gset_data (aka gd) in planner.c is always non-null if and only if
parse->groupingSets is non-null, but Coverity doesn't know that and
complains. Feed it an assertion to see if that keeps it happy.
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
Commit 45be99f8cd 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
copyObject() is declared to return void *, which allows easily assigning
the result independent of the input, but it loses all type checking.
If the compiler supports typeof or something similar, cast the result to
the input type. This creates a greater amount of type safety. In some
cases, where the result is assigned to a generic type such as Node * or
Expr *, new casts are now necessary, but in general casts are now
unnecessary in the normal case and indicate that something unusual is
happening.
Reviewed-by: Mark Dilger <hornschnorter@gmail.com>
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
This replaces the old, recursive tree-walk based evaluation, with
non-recursive, opcode dispatch based, expression evaluation.
Projection is now implemented as part of expression evaluation.
This both leads to significant performance improvements, and makes
future just-in-time compilation of expressions easier.
The speed gains primarily come from:
- non-recursive implementation reduces stack usage / overhead
- simple sub-expressions are implemented with a single jump, without
function calls
- sharing some state between different sub-expressions
- reduced amount of indirect/hard to predict memory accesses by laying
out operation metadata sequentially; including the avoidance of
nearly all of the previously used linked lists
- more code has been moved to expression initialization, avoiding
constant re-checks at evaluation time
Future just-in-time compilation (JIT) has become easier, as
demonstrated by released patches intended to be merged in a later
release, for primarily two reasons: Firstly, due to a stricter split
between expression initialization and evaluation, less code has to be
handled by the JIT. Secondly, due to the non-recursive nature of the
generated "instructions", less performance-critical code-paths can
easily be shared between interpreted and compiled evaluation.
The new framework allows for significant future optimizations. E.g.:
- basic infrastructure for to later reduce the per executor-startup
overhead of expression evaluation, by caching state in prepared
statements. That'd be helpful in OLTPish scenarios where
initialization overhead is measurable.
- optimizing the generated "code". A number of proposals for potential
work has already been made.
- optimizing the interpreter. Similarly a number of proposals have
been made here too.
The move of logic into the expression initialization step leads to some
backward-incompatible changes:
- Function permission checks are now done during expression
initialization, whereas previously they were done during
execution. In edge cases this can lead to errors being raised that
previously wouldn't have been, e.g. a NULL array being coerced to a
different array type previously didn't perform checks.
- The set of domain constraints to be checked, is now evaluated once
during expression initialization, previously it was re-built
every time a domain check was evaluated. For normal queries this
doesn't change much, but e.g. for plpgsql functions, which caches
ExprStates, the old set could stick around longer. The behavior
around might still change.
Author: Andres Freund, with significant changes by Tom Lane,
changes by Heikki Linnakangas
Reviewed-By: Tom Lane, Heikki Linnakangas
Discussion: https://postgr.es/m/20161206034955.bh33paeralxbtluv@alap3.anarazel.de
Add support for explicitly declared statistic objects (CREATE
STATISTICS), allowing collection of statistics on more complex
combinations that individual table columns. Companion commands DROP
STATISTICS and ALTER STATISTICS ... OWNER TO / SET SCHEMA / RENAME are
added too. All this DDL has been designed so that more statistic types
can be added later on, such as multivariate most-common-values and
multivariate histograms between columns of a single table, leaving room
for permitting columns on multiple tables, too, as well as expressions.
This commit only adds support for collection of n-distinct coefficient
on user-specified sets of columns in a single table. This is useful to
estimate number of distinct groups in GROUP BY and DISTINCT clauses;
estimation errors there can cause over-allocation of memory in hashed
aggregates, for instance, so it's a worthwhile problem to solve. A new
special pseudo-type pg_ndistinct is used.
(num-distinct estimation was deemed sufficiently useful by itself that
this is worthwhile even if no further statistic types are added
immediately; so much so that another version of essentially the same
functionality was submitted by Kyotaro Horiguchi:
https://postgr.es/m/20150828.173334.114731693.horiguchi.kyotaro@lab.ntt.co.jp
though this commit does not use that code.)
Author: Tomas Vondra. Some code rework by Álvaro.
Reviewed-by: Dean Rasheed, David Rowley, Kyotaro Horiguchi, Jeff Janes,
Ideriha Takeshi
Discussion: https://postgr.es/m/543AFA15.4080608@fuzzy.czhttps://postgr.es/m/20170320190220.ixlaueanxegqd5gr@alvherre.pgsql
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
Partitionwise join proposes add a concept of child join relations,
which will have the same relationship with join relations as "other
member" relations do with base relations. These relations will need
some but not all of the handling that we currently have for join
relations, and some but not all of the handling that we currently have
for appendrels, since they are a mix of the two. Refactor a little
bit so that the necessary bits of logic are exposed as separate
functions.
Ashutosh Bapat, reviewed and tested by Rajkumar Raghuwanshi and
by me.
Discussion: http://postgr.es/m/CAFjFpRfqotRR6cM3sooBHMHEVdkFfAZ6PyYg4GRZsoMuW08HjQ@mail.gmail.com
Commit 51ee6f3160 accidentally changed
the behavior around inheritance hierarchies; before, we always
considered parallel paths even for very small inheritance children,
because otherwise an inheritance hierarchy with even one small child
wouldn't be eligible for parallelism. That exception was inadverently
removed; put it back.
In passing, also adjust the degree-of-parallelism comptuation for
index-only scans not to consider the number of heap pages fetched.
Otherwise, we'll avoid parallel index-only scans on tables that are
mostly all-visible, which isn't especially logical.
Robert Haas and Amit Kapila, per a report from Ashutosh Sharma.
Discussion: http://postgr.es/m/CAE9k0PmgSoOHRd60SHu09aRVTHRSs8s6pmyhJKWHxWw9C_x+XA@mail.gmail.com
This logic was adapated from create_merge_append_plan, but the two
cases aren't really analogous, because create_merge_append_plan is not
projection-capable and must therefore have a tlist identical to that
of the underlying paths. Overwriting the tlist of Gather Merge with
whatever the underlying plan happens to produce is no good at all.
Patch by me, reviewed by Rushabh Lathia, who also reported the issue
and made an initial attempt at a fix.
Discussion: http://postgr.es/m/CA+Tgmob_-oHEOBfT9S25bjqokdqv8e8xEmh9zOY+3MPr_LmuhA@mail.gmail.com
Fallout from fcec6caafa2: mark a variable in
set_tablefunc_size_estimates as used for asserts only.
Also, the planner_rte_fetch() call is pointless with assertions
disabled, so enclose it in a USE_ASSERT_CHECKING #ifdef; fix the same
problem in set_subquery_size_estimates().
First problem noted by David Rowley, whose compiler is noisier than mine
in this regard.
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
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
Commit 45be99f8cd took the position
that performing a merge join in parallel was not likely to work out
well, but this conclusion was greeted with skepticism even at the
time. Whether it was true then or not, it's clearly not true any
more now that we have parallel index scan.
Dilip Kumar, reviewed by Amit Kapila and by me.
Discussion: http://postgr.es/m/CAFiTN-v3=cM6nyFwFGp0fmvY4=kk79Hq9Fgu0u8CSJ-EEq1Tiw@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
When the very cheapest path is not parallel-safe, we want to instead use
the cheapest unparameterized path that is. The old code searched
innerrel->cheapest_parameterized_paths, but that isn't right, because
the path we want may not be in that list. Search innerrel->pathlist
instead.
Spotted by Dilip Kumar.
Discussion: http://postgr.es/m/CAFiTN-szCEcZrQm0i_w4xqSaRUTOUFstNu32Zn4rxxDcoa8gnA@mail.gmail.com
Commit 5262f7a4fc added similar support
for parallel index scans; this extends that work to index-only scans.
As with parallel index scans, this requires support from the index AM,
so currently parallel index-only scans will only be possible for btree
indexes.
Rafia Sabih, reviewed and tested by Rahila Syed, Tushar Ahuja,
and Amit Kapila
Discussion: http://postgr.es/m/CAOGQiiPEAs4C=TBp0XShxBvnWXuzGL2u++Hm1=qnCpd6_Mf8Fw@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
This doesn't do anything to make Param nodes anything other than
parallel-restricted, so this only helps with uncorrelated subplans,
and it's not necessarily very cheap because each worker will run the
subplan separately (just as a Hash Join will build a separate copy of
the hash table in each participating process), but it's a first step
toward supporting cases that are more likely to help in practice, and
is occasionally useful on its own.
Amit Kapila, reviewed and tested by Rafia Sabih, Dilip Kumar, and
me.
Discussion: http://postgr.es/m/CAA4eK1+e8Z45D2n+rnDMDYsVEb5iW7jqaCH_tvPMYau=1Rru9w@mail.gmail.com
I noticed while hacking on join UNION transforms that planner.c's
function get_base_rel_indexes() just duplicates the functionality of
get_relids_in_jointree(). It doesn't even have the excuse of being
older code :-(. Drop it and use the latter function instead.
If we forcibly place a Material node atop a finished subplan, we need
to move any initPlans attached to the subplan up to the Material node,
in order to keep SS_finalize_plan() happy. I'd figured this out in
commit 7b67a0a49 for the case of materializing a cursor plan, but out of
an abundance of caution, I put the initPlan movement hack at the call
site for that case, rather than inside materialize_finished_plan().
That was the wrong thing, because it turns out to also be necessary for
the only other caller of materialize_finished_plan(), ie subselect.c.
We lacked any test cases that exposed the mistake, but bug#14524 from
Wei Congrui shows that it's possible to get an initPlan reference into
the top tlist in that case too, and then SS_finalize_plan() complains.
Hence, move the hack into materialize_finished_plan().
In HEAD, also relocate some recently-added tests in subselect.sql, which
I'd unthinkingly dropped into the middle of a sequence of related tests.
Report: https://postgr.es/m/20170202060020.1400.89021@wrigleys.postgresql.org
Given a targetlist like "srf(x), f(srf(x))", split_pathtarget_at_srfs()
decided that it needed two levels of ProjectSet nodes, failing to notice
that the two SRF calls are textually equal(). Because of that, setrefs.c
would convert the upper ProjectSet's tlist to "Var1, f(Var1)" (where Var1
represents a reference to the srf(x) output of the lower ProjectSet).
This triggered an assertion in nodeProjectSet.c complaining that it found
no SRFs to evaluate, as reported by Erik Rijkers.
What we want in such a case is to evaluate srf(x) only once and use a plain
Result node to compute "Var1, f(Var1)"; that gives results similar to what
previous versions produced, whereas allowing srf(x) to be evaluated again
in an upper ProjectSet would square the number of rows emitted.
Furthermore, even if the SRF calls aren't textually identical, we want them
to be evaluated in lockstep, because that's what happened in the old
implementation. But split_pathtarget_at_srfs() got this completely wrong,
using two levels of ProjectSet for a case like "srf(x), f(srf(y))".
Hence, rewrite split_pathtarget_at_srfs() from the ground up so that it
groups SRFs according to the depth of nesting of SRFs in their arguments.
This is pretty much how we envisioned that working originally, but I blew
it when it came to implementation.
In passing, optimize the case of target == input_target, which I noticed
is not only possible but quite common.
Discussion: https://postgr.es/m/dcbd2853c05d22088766553d60dc78c6@xs4all.nl
Currently, we only need this logic in order to cost a Bitmap Heap
Scan. But a pending patch for Parallel Bitmap Heap Scan also uses
it to help figure out how many workers to use for the scan, which
has to be determined prior to costing. So, move the logic to
a separate function to make that easier.
Dilip Kumar. The patch series of which this is a part has been
reviewed by Andres Freund, Amit Khendekar, Tushar Ahuja, Rafia
Sabih, Haribabu Kommi, and me; it is not clear from the email
discussion which of those people have looked specifically at this
part.
Discussion: http://postgr.es/m/CAFiTN-v3QYNJEZnnmKCeATuLbN-h9tMVfeEF0+BrouYDqjXgwg@mail.gmail.com
Joining three tables only takes two join nodes. I think when I (tgl)
wrote this, I was envisioning possible additional joins; but since the
example doesn't show any fourth table, it's just confusing to write
a third join node.
Etsuro Fujita
Discussion: https://postgr.es/m/e6cfbaa3-af02-1abc-c25e-8fa5c6bc4e21@lab.ntt.co.jp
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
Since 69f4b9c plain expression evaluation (and thus normal projection)
can't return sets of tuples anymore. Thus remove code dealing with
that possibility.
This will require adjustments in external code using
ExecEvalExpr()/ExecProject() - that should neither be hard nor very
common.
Author: Andres Freund and Tom Lane
Discussion: https://postgr.es/m/20160822214023.aaxz5l4igypowyri@alap3.anarazel.de
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
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 makes several changes that improve the consistency of
representation of lists of statements. It's always been the case
that the output of parse analysis is a list of Query nodes, whatever
the types of the individual statements in the list. This patch brings
similar consistency to the outputs of raw parsing and planning steps:
* The output of raw parsing is now always a list of RawStmt nodes;
the statement-type-dependent nodes are one level down from that.
* The output of pg_plan_queries() is now always a list of PlannedStmt
nodes, even for utility statements. In the case of a utility statement,
"planning" just consists of wrapping a CMD_UTILITY PlannedStmt around
the utility node. This list representation is now used in Portal and
CachedPlan plan lists, replacing the former convention of intermixing
PlannedStmts with bare utility-statement nodes.
Now, every list of statements has a consistent head-node type depending
on how far along it is in processing. This allows changing many places
that formerly used generic "Node *" pointers to use a more specific
pointer type, thus reducing the number of IsA() tests and casts needed,
as well as improving code clarity.
Also, the post-parse-analysis representation of DECLARE CURSOR is changed
so that it looks more like EXPLAIN, PREPARE, etc. That is, the contained
SELECT remains a child of the DeclareCursorStmt rather than getting flipped
around to be the other way. It's now true for both Query and PlannedStmt
that utilityStmt is non-null if and only if commandType is CMD_UTILITY.
That allows simplifying a lot of places that were testing both fields.
(I think some of those were just defensive programming, but in many places,
it was actually necessary to avoid confusing DECLARE CURSOR with SELECT.)
Because PlannedStmt carries a canSetTag field, we're also able to get rid
of some ad-hoc rules about how to reconstruct canSetTag for a bare utility
statement; specifically, the assumption that a utility is canSetTag if and
only if it's the only one in its list. While I see no near-term need for
relaxing that restriction, it's nice to get rid of the ad-hocery.
The API of ProcessUtility() is changed so that what it's passed is the
wrapper PlannedStmt not just the bare utility statement. This will affect
all users of ProcessUtility_hook, but the changes are pretty trivial; see
the affected contrib modules for examples of the minimum change needed.
(Most compilers should give pointer-type-mismatch warnings for uncorrected
code.)
There's also a change in the API of ExplainOneQuery_hook, to pass through
cursorOptions instead of expecting hook functions to know what to pick.
This is needed because of the DECLARE CURSOR changes, but really should
have been done in 9.6; it's unlikely that any extant hook functions
know about using CURSOR_OPT_PARALLEL_OK.
Finally, teach gram.y to save statement boundary locations in RawStmt
nodes, and pass those through to Query and PlannedStmt nodes. This allows
more intelligent handling of cases where a source query string contains
multiple statements. This patch doesn't actually do anything with the
information, but a follow-on patch will. (Passing this information through
cleanly is the true motivation for these changes; while I think this is all
good cleanup, it's unlikely we'd have bothered without this end goal.)
catversion bump because addition of location fields to struct Query
affects stored rules.
This patch is by me, but it owes a good deal to Fabien Coelho who did
a lot of preliminary work on the problem, and also reviewed the patch.
Discussion: https://postgr.es/m/alpine.DEB.2.20.1612200926310.29821@lancre
For a partial path, the cardinality estimate needs to reflect the
number of rows we think each worker will see, rather than the total
number of rows; otherwise, costing will go wrong. The previous coding
got this completely wrong for parallel joins.
Unfortunately, this change may destabilize plans for users of 9.6 who
have enabled parallel query, but since 9.6 is still fairly new I'm
hoping expectations won't be too settled yet. Also, this is really a
brown-paper-bag bug, so leaving it unfixed for the entire lifetime of
9.6 seems unwise.
Related reports (whose import I initially failed to recognize) by
Tomas Vondra and Tom Lane.
Discussion: http://postgr.es/m/CA+TgmoaDxZ5z5Kw_oCQoymNxNoVaTCXzPaODcOuao=CzK8dMZw@mail.gmail.com
RelationGetPartitionQual() and generate_partition_qual() are always
called with recurse = true, so we don't need an argument for that.
Extracted by me from a larger patch by Amit Langote.
This shouldn't change the set of paths that get generated in any
way, but it is preparatory work for further changes to allow a
partial path to be merge-joined witih a non-partial path to produce
a partial join path.
Dilip Kumar, with cosmetic adjustments by me.
This case wasn't thought through sufficiently in commit 100340e2d.
It's true that the FK proves that every outer row has a match in the
inner table, but we forgot that some of the inner rows might be filtered
away by WHERE conditions located within the semijoin's RHS.
If the RHS is just one table, we can reasonably take the semijoin
selectivity as equal to the fraction of the referenced table's rows
that are expected to survive its restriction clauses.
If the RHS is a join, it's not clear how much of the referenced table
might get through the join, so fall back to the same rule we were
already using for other outer-join cases: use the minimum of the
regular per-clause selectivity estimates. This gives the same result
as if we hadn't considered the FK at all when there's a single FK
column, but it should still help for multi-column FKs, which is the
case that 100340e2d is really meant to help with.
Back-patch to 9.6 where the previous commit came in.
Discussion: https://postgr.es/m/16149.1481835103@sss.pgh.pa.us
Andrew Gierth
Kevin Grittner
Robert Haas
Peter Eisentraut
Tom Lane
Andres Freund
Alvaro Herrera
Heikki Linnakangas
Bruce Momjian