The index is scanned by a single process, but then all cooperating
processes can iterate jointly over the resulting set of heap blocks.
In the future, we might also want to support using a parallel bitmap
index scan to set up for a parallel bitmap heap scan, but that's a
job for another day.
Dilip Kumar, with some corrections and cosmetic changes by me. The
larger patch set of which this is a part has been reviewed and tested
by (at least) Andres Freund, Amit Khandekar, Tushar Ahuja, Rafia
Sabih, Haribabu Kommi, Thomas Munro, and me.
Discussion: http://postgr.es/m/CAFiTN-uc4=0WxRGfCzs-xfkMYcSEWUC-Fon6thkJGjkh9i=13A@mail.gmail.com
Extract the logic used by hash_inner_and_outer into a separate
function, get_cheapest_parallel_safe_total_inner, so that it can
also be used to plan parallel merge joins.
Also, add a require_parallel_safe argument to the existing function
get_cheapest_path_for_pathkeys, because parallel merge join needs
to find the cheapest path for a given set of pathkeys that is
parallel-safe, not just the cheapest one overall.
Patch by me, reviewed by Dilip Kumar.
Discussion: http://postgr.es/m/CA+TgmoYOv+dFK0MWW6366dFj_xTnohQfoBDrHyB7d1oZhrgPjA@mail.gmail.com
In combination with 569174f1be, which
taught the btree AM how to perform parallel index scans, this allows
parallel index scan plans on btree indexes. This infrastructure
should be general enough to support parallel index scans for other
index AMs as well, if someone updates them to support parallel
scans.
Amit Kapila, reviewed and tested by Anastasia Lubennikova, Tushar
Ahuja, and Haribabu Kommi, and me.
When min_parallel_relation_size was added, the only supported type
of parallel scan was a parallel sequential scan, but there are
pending patches for parallel index scan, parallel index-only scan,
and parallel bitmap heap scan. Those patches introduce two new
types of complications: first, what's relevant is not really the
total size of the relation but the portion of it that we will scan;
and second, index pages and heap pages shouldn't necessarily be
treated in exactly the same way. Typically, the number of index
pages will be quite small, but that doesn't necessarily mean that
a parallel index scan can't pay off.
Therefore, we introduce min_parallel_table_scan_size, which works
out a degree of parallelism for scans based on the number of table
pages that will be scanned (and which is therefore equivalent to
min_parallel_relation_size for parallel sequential scans) and also
min_parallel_index_scan_size which can be used to work out a degree
of parallelism based on the number of index pages that will be
scanned.
Amit Kapila and Robert Haas
Discussion: http://postgr.es/m/CAA4eK1KowGSYYVpd2qPpaPPA5R90r++QwDFbrRECTE9H_HvpOg@mail.gmail.com
Discussion: http://postgr.es/m/CAA4eK1+TnM4pXQbvn7OXqam+k_HZqb0ROZUMxOiL6DWJYCyYow@mail.gmail.com
Normally, if we have a WHERE clause like "indexcol = constant",
the planner will figure out that that index column can be ignored
when determining whether the index has a desired sort ordering.
But this failed to work for boolean index columns, because a
condition like "boolcol = true" is canonicalized to just "boolcol"
which does not give rise to an EquivalenceClass. Add a check to
allow the same type of deduction to be made in this case too.
Per a complaint from Dima Pavlov. Arguably this is a bug, but given the
limited impact and the small number of complaints so far, I won't risk
destabilizing plans in stable branches by back-patching.
Patch by me, reviewed by Michael Paquier
Discussion: https://postgr.es/m/1788.1481605684@sss.pgh.pa.us
This patch provides a new implementation of the logic added by commit
137805f89 and later removed by 77ba61080. It differs from the original
primarily in expending much less effort per joinrel in large queries,
which it accomplishes by doing most of the matching work once per query not
once per joinrel. Hopefully, it's also less buggy and better commented.
The never-documented enable_fkey_estimates GUC remains gone.
There remains work to be done to make the selectivity estimates account
for nulls in FK referencing columns; but that was true of the original
patch as well. We may be able to address this point later in beta.
In the meantime, any error should be in the direction of overestimating
rather than underestimating joinrel sizes, which seems like the direction
we want to err in.
Tomas Vondra and Tom Lane
Discussion: <31041.1465069446@sss.pgh.pa.us>
The main point of doing this is to allow the cutoff to be set very small,
even zero, to allow parallel-query behavior to be tested on relatively
small tables such as we typically use in the regression tests. But it
might be of use to users too. The number-of-workers scaling behavior in
create_plain_partial_paths() is pretty ad-hoc and subject to change, so
we won't expose anything about that, but the notion of not considering
parallel query at all for tables below size X seems reasonably stable.
Amit Kapila, per a suggestion from me
Discussion: <17170.1465830165@sss.pgh.pa.us>
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>
Given a three-or-more-way equivalence class, such as X.Y = Y.Y = Z.Z,
it was possible for the planner to omit one of the quals needed to
enforce that all members of the equivalence class are actually equal.
This only happened in the case of a parameterized join node for two
of the relations, that is a plan tree like
Nested Loop
-> Scan X
-> Nested Loop
-> Scan Y
-> Scan Z
Filter: Z.Z = X.X
The eclass machinery normally expects to apply X.X = Y.Y when those
two relations are joined, but in this shape of plan tree they aren't
joined until the top node --- and, if the lower nested loop is marked
as parameterized by X, the top node will assume that the relevant eclass
condition(s) got pushed down into the lower node. On the other hand,
the scan of Z assumes that it's only responsible for constraining Z.Z
to match any one of the other eclass members. So one or another of
the required quals sometimes fell between the cracks, depending on
whether consideration of the eclass in get_joinrel_parampathinfo()
for the lower nested loop chanced to generate X.X = Y.Y or X.X = Z.Z
as the appropriate constraint there. If it generated the latter,
it'd erroneously suppose that the Z scan would take care of matters.
To fix, force X.X = Y.Y to be generated and applied at that join node
when this case occurs.
This is *extremely* hard to hit in practice, because various planner
behaviors conspire to mask the problem; starting with the fact that the
planner doesn't really like to generate a parameterized plan of the
above shape. (It might have been impossible to hit it before we
tweaked things to allow this plan shape for star-schema cases.) Many
thanks to Alexander Kirkouski for submitting a reproducible test case.
The bug can be demonstrated in all branches back to 9.2 where parameterized
paths were introduced, so back-patch that far.
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
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.
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.
When use_remote_estimate is enabled, consider adding ORDER BY to the
query we sending to the remote server so that we can use that ordered
data for a merge join. Commit f18c944b61
arranges to push down the query pathkeys, which seems like the case
mostly likely to be a win, but testing shows this can sometimes win,
too.
For a regular table, we know which indexes are present and therefore
test whether the ordering provided by each such index is useful. Here,
we take the opposite approach: guess what orderings would be useful if
they could be generated cheaply, and then ask the remote side what those
will cost.
Ashutosh Bapat, with very substantial cosmetic revisions by me. Also
reviewed by Rushabh Lathia.
More fuzz testing by Andreas Seltenreich exposed that the planner did not
cope well with chains of lateral references. If relation X references Y
laterally, and Y references Z laterally, then we will have to scan X on the
inside of a nestloop with Z, so for all intents and purposes X is laterally
dependent on Z too. The planner did not understand this and would generate
intermediate joins that could not be used. While that was usually harmless
except for wasting some planning cycles, under the right circumstances it
would lead to "failed to build any N-way joins" or "could not devise a
query plan" planner failures.
To fix that, convert the existing per-relation lateral_relids and
lateral_referencers relid sets into their transitive closures; that is,
they now show all relations on which a rel is directly or indirectly
laterally dependent. This not only fixes the chained-reference problem
but allows some of the relevant tests to be made substantially simpler
and faster, since they can be reduced to simple bitmap manipulations
instead of searches of the LateralJoinInfo list.
Also, when a PlaceHolderVar that is due to be evaluated at a join contains
lateral references, we should treat those references as indirect lateral
dependencies of each of the join's base relations. This prevents us from
trying to join any individual base relations to the lateral reference
source before the join is formed, which again cannot work.
Andreas' testing also exposed another oversight in the "dangerous
PlaceHolderVar" test added in commit 85e5e222b1. Simply rejecting
unsafe join paths in joinpath.c is insufficient, because in some cases
we will end up rejecting *all* possible paths for a particular join, again
leading to "could not devise a query plan" failures. The restriction has
to be known also to join_is_legal and its cohort functions, so that they
will not select a join for which that will happen. I chose to move the
supporting logic into joinrels.c where the latter functions are.
Back-patch to 9.3 where LATERAL support was introduced.
Formerly, this function would always return "true" for an appendrel child
relation, because it would think that the appendrel parent was a potential
join target for the child. In principle that should only lead to some
inefficiency in planning, but fuzz testing by Andreas Seltenreich disclosed
that it could lead to "could not find pathkey item to sort" planner errors
in odd corner cases. Specifically, we would think that all columns of a
child table's multicolumn index were interesting pathkeys, causing us to
generate a MergeAppend path that sorts by all the columns. However, if any
of those columns weren't actually used above the level of the appendrel,
they would not get added to that rel's targetlist, which would result in
being unable to resolve the MergeAppend's sort keys against its targetlist
during createplan.c.
Backpatch to 9.3. In older versions, columns of an appendrel get added
to its targetlist even if they're not mentioned above the scan level,
so that the failure doesn't occur. It might be worth back-patching this
fix to older versions anyway, but I'll refrain for the moment.
Commit e7cb7ee145 included some design
decisions that seem pretty questionable to me, and there was quite a lot
of stuff not to like about the documentation and comments. Clean up
as follows:
* Consider foreign joins only between foreign tables on the same server,
rather than between any two foreign tables with the same underlying FDW
handler function. In most if not all cases, the FDW would simply have had
to apply the same-server restriction itself (far more expensively, both for
lack of caching and because it would be repeated for each combination of
input sub-joins), or else risk nasty bugs. Anyone who's really intent on
doing something outside this restriction can always use the
set_join_pathlist_hook.
* Rename fdw_ps_tlist/custom_ps_tlist to fdw_scan_tlist/custom_scan_tlist
to better reflect what they're for, and allow these custom scan tlists
to be used even for base relations.
* Change make_foreignscan() API to include passing the fdw_scan_tlist
value, since the FDW is required to set that. Backwards compatibility
doesn't seem like an adequate reason to expect FDWs to set it in some
ad-hoc extra step, and anyway existing FDWs can just pass NIL.
* Change the API of path-generating subroutines of add_paths_to_joinrel,
and in particular that of GetForeignJoinPaths and set_join_pathlist_hook,
so that various less-used parameters are passed in a struct rather than
as separate parameter-list entries. The objective here is to reduce the
probability that future additions to those parameter lists will result in
source-level API breaks for users of these hooks. It's possible that this
is even a small win for the core code, since most CPU architectures can't
pass more than half a dozen parameters efficiently anyway. I kept root,
joinrel, outerrel, innerrel, and jointype as separate parameters to reduce
code churn in joinpath.c --- in particular, putting jointype into the
struct would have been problematic because of the subroutines' habit of
changing their local copies of that variable.
* Avoid ad-hocery in ExecAssignScanProjectionInfo. It was probably all
right for it to know about IndexOnlyScan, but if the list is to grow
we should refactor the knowledge out to the callers.
* Restore nodeForeignscan.c's previous use of the relcache to avoid
extra GetFdwRoutine lookups for base-relation scans.
* Lots of cleanup of documentation and missed comments. Re-order some
code additions into more logical places.
Foreign data wrappers can use this capability for so-called "join
pushdown"; that is, instead of executing two separate foreign scans
and then joining the results locally, they can generate a path which
performs the join on the remote server and then is scanned locally.
This commit does not extend postgres_fdw to take advantage of this
capability; it just provides the infrastructure.
Custom scan providers can use this in a similar way. Previously,
it was only possible for a custom scan provider to scan a single
relation. Now, it can scan an entire join tree, provided of course
that it knows how to produce the same results that the join would
have produced if executed normally.
KaiGai Kohei, reviewed by Shigeru Hanada, Ashutosh Bapat, and me.
Instead of register_custom_path_provider and a CreateCustomScanPath
callback, let's just provide a standard function hook in set_rel_pathlist.
This is more flexible than what was previously committed, is more like the
usual conventions for planner hooks, and requires less support code in the
core. We had discussed this design (including centralizing the
set_cheapest() calls) back in March or so, so I'm not sure why it wasn't
done like this already.
We don't need make_restrictinfo_from_bitmapqual() anymore at all.
generate_bitmap_or_paths() doesn't need to be exported, and we can
drop its rather klugy restriction_only flag.
It's possible to extract a restriction OR clause from a join clause that
has the form of an OR-of-ANDs, if each sub-AND includes a clause that
mentions only one specific relation. While PG has been aware of that idea
for many years, the code previously only did it if it could extract an
indexable OR clause. On reflection, though, that seems a silly limitation:
adding a restriction clause can be a win by reducing the number of rows
that have to be filtered at the join step, even if we have to test the
clause as a plain filter clause during the scan. This should be especially
useful for foreign tables, where the change can cut the number of rows that
have to be retrieved from the foreign server; but testing shows it can win
even on local tables. Per a suggestion from Robert Haas.
As a heuristic, I made the code accept an extracted restriction clause
if its estimated selectivity is less than 0.9, which will probably result
in accepting extracted clauses just about always. We might need to tweak
that later based on experience.
Since the code no longer has even a weak connection to Path creation,
remove orindxpath.c and create a new file optimizer/util/orclauses.c.
There's some additional janitorial cleanup of now-dead code that needs
to happen, but it seems like that's a fit subject for a separate commit.
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
Bug #8591 from Claudio Freire demonstrates that get_eclass_for_sort_expr
must be able to compute valid em_nullable_relids for any new equivalence
class members it creates. I'd worried about this in the commit message
for db9f0e1d9a, but claimed that it wasn't a
problem because multi-member ECs should already exist when it runs. That
is transparently wrong, though, because this function is also called by
initialize_mergeclause_eclasses, which runs during deconstruct_jointree.
The example given in the bug report (which the new regression test item
is based upon) fails because the COALESCE() expression is first seen by
initialize_mergeclause_eclasses rather than process_equivalence.
Fixing this requires passing the appropriate nullable_relids set to
get_eclass_for_sort_expr, and it requires new code to compute that set
for top-level expressions such as ORDER BY, GROUP BY, etc. We store
the top-level nullable_relids in a new field in PlannerInfo to avoid
computing it many times. In the back branches, I've added the new
field at the end of the struct to minimize ABI breakage for planner
plugins. There doesn't seem to be a good alternative to changing
get_eclass_for_sort_expr's API signature, though. There probably aren't
any third-party extensions calling that function directly; moreover,
if there are, they probably need to think about what to pass for
nullable_relids anyway.
Back-patch to 9.2, like the previous patch in this area.
This patch gets rid of the concept of, and infrastructure for,
non-canonical PathKeys; we now only ever create canonical pathkey lists.
The need for non-canonical pathkeys came from the desire to have
grouping_planner initialize query_pathkeys and related pathkey lists before
calling query_planner. However, since query_planner didn't actually *do*
anything with those lists before they'd been made canonical, we can get rid
of the whole mess by just not creating the lists at all until the point
where we formerly canonicalized them.
There are several ways in which we could implement that without making
query_planner itself deal with grouping/sorting features (which are
supposed to be the province of grouping_planner). I chose to add a
callback function to query_planner's API; other alternatives would have
required adding more fields to PlannerInfo, which while not bad in itself
would create an ABI break for planner-related plugins in the 9.2 release
series. This still breaks ABI for anything that calls query_planner
directly, but it seems somewhat unlikely that there are any such plugins.
I had originally conceived of this change as merely a step on the way to
fixing bug #8049 from Teun Hoogendoorn; but it turns out that this fixes
that bug all by itself, as per the added regression test. The reason is
that now get_eclass_for_sort_expr is adding the ORDER BY expression at the
end of EquivalenceClass creation not the start, and so anything that is in
a multi-member EquivalenceClass has already been created with correct
em_nullable_relids. I am suspicious that there are related scenarios in
which we still need to teach get_eclass_for_sort_expr to compute correct
nullable_relids, but am not eager to risk destabilizing either 9.2 or 9.3
to fix bugs that are only hypothetical. So for the moment, do this and
stop here.
Back-patch to 9.2 but not to earlier branches, since they don't exhibit
this bug for lack of join-clause-movement logic that depends on
em_nullable_relids being correct. (We might have to revisit that choice
if any related bugs turn up.) In 9.2, don't change the signature of
make_pathkeys_for_sortclauses nor remove canonicalize_pathkeys, so as
not to risk more plugin breakage than we have to.
I wasn't going to ship this without having at least some example of how
to do that. This version isn't terribly bright; in particular it won't
consider any combinations of multiple join clauses. Given the cost of
executing a remote EXPLAIN, I'm not sure we want to be very aggressive
about doing that, anyway.
In support of this, refactor generate_implied_equalities_for_indexcol
so that it can be used to extract equivalence clauses that aren't
necessarily tied to an index.
In a query such as "SELECT DISTINCT min(x) FROM tab", the DISTINCT is
pretty useless (there being only one output row), but nonetheless it
shouldn't fail. But it could fail if "tab" is an inheritance parent,
because planagg.c's code for fixing up equivalence classes after making the
index-optimized MIN/MAX transformation wasn't prepared to find child-table
versions of the aggregate expression. The least ugly fix seems to be
to add an option to mutate_eclass_expressions() to skip child-table
equivalence class members, which aren't used anymore at this stage of
planning so it's not really necessary to fix them. Since child members
are ignored in many cases already, it seems plausible for
mutate_eclass_expressions() to have an option to ignore them too.
Per bug #7703 from Maxim Boguk.
Back-patch to 9.1. Although the same code exists before that, it cannot
encounter child-table aggregates AFAICS, because the index optimization
transformation cannot succeed on inheritance trees before 9.1 (for lack
of MergeAppend).
Given a query such as
SELECT * FROM foo JOIN LATERAL (SELECT foo.var1) ss(x) ON ss.x = foo.var2
the existence of the join clause "ss.x = foo.var2" encourages indxpath.c to
build a parameterized path for foo using any index available for foo.var2.
This is completely useless activity, though, since foo has got to be on the
outside not the inside of any nestloop join with ss. It's reasonably
inexpensive to add tests that prevent creation of such paths, so let's do
that.
This patch adjusts the treatment of parameterized paths so that all paths
with the same parameterization (same set of required outer rels) for the
same relation will have the same rowcount estimate. We cache the rowcount
estimates to ensure that property, and hopefully save a few cycles too.
Doing this makes it practical for add_path_precheck to operate without
a rowcount estimate: it need only assume that paths with different
parameterizations never dominate each other, which is close enough to
true anyway for coarse filtering, because normally a more-parameterized
path should yield fewer rows thanks to having more join clauses to apply.
In add_path, we do the full nine yards of comparing rowcount estimates
along with everything else, so that we can discard parameterized paths that
don't actually have an advantage. This fixes some issues I'd found with
add_path rejecting parameterized paths on the grounds that they were more
expensive than not-parameterized ones, even though they yielded many fewer
rows and hence would be cheaper once subsequent joining was considered.
To make the same-rowcounts assumption valid, we have to require that any
parameterized path enforce *all* join clauses that could be obtained from
the particular set of outer rels, even if not all of them are useful for
indexing. This is required at both base scans and joins. It's a good
thing anyway since the net impact is that join quals are checked at the
lowest practical level in the join tree. Hence, discard the original
rather ad-hoc mechanism for choosing parameterization joinquals, and build
a better one that has a more principled rule for when clauses can be moved.
The original rule was actually buggy anyway for lack of knowledge about
which relations are part of an outer join's outer side; getting this right
requires adding an outer_relids field to RestrictInfo.
In commit 57664ed25e I tried to fix a bug
reported by Teodor Sigaev by making non-simple-Var output columns distinct
(by wrapping their expressions with dummy PlaceHolderVar nodes). This did
not work too well. Commit b28ffd0fcc fixed
some ensuing problems with matching to child indexes, but per a recent
report from Claus Stadler, constraint exclusion of UNION ALL subqueries was
still broken, because constant-simplification didn't handle the injected
PlaceHolderVars well either. On reflection, the original patch was quite
misguided: there is no reason to expect that EquivalenceClass child members
will be distinct. So instead of trying to make them so, we should ensure
that we can cope with the situation when they're not.
Accordingly, this patch reverts the code changes in the above-mentioned
commits (though the regression test cases they added stay). Instead, I've
added assorted defenses to make sure that duplicate EC child members don't
cause any problems. Teodor's original problem ("MergeAppend child's
targetlist doesn't match MergeAppend") is addressed more directly by
revising prepare_sort_from_pathkeys to let the parent MergeAppend's sort
list guide creation of each child's sort list.
In passing, get rid of add_sort_column; as far as I can tell, testing for
duplicate sort keys at this stage is dead code. Certainly it doesn't
trigger often enough to be worth expending cycles on in ordinary queries.
And keeping the test would've greatly complicated the new logic in
prepare_sort_from_pathkeys, because comparing pathkey list entries against
a previous output array requires that we not skip any entries in the list.
Back-patch to 9.1, like the previous patches. The only known issue in
this area that wasn't caused by the ill-advised previous patches was the
MergeAppend planning failure, which of course is not relevant before 9.1.
It's possible that we need some of the new defenses against duplicate child
EC entries in older branches, but until there's some clear evidence of that
I'm going to refrain from back-patching further.
This patch fixes the planner so that it can generate nestloop-with-
inner-indexscan plans even with one or more levels of joining between
the indexscan and the nestloop join that is supplying the parameter.
The executor was fixed to handle such cases some time ago, but the
planner was not ready. This should improve our plans in many situations
where join ordering restrictions formerly forced complete table scans.
There is probably a fair amount of tuning work yet to be done, because
of various heuristics that have been added to limit the number of
parameterized paths considered. However, we are not going to find out
what needs to be adjusted until the code gets some real-world use, so
it's time to get it in there where it can be tested easily.
Note API change for index AM amcostestimate functions. I'm not aware of
any non-core index AMs, but if there are any, they will need minor
adjustments.
In commit e2c2c2e8b1 I made use of nested
list structures to show which clauses went with which index columns, but
on reflection that's a data structure that only an old-line Lisp hacker
could love. Worse, it adds unnecessary complication to the many places
that don't much care which clauses go with which index columns. Revert
to the previous arrangement of flat lists of clauses, and instead add a
parallel integer list of column numbers. The places that care about the
pairing can chase both lists with forboth(), while the places that don't
care just examine one list the same as before.
The only real downside to this is that there are now two more lists that
need to be passed to amcostestimate functions in case they care about
column matching (which btcostestimate does, so not passing the info is not
an option). Rather than deal with 11-argument amcostestimate functions,
pass just the IndexPath and expect the functions to extract fields from it.
That gets us down to 7 arguments which is better than 11, and it seems
more future-proof against likely additions to the information we keep
about an index path.
It's potentially useful for an index to repeat the same indexable column
or expression in multiple index columns, if the columns have different
opclasses. (If they share opclasses too, the duplicate column is pretty
useless, but nonetheless we've allowed such cases since 9.0.) However,
the planner failed to cope with this, because createplan.c was relying on
simple equal() matching to figure out which index column each index qual
is intended for. We do have that information available upstream in
indxpath.c, though, so the fix is to not flatten the multi-level indexquals
list when putting it into an IndexPath. Then we can rely on the sublist
structure to identify target index columns in createplan.c. There's a
similar issue for index ORDER BYs (the KNNGIST feature), so introduce a
multi-level-list representation for that too. This adds a bit more
representational overhead, but we might more or less buy that back by not
having to search for matching index columns anymore in createplan.c;
likewise btcostestimate saves some cycles.
Per bug #6351 from Christian Rudolph. Likely symptoms include the "btree
index keys must be ordered by attribute" failure shown there, as well as
"operator MMMM is not a member of opfamily NNNN".
Although this is a pre-existing problem that can be demonstrated in 9.0 and
9.1, I'm not going to back-patch it, because the API changes in the planner
seem likely to break things such as index plugins. The corner cases where
this matters seem too narrow to justify possibly breaking things in a minor
release.
If the right-hand side of a semijoin is unique, then we can treat it like a
normal join (or another way to say that is: we don't need to explicitly
unique-ify the data before doing it as a normal join). We were recognizing
such cases when the RHS was a sub-query with appropriate DISTINCT or GROUP
BY decoration, but there's another way: if the RHS is a plain relation with
unique indexes, we can check if any of the indexes prove the output is
unique. Most of the infrastructure for that was there already in the join
removal code, though I had to rearrange it a bit. Per reflection about a
recent example in pgsql-performance.
Instead of playing cute games with pathkeys, just build a direct
representation of the intended sub-select, and feed it through
query_planner to get a Path for the index access. This is a bit slower
than 9.1's previous method, since we'll duplicate most of the overhead of
query_planner; but since the whole optimization only applies to rather
simple single-table queries, that probably won't be much of a problem in
practice. The advantage is that we get to do the right thing when there's
a partial index that needs the implicit IS NOT NULL clause to be usable.
Also, although this makes planagg.c be a bit more closely tied to the
ordering of operations in grouping_planner, we can get rid of some coupling
to lower-level parts of the planner. Per complaint from Marti Raudsepp.
All expression nodes now have an explicit output-collation field, unless
they are known to only return a noncollatable data type (such as boolean
or record). Also, nodes that can invoke collation-aware functions store
a separate field that is the collation value to pass to the function.
This avoids confusion that arises when a function has collatable inputs
and noncollatable output type, or vice versa.
Also, replace the parser's on-the-fly collation assignment method with
a post-pass over the completed expression tree. This allows us to use
a more complex (and hopefully more nearly spec-compliant) assignment
rule without paying for it in extra storage in every expression node.
Fix assorted bugs in the planner's handling of collations by making
collation one of the defining properties of an EquivalenceClass and
by converting CollateExprs into discardable RelabelType nodes during
expression preprocessing.
Per my recent proposal, get rid of all the direct inspection of indexes
and manual generation of paths in planagg.c. Instead, set up
EquivalenceClasses for the aggregate argument expressions, and let the
regular path generation logic deal with creating paths that can satisfy
those sort orders. This makes planagg.c a bit more visible to the rest
of the planner than it was originally, but the approach is basically a lot
cleaner than before. A major advantage of doing it this way is that we get
MIN/MAX optimization on inheritance trees (using MergeAppend of indexscans)
practically for free, whereas in the old way we'd have had to add a whole
lot more duplicative logic.
One small disadvantage of this approach is that MIN/MAX aggregates can no
longer exploit partial indexes having an "x IS NOT NULL" predicate, unless
that restriction or something that implies it is specified in the query.
The previous implementation was able to use the added "x IS NOT NULL"
condition as an extra predicate proof condition, but in this version we
rely entirely on indexes that are considered usable by the main planning
process. That seems a fair tradeoff for the simplicity and functionality
gained.
Zoltan Boszormenyi exhibited a test case in which planning time was
dominated by construction of EquivalenceClasses and PathKeys that had no
actual relevance to the query (and in fact got discarded immediately).
This happened because we generated PathKeys describing the sort ordering of
every index on every table in the query, and only after that checked to see
if the sort ordering was relevant. The EC/PK construction code is O(N^2)
in the number of ECs, which is all right for the intended number of such
objects, but it gets out of hand if there are ECs for lots of irrelevant
indexes.
To fix, twiddle the handling of mergeclauses a little bit to ensure that
every interesting EC is created before we begin path generation. (This
doesn't cost anything --- in fact I think it's a bit cheaper than before
--- since we always eventually created those ECs anyway.) Then, if an
index column can't be found in any pre-existing EC, we know that that sort
ordering is irrelevant for the query. Instead of creating a useless EC,
we can just not build a pathkey for the index column in the first place.
The index will still be considered if it's useful for non-order-related
reasons, but we will think of its output as unsorted.
by adding a requirement that build_join_rel add new join RelOptInfos to the
appropriate list immediately at creation. Per report from Robert Haas,
the list_concat_unique_ptr() calls that this change eliminates were taking
the lion's share of the runtime in larger join problems. This doesn't do
anything to fix the fundamental combinatorial explosion in large join
problems, but it should push out the threshold of pain a bit further.
Note: because this changes the order in which joinrel lists are built,
it might result in changes in selected plans in cases where different
alternatives have exactly the same costs. There is one example in the
regression tests.
is unique and is not referenced above the join. In this case the inner
side doesn't affect the query result and can be thrown away entirely.
Although perhaps nobody would ever write such a thing by hand, it's
a reasonably common case in machine-generated SQL.
The current implementation only recognizes the case where the inner side
is a simple relation with a unique index matching the query conditions.
This is enough for the use-cases that have been shown so far, but we
might want to try to handle other cases later.
Robert Haas, somewhat rewritten by Tom
Robert Haas
Tom Lane
Bruce Momjian
Simon Riggs
Magnus Hagander