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
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
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
I'd somehow talked myself into believing that set_append_rel_size
doesn't need to worry about getting back an AND clause when it applies
eval_const_expressions to the result of adjust_appendrel_attrs (that is,
transposing the appendrel parent's restriction clauses for one child).
But that is nonsense, and Andreas Seltenreich's fuzz tester soon
turned up a counterexample. Put back the make_ands_implicit step
that was there before, and add a regression test covering the case.
Report: https://postgr.es/m/878tq6vja6.fsf@ansel.ydns.eu
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
In an RLS query, we must ensure that security filter quals are evaluated
before ordinary query quals, in case the latter contain "leaky" functions
that could expose the contents of sensitive rows. The original
implementation of RLS planning ensured this by pushing the scan of a
secured table into a sub-query that it marked as a security-barrier view.
Unfortunately this results in very inefficient plans in many cases, because
the sub-query cannot be flattened and gets planned independently of the
rest of the query.
To fix, drop the use of sub-queries to enforce RLS qual order, and instead
mark each qual (RestrictInfo) with a security_level field establishing its
priority for evaluation. Quals must be evaluated in security_level order,
except that "leakproof" quals can be allowed to go ahead of quals of lower
security_level, if it's helpful to do so. This has to be enforced within
the ordering of any one list of quals to be evaluated at a table scan node,
and we also have to ensure that quals are not chosen for early evaluation
(i.e., use as an index qual or TID scan qual) if they're not allowed to go
ahead of other quals at the scan node.
This is sufficient to fix the problem for RLS quals, since we only support
RLS policies on simple tables and thus RLS quals will always exist at the
table scan level only. Eventually these qual ordering rules should be
enforced for join quals as well, which would permit improving planning for
explicit security-barrier views; but that's a task for another patch.
Note that FDWs would need to be aware of these rules --- and not, for
example, send an insecure qual for remote execution --- but since we do
not yet allow RLS policies on foreign tables, the case doesn't arise.
This will need to be addressed before we can allow such policies.
Patch by me, reviewed by Stephen Frost and Dean Rasheed.
Discussion: https://postgr.es/m/8185.1477432701@sss.pgh.pa.us
Pushing an upper-level restriction clause into an unflattened
subquery-in-FROM is okay when the subquery contains no SRFs in its
targetlist, or when it does but the SRFs are unreferenced by the clause
*and the clause is not volatile*. Otherwise, we're changing the number
of times the clause is evaluated, which is bad for volatile quals, and
possibly changing the result, since a volatile qual might succeed for some
SRF output rows and not others despite not referencing any of the changing
columns. (Indeed, if the clause is something like "random() > 0.5", the
user is probably expecting exactly that behavior.)
We had most of these restrictions down, but not the one about the upper
clause not being volatile. Fix that, and add a regression test to
illustrate the expected behavior.
Although this is definitely a bug, it doesn't seem like back-patch
material, since possibly some users don't realize that the broken
behavior is broken and are relying on what happens now. Also, while
the added test is quite cheap in the wake of commit a4c35ea1c, it would
be much more expensive (or else messier) in older branches.
Per report from Tom van Tilburg.
Discussion: <CAP3PPDiucxYCNev52=YPVkrQAPVF1C5PFWnrQPT7iMzO1fiKFQ@mail.gmail.com>
Teach the parser to reject misplaced set-returning functions during parse
analysis using p_expr_kind, in much the same way as we do for aggregates
and window functions (cf commit eaccfded9). While this isn't complete
(it misses nesting-based restrictions), it's much better than the previous
error reporting for such cases, and it allows elimination of assorted
ad-hoc expression_returns_set() error checks. We could add nesting checks
later if it seems important to catch all cases at parse time.
There is one case the parser will now throw error for although previous
versions allowed it, which is SRFs in the tlist of an UPDATE. That never
behaved sensibly (since it's ill-defined which generated row should be
used to perform the update) and it's hard to see why it should not be
treated as an error. It's a release-note-worthy change though.
Also, add a new Query field hasTargetSRFs reporting whether there are
any SRFs in the targetlist (including GROUP BY/ORDER BY expressions).
The parser can now set that basically for free during parse analysis,
and we can use it in a number of places to avoid expression_returns_set
searches. (There will be more such checks soon.) In some places, this
allows decontorting the logic since it's no longer expensive to check for
SRFs in the tlist --- so I made the checks parallel to the handling of
hasAggs/hasWindowFuncs wherever it seemed appropriate.
catversion bump because adding a Query field changes stored rules.
Andres Freund and Tom Lane
Discussion: <24639.1473782855@sss.pgh.pa.us>
Obvious brain fade in set_rel_consider_parallel(). Noticed it while
adjusting the adjacent RTE_FUNCTION case.
In 9.6, also make the code look more like what I just did in HEAD
by removing the unnecessary function_rte_parallel_ok subroutine
(it does nothing that expression_tree_walker wouldn't do).
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>
There isn't really any reason not to; the original comments here were
partly confused about subplans versus subquery-in-FROM, and partly
dependent on restrictions that no longer apply now that subqueries return
Paths not Plans. Depending on what's inside the subquery, it might fail
to produce any parallel_safe Paths, but that's fine.
Tom Lane and Robert Haas
The previous coding assumed that the value derived by
set_rel_consider_parallel() for an appendrel parent would be accurate for
all the appendrel's children; but this is not so, for example because one
child might scan a temp table. Instead, apply set_rel_consider_parallel()
to each child rel as well as the parent, and then take the AND of the
results as controlling parallel safety for the appendrel as a whole.
(We might someday be able to deal more intelligently than this with cases
in which some of the childrels are parallel-safe and others not, but that's
for later.)
Robert Haas and Tom Lane
This was the intention all along, but an extraneous "return;" in
set_rel_consider_parallel() caused sampled rels to never be marked
consider_parallel.
Since we don't have any partial tablesample path/plan type yet, there's
no possibility of parallelizing the sample scan itself; but this fix
allows such a scan to appear below a parallel join, for example.
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>
Commit b12fd41c6 added a "reltarget_has_non_vars" field to RelOptInfo,
but failed to maintain it accurately. Since its only purpose was to skip
calls to has_parallel_hazard() in the simple case where a rel's targetlist
is all Vars, and that call is really pretty cheap in that case anyway, it
seems like this is just a case of premature optimization. Let's drop the
flag and do the calls unconditionally until it's proven that we need more
smarts here.
Such paths are unsafe. To make it cheaper to detect when this case
applies, track whether a relation's default PathTarget contains any
non-Vars. In most cases, the answer will be no, which enables us to
determine cheaply that the target list for a proposed path is
parallel-safe. However, subquery pull-up can create cases that
require us to inspect the target list more carefully.
Amit Kapila, reviewed by me.
Fix a couple of overlooked uses of "degree" terminology. Make the parallel
worker count selection logic in create_plain_partial_paths more robust (in
particular, it failed with max_parallel_workers_per_gather set to zero).
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).
Now that Paths have their own rows field, print that rather than
the parent relation's rowcount.
Show the relid sets associated with Paths using table names rather
than numbers; since this code is able to print simple Var references
using table names, it seems a bit silly that print_relids can't.
Print the cheapest_parameterized_paths list for a RelOptInfo, and
include information about a parameterized path's required_outer rels.
Noted while trying to use this feature to debug Alexander Kirkouski's
recent bug report.
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>
The code that estimates what parallel degree should be uesd for the
scan of a relation is currently rather stupid, so add a parallel_degree
reloption that can be used to override the planner's rather limited
judgement.
Julien Rouhaud, reviewed by David Rowley, James Sewell, Amit Kapila,
and me. Some further hacking by me.
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
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.
In commit 1d97c19a0f and later c1d9579dd8, we extended
pull_var_clause's API by adding enum-type arguments. That's sort of a pain
to maintain, though, because it means every time we add a new behavior we
must touch every last one of the call sites, even if there's a reasonable
default behavior that most of them could use. Let's switch over to using a
bitmask of flags, instead; that seems more maintainable and might save a
nanosecond or two as well. This commit changes no behavior in itself,
though I'm going to follow it up with one that does add a new behavior.
In passing, remove flatten_tlist(), which has not been used since 9.1
and would otherwise need the same API changes.
Removing these enums means that optimizer/tlist.h no longer needs to
depend on optimizer/var.h. Changing that caused a number of C files to
need addition of #include "optimizer/var.h" (probably we can thank old
runs of pgrminclude for that); but on balance it seems like a good change
anyway.
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.
In commit 19a541143a I replaced RelOptInfo.width with
RelOptInfo.reltarget.width, but I missed updating debug_print_rel()
for that because it's not compiled by default.
Reported by Salvador Fandino, patch by Michael Paquier.
This is basically a bug fix; the old code assumes that a ForeignScan
is always parallel-safe, but for postgres_fdw, for example, this is
definitely false. It should be true for file_fdw, though, since a
worker can read a file from the filesystem just as well as any other
backend process.
Original patch by Thomas Munro. Documentation, and changes to the
comments, by me.
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.
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.
The planner generally expects that the estimated rowcount of any relation
is at least one row, *unless* it has been proven empty by constraint
exclusion or similar mechanisms, which is marked by installing a dummy path
as the rel's cheapest path (cf. IS_DUMMY_REL). When I split up
allpaths.c's processing of base rels into separate set_base_rel_sizes and
set_base_rel_pathlists steps, the intention was that dummy rels would get
marked as such during the "set size" step; this is what justifies an Assert
in indxpath.c's get_loop_count that other relations should either be dummy
or have positive rowcount. Unfortunately I didn't get that quite right
for append relations: if all the child rels have been proven empty then
set_append_rel_size would come up with a rowcount of zero, which is
correct, but it didn't then do set_dummy_rel_pathlist. (We would have
ended up with the right state after set_append_rel_pathlist, but that's
too late, if we generate indexpaths for some other rel first.)
In addition to fixing the actual bug, I installed an Assert enforcing this
convention in set_rel_size; that then allows simplification of a couple
of now-redundant tests for zero rowcount in set_append_rel_size.
Also, to cover the possibility that third-party FDWs have been careless
about not returning a zero rowcount estimate, apply clamp_row_est to
whatever an FDW comes up with as the rows estimate.
Per report from Andreas Seltenreich. Back-patch to 9.2. Earlier branches
did not have the separation between set_base_rel_sizes and
set_base_rel_pathlists steps, so there was no intermediate state where an
appendrel would have had inconsistent rowcount and pathlist. It's possible
that adding the Assert to set_rel_size would be a good idea in older
branches too; but since they're not under development any more, it's likely
not worth the trouble.
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.
UPDATE ... WHERE CURRENT OF would not work in conjunction with
RLS. Arrange to allow the CURRENT OF expression to be pushed down.
Issue noted by Peter Geoghegan. Patch by Dean Rasheed. Back patch
to 9.5 where RLS was introduced.
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.
This SQL standard functionality allows to aggregate data by different
GROUP BY clauses at once. Each grouping set returns rows with columns
grouped by in other sets set to NULL.
This could previously be achieved by doing each grouping as a separate
query, conjoined by UNION ALLs. Besides being considerably more concise,
grouping sets will in many cases be faster, requiring only one scan over
the underlying data.
The current implementation of grouping sets only supports using sorting
for input. Individual sets that share a sort order are computed in one
pass. If there are sets that don't share a sort order, additional sort &
aggregation steps are performed. These additional passes are sourced by
the previous sort step; thus avoiding repeated scans of the source data.
The code is structured in a way that adding support for purely using
hash aggregation or a mix of hashing and sorting is possible. Sorting
was chosen to be supported first, as it is the most generic method of
implementation.
Instead of, as in an earlier versions of the patch, representing the
chain of sort and aggregation steps as full blown planner and executor
nodes, all but the first sort are performed inside the aggregation node
itself. This avoids the need to do some unusual gymnastics to handle
having to return aggregated and non-aggregated tuples from underlying
nodes, as well as having to shut down underlying nodes early to limit
memory usage. The optimizer still builds Sort/Agg node to describe each
phase, but they're not part of the plan tree, but instead additional
data for the aggregation node. They're a convenient and preexisting way
to describe aggregation and sorting. The first (and possibly only) sort
step is still performed as a separate execution step. That retains
similarity with existing group by plans, makes rescans fairly simple,
avoids very deep plans (leading to slow explains) and easily allows to
avoid the sorting step if the underlying data is sorted by other means.
A somewhat ugly side of this patch is having to deal with a grammar
ambiguity between the new CUBE keyword and the cube extension/functions
named cube (and rollup). To avoid breaking existing deployments of the
cube extension it has not been renamed, neither has cube been made a
reserved keyword. Instead precedence hacking is used to make GROUP BY
cube(..) refer to the CUBE grouping sets feature, and not the function
cube(). To actually group by a function cube(), unlikely as that might
be, the function name has to be quoted.
Needs a catversion bump because stored rules may change.
Author: Andrew Gierth and Atri Sharma, with contributions from Andres Freund
Reviewed-By: Andres Freund, Noah Misch, Tom Lane, Svenne Krap, Tomas
Vondra, Erik Rijkers, Marti Raudsepp, Pavel Stehule
Discussion: CAOeZVidmVRe2jU6aMk_5qkxnB7dfmPROzM7Ur8JPW5j8Y5X-Lw@mail.gmail.com
Add a TABLESAMPLE clause to SELECT statements that allows
user to specify random BERNOULLI sampling or block level
SYSTEM sampling. Implementation allows for extensible
sampling functions to be written, using a standard API.
Basic version follows SQLStandard exactly. Usable
concrete use cases for the sampling API follow in later
commits.
Petr Jelinek
Reviewed by Michael Paquier and Simon Riggs
The original security barrier view implementation, on which RLS is
built, prevented all non-leakproof functions from being pushed down to
below the view, even when the function was not receiving any data from
the view. This optimization improves on that situation by, instead of
checking strictly for non-leakproof functions, it checks for Vars being
passed to non-leakproof functions and allows functions which do not
accept arguments or whose arguments are not from the current query level
(eg: constants can be particularly useful) to be pushed down.
As discussed, this does mean that a function which is pushed down might
gain some idea that there are rows meeting a certain criteria based on
the number of times the function is called, but this isn't a
particularly new issue and the documentation in rules.sgml already
addressed similar covert-channel risks. That documentation is updated
to reflect that non-leakproof functions may be pushed down now, if
they meet the above-described criteria.
Author: Dean Rasheed, with a bit of rework to make things clearer,
along with comment and documentation updates from me.
Robert Haas
Alvaro Herrera
Peter Eisentraut
Tom Lane
Andres Freund
Bruce Momjian
Joe Conway
Simon Riggs
Stephen Frost