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Since commit 4f15e5d09de276fb77326be5567dd9796008ca2e made grouped_rel
set reltarget, a variety of other functions can just get it from
grouped_rel instead of having to pass it around explicitly. Simplify
accordingly.
Patch by me, reviewed by Ashutosh Bapat.
Discussion: http://postgr.es/m/CA+TgmoZ+ZJTVad-=vEq393N99KTooxv9k7M+z73qnTAqkb49BQ@mail.gmail.com
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If we're inside a lateral subquery, there may be no unparameterized paths
for a particular child relation of an appendrel, in which case we *must*
be able to create similarly-parameterized paths for each other child
relation, else the planner will fail with "could not devise a query plan
for the given query". This means that there are situations where we'd
better be able to reparameterize at least one path for each child.
This calls into question the assumption in reparameterize_path() that
it can just punt if it feels like it. However, the only case that is
known broken right now is where the child is itself an appendrel so that
all its paths are AppendPaths. (I think possibly I disregarded that in
the original coding on the theory that nested appendrels would get folded
together --- but that only happens *after* reparameterize_path(), so it's
not excused from handling a child AppendPath.) Given that this code's been
like this since 9.3 when LATERAL was introduced, it seems likely we'd have
heard of other cases by now if there were a larger problem.
Per report from Elvis Pranskevichus. Back-patch to 9.3.
Discussion: https://postgr.es/m/5981018.zdth1YWmNy@hammer.magicstack.net
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When an UPDATE causes a row to no longer match the partition
constraint, try to move it to a different partition where it does
match the partition constraint. In essence, the UPDATE is split into
a DELETE from the old partition and an INSERT into the new one. This
can lead to surprising behavior in concurrency scenarios because
EvalPlanQual rechecks won't work as they normally did; the known
problems are documented. (There is a pending patch to improve the
situation further, but it needs more review.)
Amit Khandekar, reviewed and tested by Amit Langote, David Rowley,
Rajkumar Raghuwanshi, Dilip Kumar, Amul Sul, Thomas Munro, Álvaro
Herrera, Amit Kapila, and me. A few final revisions by me.
Discussion: http://postgr.es/m/CAJ3gD9do9o2ccQ7j7+tSgiE1REY65XRiMb=yJO3u3QhyP8EEPQ@mail.gmail.com
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Reorder header files in joinrels.c and pathnode.c in alphabetical order,
removing unnecessary ones.
Author: Etsuro Fujita
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Commit ab7271677 introduced code that attempts to order the child
scans of a Parallel Append node in a way that will minimize execution
time, based on total cost and startup cost. However, it failed to
think hard about what to do when estimated costs are exactly equal;
a case that's particularly likely to occur when comparing on startup
cost. In such a case the ordering of the child paths would be left
to the whims of qsort, an algorithm that isn't even stable.
We can improve matters by applying the rule used elsewhere in the
planner: if total costs are equal, sort on startup cost, and
vice versa. When both cost estimates are exactly equal, rather
than letting qsort do something unpredictable, sort based on the
child paths' relids, which should typically result in sorting in
inheritance order. (The latter provision requires inventing a
qsort-style comparator for bitmapsets, but maybe we'll have use
for that for other reasons in future.)
This results in a few plan changes in the select_parallel test,
but those all look more reasonable than before, when the actual
underlying cost numbers are taken into account.
Discussion: https://postgr.es/m/4944.1515446989@sss.pgh.pa.us
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Backpatch-through: certain files through 9.3
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Introduce parallel-aware hash joins that appear in EXPLAIN plans as Parallel
Hash Join with Parallel Hash. While hash joins could already appear in
parallel queries, they were previously always parallel-oblivious and had a
partial subplan only on the outer side, meaning that the work of the inner
subplan was duplicated in every worker.
After this commit, the planner will consider using a partial subplan on the
inner side too, using the Parallel Hash node to divide the work over the
available CPU cores and combine its results in shared memory. If the join
needs to be split into multiple batches in order to respect work_mem, then
workers process different batches as much as possible and then work together
on the remaining batches.
The advantages of a parallel-aware hash join over a parallel-oblivious hash
join used in a parallel query are that it:
* avoids wasting memory on duplicated hash tables
* avoids wasting disk space on duplicated batch files
* divides the work of building the hash table over the CPUs
One disadvantage is that there is some communication between the participating
CPUs which might outweigh the benefits of parallelism in the case of small
hash tables. This is avoided by the planner's existing reluctance to supply
partial plans for small scans, but it may be necessary to estimate
synchronization costs in future if that situation changes. Another is that
outer batch 0 must be written to disk if multiple batches are required.
A potential future advantage of parallel-aware hash joins is that right and
full outer joins could be supported, since there is a single set of matched
bits for each hashtable, but that is not yet implemented.
A new GUC enable_parallel_hash is defined to control the feature, defaulting
to on.
Author: Thomas Munro
Reviewed-By: Andres Freund, Robert Haas
Tested-By: Rafia Sabih, Prabhat Sahu
Discussion:
https://postgr.es/m/CAEepm=2W=cOkiZxcg6qiFQP-dHUe09aqTrEMM7yJDrHMhDv_RA@mail.gmail.com
https://postgr.es/m/CAEepm=37HKyJ4U6XOLi=JgfSHM3o6B-GaeO-6hkOmneTDkH+Uw@mail.gmail.com
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When we create an Append node, we can spread out the workers over the
subplans instead of piling on to each subplan one at a time, which
should typically be a bit more efficient, both because the startup
cost of any plan executed entirely by one worker is paid only once and
also because of reduced contention. We can also construct Append
plans using a mix of partial and non-partial subplans, which may allow
for parallelism in places that otherwise couldn't support it.
Unfortunately, this patch doesn't handle the important case of
parallelizing UNION ALL by running each branch in a separate worker;
the executor infrastructure is added here, but more planner work is
needed.
Amit Khandekar, Robert Haas, Amul Sul, reviewed and tested by
Ashutosh Bapat, Amit Langote, Rafia Sabih, Amit Kapila, and
Rajkumar Raghuwanshi.
Discussion: http://postgr.es/m/CAJ3gD9dy0K_E8r727heqXoBmWZ83HwLFwdcaSSmBQ1+S+vRuUQ@mail.gmail.com
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Put the unique path in the same context as the owning RelOptInfo, rather
than the toplevel planner context. This is how this function worked
originally, but commit f41803bb39bc2949db200116a609fd242d0ec221
changed it without explanation. mark_dummy_rel adopted the older (or
newer?) technique in commit eca75a12a27d28b972fc269c1c8813cd8eb15441,
which also featured a much better explanation of why it is correct.
So, switch back to that technique here, with the same explanation
given there.
Although this fixes a possible memory leak when GEQO is in use, the
leak is minor and probably nobody cares, so no back-patch.
Ashutosh Bapat, reviewed by Tom Lane and by me
Discussion: http://postgr.es/m/CAFjFpRcXkHHrXyD9BCvkgGJV4TnHG2SWJ0PhJfrDu3NAcQvh7g@mail.gmail.com
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Discussion: http://postgr.es/m/CA+TgmoaA9=1RWKtBWpDaj+sF3Stgc8sHgf5z=KGtbjwPLQVDMA@mail.gmail.com
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We already do this for Gather, but it got overlooked for Gather Merge.
Amit Kapila, with review and minor revisions by Rushabh Lathia
and by me.
Discussion: http://postgr.es/m/CAA4eK1KUC5Uyu7qaifxrjpHxbSeoQh3yzwN3bThnJsmJcZ-qtA@mail.gmail.com
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For some reason, we have never accounted for either the evaluation cost
or the selectivity of filter conditions attached to Agg and Group nodes
(which, in practice, are always conditions from a HAVING clause).
Applying our regular selectivity logic to post-grouping conditions is a
bit bogus, but it's surely better than taking the selectivity as 1.0.
Perhaps someday the extended-statistics mechanism can be taught to provide
statistics that would help us in getting non-default estimates here.
Per a gripe from Benjamin Coutu. This is surely a bug fix, but I'm
hesitant to back-patch because of the prospect of destabilizing existing
plan choices. Given that it took us this long to notice the bug, it's
probably not hurting too many people in the field.
Discussion: https://postgr.es/m/20968.1509486337@sss.pgh.pa.us
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Instead of joining two partitioned tables in their entirety we can, if
it is an equi-join on the partition keys, join the matching partitions
individually. This involves teaching the planner about "other join"
rels, which are related to regular join rels in the same way that
other member rels are related to baserels. This can use significantly
more CPU time and memory than regular join planning, because there may
now be a set of "other" rels not only for every base relation but also
for every join relation. In most practical cases, this probably
shouldn't be a problem, because (1) it's probably unusual to join many
tables each with many partitions using the partition keys for all
joins and (2) if you do that scenario then you probably have a big
enough machine to handle the increased memory cost of planning and (3)
the resulting plan is highly likely to be better, so what you spend in
planning you'll make up on the execution side. All the same, for now,
turn this feature off by default.
Currently, we can only perform joins between two tables whose
partitioning schemes are absolutely identical. It would be nice to
cope with other scenarios, such as extra partitions on one side or the
other with no match on the other side, but that will have to wait for
a future patch.
Ashutosh Bapat, reviewed and tested by Rajkumar Raghuwanshi, Amit
Langote, Rafia Sabih, Thomas Munro, Dilip Kumar, Antonin Houska, Amit
Khandekar, and by me. A few final adjustments by me.
Discussion: http://postgr.es/m/CAFjFpRfQ8GrQvzp3jA2wnLqrHmaXna-urjm_UY9BqXj=EaDTSA@mail.gmail.com
Discussion: http://postgr.es/m/CAFjFpRcitjfrULr5jfuKWRPsGUX0LQ0k8-yG0Qw2+1LBGNpMdw@mail.gmail.com
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Instead of duplicating the logic to search for a matching
ParamPathInfo in multiple places, factor it out into a separate
function.
Pass only the relevant bits of the PartitionKey to
partition_bounds_equal instead of the whole thing, because
partition-wise join will want to call this without having a
PartitionKey available.
Adjust allow_star_schema_join and calc_nestloop_required_outer
to take relevant Relids rather than the entire Path, because
partition-wise join will want to call it with the top-parent
relids to determine whether a child join is allowable.
Ashutosh Bapat. Review and testing of the larger patch set of which
this is a part by Amit Langote, Rajkumar Raghuwanshi, Rafia Sabih,
Thomas Munro, Dilip Kumar, and me.
Discussion: http://postgr.es/m/CA+TgmobQK80vtXjAsPZWWXd7c8u13G86gmuLupN+uUJjA+i4nA@mail.gmail.com
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Etsuro Fujita, slightly adjusted by me.
Discussion: http://postgr.es/m/e87c4a6d-23d7-5e7c-e8db-44ed418eb5d1@lab.ntt.co.jp
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Don't move parenthesized lines to the left, even if that means they
flow past the right margin.
By default, BSD indent lines up statement continuation lines that are
within parentheses so that they start just to the right of the preceding
left parenthesis. However, traditionally, if that resulted in the
continuation line extending to the right of the desired right margin,
then indent would push it left just far enough to not overrun the margin,
if it could do so without making the continuation line start to the left of
the current statement indent. That makes for a weird mix of indentations
unless one has been completely rigid about never violating the 80-column
limit.
This behavior has been pretty universally panned by Postgres developers.
Hence, disable it with indent's new -lpl switch, so that parenthesized
lines are always lined up with the preceding left paren.
This patch is much less interesting than the first round of indent
changes, but also bulkier, so I thought it best to separate the effects.
Discussion: https://postgr.es/m/E1dAmxK-0006EE-1r@gemulon.postgresql.org
Discussion: https://postgr.es/m/30527.1495162840@sss.pgh.pa.us
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Change pg_bsd_indent to follow upstream rules for placement of comments
to the right of code, and remove pgindent hack that caused comments
following #endif to not obey the general rule.
Commit e3860ffa4dd0dad0dd9eea4be9cc1412373a8c89 wasn't actually using
the published version of pg_bsd_indent, but a hacked-up version that
tried to minimize the amount of movement of comments to the right of
code. The situation of interest is where such a comment has to be
moved to the right of its default placement at column 33 because there's
code there. BSD indent has always moved right in units of tab stops
in such cases --- but in the previous incarnation, indent was working
in 8-space tab stops, while now it knows we use 4-space tabs. So the
net result is that in about half the cases, such comments are placed
one tab stop left of before. This is better all around: it leaves
more room on the line for comment text, and it means that in such
cases the comment uniformly starts at the next 4-space tab stop after
the code, rather than sometimes one and sometimes two tabs after.
Also, ensure that comments following #endif are indented the same
as comments following other preprocessor commands such as #else.
That inconsistency turns out to have been self-inflicted damage
from a poorly-thought-through post-indent "fixup" in pgindent.
This patch is much less interesting than the first round of indent
changes, but also bulkier, so I thought it best to separate the effects.
Discussion: https://postgr.es/m/E1dAmxK-0006EE-1r@gemulon.postgresql.org
Discussion: https://postgr.es/m/30527.1495162840@sss.pgh.pa.us
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Otherwise, set_plan_refs() can get applied to the same list
multiple times through different references, leading to chaos.
Amit Langote, Dilip Kumar, and Robert Haas, reviewed by Ashutosh
Bapat. Original report by Sveinn Sveinsson.
Discussion: http://postgr.es/m/20170517141151.1435.79890@wrigleys.postgresql.org
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perltidy run not included.
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If there can certainly be no more than one matching inner row for a given
outer row, then the executor can move on to the next outer row as soon as
it's found one match; there's no need to continue scanning the inner
relation for this outer row. This saves useless scanning in nestloop
and hash joins. In merge joins, it offers the opportunity to skip
mark/restore processing, because we know we have not advanced past the
first possible match for the next outer row.
Of course, the devil is in the details: the proof of uniqueness must
depend only on joinquals (not otherquals), and if we want to skip
mergejoin mark/restore then it must depend only on merge clauses.
To avoid adding more planning overhead than absolutely necessary,
the present patch errs in the conservative direction: there are cases
where inner_unique or skip_mark_restore processing could be used, but
it will not do so because it's not sure that the uniqueness proof
depended only on "safe" clauses. This could be improved later.
David Rowley, reviewed and rather heavily editorialized on by me
Discussion: https://postgr.es/m/CAApHDvqF6Sw-TK98bW48TdtFJ+3a7D2mFyZ7++=D-RyPsL76gw@mail.gmail.com
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A QueryEnvironment concept is added, which allows new types of
objects to be passed into queries from parsing on through
execution. At this point, the only thing implemented is a
collection of EphemeralNamedRelation objects -- relations which
can be referenced by name in queries, but do not exist in the
catalogs. The only type of ENR implemented is NamedTuplestore, but
provision is made to add more types fairly easily.
An ENR can carry its own TupleDesc or reference a relation in the
catalogs by relid.
Although these features can be used without SPI, convenience
functions are added to SPI so that ENRs can easily be used by code
run through SPI.
The initial use of all this is going to be transition tables in
AFTER triggers, but that will be added to each PL as a separate
commit.
An incidental effect of this patch is to produce a more informative
error message if an attempt is made to modify the contents of a CTE
from a referencing DML statement. No tests previously covered that
possibility, so one is added.
Kevin Grittner and Thomas Munro
Reviewed by Heikki Linnakangas, David Fetter, and Thomas Munro
with valuable comments and suggestions from many others
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Commit 45be99f8cd5d606086e0a458c9c72910ba8a613d removed GatherPath's
num_workers field, but this is entirely bogus. Normally, a path's
parallel_workers flag is supposed to indicate the number of workers
that it wants, and should be 0 for a non-partial path. In that
commit, I mistakenly thought that GatherPath could also use that field
to indicate the number of workers that it would try to start, but
that's disastrous, because then it can propagate up to higher nodes in
the plan tree, which will then get incorrect rowcounts because the
parallel_workers flag is involved in computing those values. Repair
by putting the separate field back.
Report by Tomas Vondra. Patch by me, reviewed by Amit Kapila.
Discussion: http://postgr.es/m/f91b4a44-f739-04bd-c4b6-f135bd643669@2ndquadrant.com
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This extends the Aggregate node with two new features: HashAggregate
can now run multiple hashtables concurrently, and a new strategy
MixedAggregate populates hashtables while doing sorted grouping.
The planner will now attempt to save as many sorts as possible when
planning grouping sets queries, while not exceeding work_mem for the
estimated combined sizes of all hashtables used. No SQL-level changes
are required. There should be no user-visible impact other than the
new EXPLAIN output and possible changes to result ordering when ORDER
BY was not used (which affected a few regression tests). The
enable_hashagg option is respected.
Author: Andrew Gierth
Reviewers: Mark Dilger, Andres Freund
Discussion: https://postgr.es/m/87vatszyhj.fsf@news-spur.riddles.org.uk
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Partitioned tables do not contain any data; only their unpartitioned
descendents need to be scanned. However, the partitioned tables still
need to be locked, even though they're not scanned. To make that
work, Append and MergeAppend relations now need to carry a list of
(unscanned) partitioned relations that must be locked, and InitPlan
must lock all partitioned result relations.
Aside from the obvious advantage of avoiding some work at execution
time, this has two other advantages. First, it may improve the
planner's decision-making in some cases since the empty relation
might throw things off. Second, it paves the way to getting rid of
the storage for partitioned tables altogether.
Amit Langote, reviewed by me.
Discussion: http://postgr.es/m/6837c359-45c4-8044-34d1-736756335a15@lab.ntt.co.jp
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Like Gather, we spawn multiple workers and run the same plan in each
one; however, Gather Merge is used when each worker produces the same
output ordering and we want to preserve that output ordering while
merging together the streams of tuples from various workers. (In a
way, Gather Merge is like a hybrid of Gather and MergeAppend.)
This works out to a win if it saves us from having to perform an
expensive Sort. In cases where only a small amount of data would need
to be sorted, it may actually be faster to use a regular Gather node
and then sort the results afterward, because Gather Merge sometimes
needs to wait synchronously for tuples whereas a pure Gather generally
doesn't. But if this avoids an expensive sort then it's a win.
Rushabh Lathia, reviewed and tested by Amit Kapila, Thomas Munro,
and Neha Sharma, and reviewed and revised by me.
Discussion: http://postgr.es/m/CAGPqQf09oPX-cQRpBKS0Gq49Z+m6KBxgxd_p9gX8CKk_d75HoQ@mail.gmail.com
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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
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XMLTABLE is defined by the SQL/XML standard as a feature that allows
turning XML-formatted data into relational form, so that it can be used
as a <table primary> in the FROM clause of a query.
This new construct provides significant simplicity and performance
benefit for XML data processing; what in a client-side custom
implementation was reported to take 20 minutes can be executed in 400ms
using XMLTABLE. (The same functionality was said to take 10 seconds
using nested PostgreSQL XPath function calls, and 5 seconds using
XMLReader under PL/Python).
The implemented syntax deviates slightly from what the standard
requires. First, the standard indicates that the PASSING clause is
optional and that multiple XML input documents may be given to it; we
make it mandatory and accept a single document only. Second, we don't
currently support a default namespace to be specified.
This implementation relies on a new executor node based on a hardcoded
method table. (Because the grammar is fixed, there is no extensibility
in the current approach; further constructs can be implemented on top of
this such as JSON_TABLE, but they require changes to core code.)
Author: Pavel Stehule, Álvaro Herrera
Extensively reviewed by: Craig Ringer
Discussion: https://postgr.es/m/CAFj8pRAgfzMD-LoSmnMGybD0WsEznLHWap8DO79+-GTRAPR4qA@mail.gmail.com
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In combination with 569174f1be92be93f5366212cc46960d28a5c5cd, 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.
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Evaluation of set returning functions (SRFs_ in the targetlist (like SELECT
generate_series(1,5)) so far was done in the expression evaluation (i.e.
ExecEvalExpr()) and projection (i.e. ExecProject/ExecTargetList) code.
This meant that most executor nodes performing projection, and most
expression evaluation functions, had to deal with the possibility that an
evaluated expression could return a set of return values.
That's bad because it leads to repeated code in a lot of places. It also,
and that's my (Andres's) motivation, made it a lot harder to implement a
more efficient way of doing expression evaluation.
To fix this, introduce a new executor node (ProjectSet) that can evaluate
targetlists containing one or more SRFs. To avoid the complexity of the old
way of handling nested expressions returning sets (e.g. having to pass up
ExprDoneCond, and dealing with arguments to functions returning sets etc.),
those SRFs can only be at the top level of the node's targetlist. The
planner makes sure (via split_pathtarget_at_srfs()) that SRF evaluation is
only necessary in ProjectSet nodes and that SRFs are only present at the
top level of the node's targetlist. If there are nested SRFs the planner
creates multiple stacked ProjectSet nodes. The ProjectSet nodes always get
input from an underlying node.
We also discussed and prototyped evaluating targetlist SRFs using ROWS
FROM(), but that turned out to be more complicated than we'd hoped.
While moving SRF evaluation to ProjectSet would allow to retain the old
"least common multiple" behavior when multiple SRFs are present in one
targetlist (i.e. continue returning rows until all SRFs are at the end of
their input at the same time), we decided to instead only return rows till
all SRFs are exhausted, returning NULL for already exhausted ones. We
deemed the previous behavior to be too confusing, unexpected and actually
not particularly useful.
As a side effect, the previously prohibited case of multiple set returning
arguments to a function, is now allowed. Not because it's particularly
desirable, but because it ends up working and there seems to be no argument
for adding code to prohibit it.
Currently the behavior for COALESCE and CASE containing SRFs has changed,
returning multiple rows from the expression, even when the SRF containing
"arm" of the expression is not evaluated. That's because the SRFs are
evaluated in a separate ProjectSet node. As that's quite confusing, we're
likely to instead prohibit SRFs in those places. But that's still being
discussed, and the code would reside in places not touched here, so that's
a task for later.
There's a lot of, now superfluous, code dealing with set return expressions
around. But as the changes to get rid of those are verbose largely boring,
it seems better for readability to keep the cleanup as a separate commit.
Author: Tom Lane and Andres Freund
Discussion: https://postgr.es/m/20160822214023.aaxz5l4igypowyri@alap3.anarazel.de
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create_merge_append_path should use the path rowcount it just computed,
not rel->tuples, for costing purposes. Those numbers should always be
the same at present, but if we ever support parameterized MergeAppend
paths (a case this function is otherwise prepared for), the former would
be right and the latter wrong.
No need for back-patch since the problem is only latent.
Ashutosh Bapat
Discussion: <CAFjFpRek+cLCnTo24youuGtsq4zRphEB8EUUPjDxZjnL4n4HYQ@mail.gmail.com>
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We need to scan the whole parse tree for parallel-unsafe functions.
If there are none, we'll later need to determine whether particular
subtrees contain any parallel-restricted functions. The previous coding
retained no knowledge from the first scan, even though this is very
wasteful in the common case where the query contains only parallel-safe
functions. We can bypass all of the later scans by remembering that fact.
This provides a small but measurable speed improvement when the case
applies, and shouldn't cost anything when it doesn't.
Patch by me, reviewed by Robert Haas
Discussion: <3740.1471538387@sss.pgh.pa.us>
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Commit 3fc6e2d7f5b652b417fa6937c34de2438d60fa9f introduced new "upper"
RelOptInfo structures but didn't set consider_parallel for them
correctly, a point I completely missed when reviewing it. Later,
commit e06a38965b3bcdaa881e7e06892d4d8ab6c2c980 made the situation
worse by doing it incorrectly for the grouping relation. Try to
straighten all of that out. Along the way, get rid of the annoying
wholePlanParallelSafe flag, which was only necessarily because of
the fact that upper planning stages didn't use paths at the time
that code was written.
The most important immediate impact of these changes is that
force_parallel_mode will provide useful test coverage in quite a few
more scenarios than it did previously, but it's also necessary
preparation for fixing some problems related to subqueries.
Patch by me, reviewed by Tom Lane.
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The original coding had three separate booleans representing partial
aggregation behavior, which was confusing, unreadable, and error-prone,
not least because the booleans weren't always listed in the same order.
It was also inadequate for the allegedly-desirable future extension to
support intermediate partial aggregation, because we'd need separate
markers for serialization and deserialization in such a case.
Merge these bools into an enum "AggSplit" to provide symbolic names for
the supported operating modes (and document what those are). By assigning
the values of the enum constants carefully, we can treat AggSplit values
as options bitmasks so that tests of what to do aren't noticeably more
expensive than before.
While at it, get rid of Aggref.aggoutputtype. That's not needed since
commit 59a3795c2 got rid of setrefs.c's special-purpose Aggref comparison
code, and it likewise seemed more confusing than helpful.
Assorted comment cleanup as well (there's still more that I want to do
in that line).
catversion bump for change in Aggref node contents. Should be the last
one for partial-aggregation changes.
Discussion: <29309.1466699160@sss.pgh.pa.us>
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The original upper-planner-pathification design (commit 3fc6e2d7f5b652b4)
assumed that we could always determine during Path formation whether or not
we would need a Result plan node to perform projection of a targetlist.
That turns out not to work very well, though, because createplan.c still
has some responsibilities for choosing the specific target list associated
with sorting/grouping nodes (in particular it might choose to add resjunk
columns for sorting). We might not ever refactor that --- doing so would
push more work into Path formation, which isn't attractive --- and we
certainly won't do so for 9.6. So, while create_projection_path and
apply_projection_to_path can tell for sure what will happen if the subpath
is projection-capable, they can't tell for sure when it isn't. This is at
least a latent bug in apply_projection_to_path, which might think it can
apply a target to a non-projecting node when the node will end up computing
something different.
Also, I'd tied the creation of a ProjectionPath node to whether or not a
Result is needed, but it turns out that we sometimes need a ProjectionPath
node anyway to avoid modifying a possibly-shared subpath node. Callers had
to use create_projection_path for such cases, and we added code to them
that knew about the potential omission of a Result node and attempted to
adjust the cost estimates for that. That was uncertainly correct and
definitely ugly/unmaintainable.
To fix, have create_projection_path explicitly check whether a Result
is needed and adjust its cost estimate accordingly, though it creates
a ProjectionPath in either case. apply_projection_to_path is now mostly
just an optimized version that can avoid creating an extra Path node when
the input is known to not be shared with any other live path. (There
is one case that create_projection_path doesn't handle, which is pushing
parallel-safe expressions below a Gather node. We could make it do that
by duplicating the GatherPath, but there seems no need as yet.)
create_projection_plan still has to recheck the tlist-match condition,
which means that if the matching situation does get changed by createplan.c
then we'll have made a slightly incorrect cost estimate. But there seems
no help for that in the near term, and I doubt it occurs often enough,
let alone would change planning decisions often enough, to be worth
stressing about.
I added a "dummypp" field to ProjectionPath to track whether
create_projection_path thinks a Result is needed. This is not really
necessary as-committed because create_projection_plan doesn't look at the
flag; but it seems like a good idea to remember what we thought when
forming the cost estimate, if only for debugging purposes.
In passing, get rid of the target_parallel parameter added to
apply_projection_to_path by commit 54f5c5150. I don't think that's a good
idea because it involves callers in what should be an internal decision,
and opens us up to missing optimization opportunities if callers think they
don't need to provide a valid flag, as most don't. For the moment, this
just costs us an extra has_parallel_hazard call when planning a Gather.
If that starts to look expensive, I think a better solution would be to
teach PathTarget to carry/cache knowledge of parallel-safety of its
contents.
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Commit 04ae11f62e643e07c411c4935ea6af46cb112aa9 removed some broken
code to apply the scan/join target to partial paths, but its theory
that this processing step is totally unnecessary turns out to be wrong.
Put similar code back again, but this time, check for parallel-safety
and avoid in-place modifications to paths that may already have been
used as part of some other path.
(This is not an entirely elegant solution to this problem; it might
be better, for example, to postpone generate_gather_paths for the
topmost scan/join rel until after the scan/join target has been
applied. But this is not the time for such redesign work.)
Amit Kapila and Robert Haas
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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).
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We mustn't run generate_gather_paths() during add_paths_to_joinrel(),
because that function can be invoked multiple times for the same target
joinrel. Not only is it wasteful to build GatherPaths repeatedly, but
a later add_partial_path() could delete the partial path that a previously
created GatherPath depends on. Instead establish the convention that we
do generate_gather_paths() for a rel only just before set_cheapest().
The code was accidentally not broken for baserels, because as of today there
never is more than one partial path for a baserel. But that assumption
obviously has a pretty short half-life, so move the generate_gather_paths()
calls for those cases as well.
Also add some generic comments explaining how and why this all works.
Per fuzz testing by Andreas Seltenreich.
Report: <871t5pgwdt.fsf@credativ.de>
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This is necessary infrastructure for supporting parallel aggregation
for aggregates whose transition type is "internal". Such values
can't be passed between cooperating processes, because they are
just pointers.
David Rowley, reviewed by Tomas Vondra and by me.
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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.
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This means that, for example, "SELECT expensive_func(a) FROM bigtab
WHERE something" can compute expensive_func(a) in the workers rather
than the leader if it happens to be parallel-safe, which figures to be
a big win in some practical cases.
Currently, we can only do this if the entire target list is
parallel-safe. If we worked harder, we might be able to evaluate
parallel-safe targets in the worker and any parallel-restricted
targets in the leader, but that would be more complicated, and there
aren't that many parallel-restricted functions that people are likely
to use in queries anyway. I think. So just do the simple thing for
the moment.
Robert Haas, Amit Kapila, and Tom Lane
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This is basically like the just-added create_upper_paths_hook, but
control is funneled only to the FDW responsible for all the baserels
of the current query; so providing such a callback is much less likely
to add useless overhead than using the hook function is.
The documentation is a bit sketchy. We'll likely want to improve it,
and/or adjust the call conventions, when we get some experience with
actually using this callback. Hopefully somebody will find time to
experiment with it before 9.6 feature freeze.
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Although the default choice of rel->reltarget should typically be
sufficient for scan or join paths, it's not at all sufficient for the
purposes PathTargets were invented for; in particular not for
upper-relation Paths. So break API compatibility by adding a PathTarget
argument to create_foreignscan_path(). To ease updating of existing
code, accept a NULL value of the argument as selecting rel->reltarget.
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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.
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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.
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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.
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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.
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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.
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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.
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Backpatch certain files through 9.1
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