in guc-file.l look forward to a redesign of the
DYNAMIC_DEFAULT mechanism; if that ever happens, we should consider this
case as one of the things we'd like to improve.
Fix integer overflow issue noted by Magnus Hagander, as well as a bunch
of other infelicities in commit ee1e5662d8
and its unreasonably large number of followups.
This patch adds the ability to write TABLE( function1(), function2(), ...)
as a single FROM-clause entry. The result is the concatenation of the
first row from each function, followed by the second row from each
function, etc; with NULLs inserted if any function produces fewer rows than
others. This is believed to be a much more useful behavior than what
Postgres currently does with multiple SRFs in a SELECT list.
This syntax also provides a reasonable way to combine use of column
definition lists with WITH ORDINALITY: put the column definition list
inside TABLE(), where it's clear that it doesn't control the ordinality
column as well.
Also implement SQL-compliant multiple-argument UNNEST(), by turning
UNNEST(a,b,c) into TABLE(unnest(a), unnest(b), unnest(c)).
The SQL standard specifies TABLE() with only a single function, not
multiple functions, and it seems to require an implicit UNNEST() which is
not what this patch does. There may be something wrong with that reading
of the spec, though, because if it's right then the spec's TABLE() is just
a pointless alternative spelling of UNNEST(). After further review of
that, we might choose to adopt a different syntax for what this patch does,
but in any case this functionality seems clearly worthwhile.
Andrew Gierth, reviewed by Zoltán Böszörményi and Heikki Linnakangas, and
significantly revised by me
The planner largely failed to consider the possibility that a
PlaceHolderVar's expression might contain a lateral reference to a Var
coming from somewhere outside the PHV's syntactic scope. We had a previous
report of a problem in this area, which I tried to fix in a quick-hack way
in commit 4da6439bd8, but Antonin Houska
pointed out that there were still some problems, and investigation turned
up other issues. This patch largely reverts that commit in favor of a more
thoroughly thought-through solution. The new theory is that a PHV's
ph_eval_at level cannot be higher than its original syntactic level. If it
contains lateral references, those don't change the ph_eval_at level, but
rather they create a lateral-reference requirement for the ph_eval_at join
relation. The code in joinpath.c needs to handle that.
Another issue is that createplan.c wasn't handling nested PlaceHolderVars
properly.
In passing, push knowledge of lateral-reference checks for join clauses
into join_clause_is_movable_to. This is mainly so that FDWs don't need
to deal with it.
This patch doesn't fix the original join-qual-placement problem reported by
Jeremy Evans (and indeed, one of the new regression test cases shows the
wrong answer because of that). But the PlaceHolderVar problems need to be
fixed before that issue can be addressed, so committing this separately
seems reasonable.
This is SQL-standard with a few extensions, namely support for
subqueries and outer references in clause expressions.
catversion bump due to change in Aggref and WindowFunc.
David Fetter, reviewed by Dean Rasheed.
In commit 0f61d4dd1b, I added code to copy up
column width estimates for each column of a subquery. That code supposed
that the subquery couldn't have any output columns that didn't correspond
to known columns of the current query level --- which is true when a query
is parsed from scratch, but the assumption fails when planning a view that
depends on another view that's been redefined (adding output columns) since
the upper view was made. This results in an assertion failure or even a
crash, as per bug #8025 from lindebg. Remove the Assert and instead skip
the column if its resno is out of the expected range.
This reduces unnecessary exposure of other headers through htup.h, which
is very widely included by many files.
I have chosen to move the function prototypes to the new file as well,
because that means htup.h no longer needs to include tupdesc.h. In
itself this doesn't have much effect in indirect inclusion of tupdesc.h
throughout the tree, because it's also required by execnodes.h; but it's
something to explore in the future, and it seemed best to do the htup.h
change now while I'm busy with it.
This patch takes care of a number of problems having to do with failure
to choose valid join orders and incorrect handling of lateral references
pulled up from subqueries. Notable changes:
* Add a LateralJoinInfo data structure similar to SpecialJoinInfo, to
represent join ordering constraints created by lateral references.
(I first considered extending the SpecialJoinInfo structure, but the
semantics are different enough that a separate data structure seems
better.) Extend join_is_legal() and related functions to prevent trying
to form unworkable joins, and to ensure that we will consider joins that
satisfy lateral references even if the joins would be clauseless.
* Fill in the infrastructure needed for the last few types of relation scan
paths to support parameterization. We'd have wanted this eventually
anyway, but it is necessary now because a relation that gets pulled up out
of a UNION ALL subquery may acquire a reltargetlist containing lateral
references, meaning that its paths *have* to be parameterized whether or
not we have any code that can push join quals down into the scan.
* Compute data about lateral references early in query_planner(), and save
in RelOptInfo nodes, to avoid repetitive calculations later.
* Assorted corner-case bug fixes.
There's probably still some bugs left, but this is a lot closer to being
real than it was before.
Re-allow subquery pullup for LATERAL subqueries, except when the subquery
is below an outer join and contains lateral references to relations outside
that outer join. If we pull up in such a case, we risk introducing lateral
cross-references into outer joins' ON quals, which is something the code is
entirely unprepared to cope with right now; and I'm not sure it'll ever be
worth coping with.
Support lateral refs in VALUES (this seems to be the only additional path
type that needs such support as a consequence of re-allowing subquery
pullup).
Put in a slightly hacky fix for joinpath.c's refusal to consider
parameterized join paths even when there cannot be any unparameterized
ones. This was causing "could not devise a query plan for the given query"
failures in queries involving more than two FROM items.
Put in an even more hacky fix for distribute_qual_to_rels() being unhappy
with join quals that contain references to rels outside their syntactic
scope; which is to say, disable that test altogether. Need to think about
how to preserve some sort of debugging cross-check here, while not
expending more cycles than befits a debugging cross-check.
Robert Haas
Tom Lane
Simon Riggs
Bruce Momjian
Heikki Linnakangas
Noah Misch
Andrew Dunstan
Alvaro Herrera