When the input value to a CoerceToDomain expression node is a read-write
expanded datum, we should pass a read-only pointer to any domain CHECK
expressions and then return the original read-write pointer as the
expression result. Previously we were blindly passing the same pointer to
all the consumers of the value, making it possible for a function in CHECK
to modify or even delete the expanded value. (Since a plpgsql function
will absorb a passed-in read-write expanded array as a local variable
value, it will in fact delete the value on exit.)
A similar hazard of passing the same read-write pointer to multiple
consumers exists in domain_check() and in ExecEvalCase, so fix those too.
The fix requires adding MakeExpandedObjectReadOnly calls at the appropriate
places, which is simple enough except that we need to get the data type's
typlen from somewhere. For the domain cases, solve this by redefining
DomainConstraintRef.tcache as okay for callers to access; there wasn't any
reason for the original convention against that, other than not wanting the
API of typcache.c to be any wider than it had to be. For CASE, there's
no good solution except to add a syscache lookup during executor start.
Per bug #14472 from Marcos Castedo. Back-patch to 9.5 where expanded
values were introduced.
Discussion: https://postgr.es/m/15225.1482431619@sss.pgh.pa.us
ExecEvalCase() tried to save a cycle or two by passing
&econtext->caseValue_isNull as the isNull argument to its sub-evaluation of
the CASE value expression. If that subexpression itself contained a CASE,
then *isNull was an alias for econtext->caseValue_isNull within the
recursive call of ExecEvalCase(), leading to confusion about whether the
inner call's caseValue was null or not. In the worst case this could lead
to a core dump due to dereferencing a null pointer. Fix by not assigning
to the global variable until control comes back from the subexpression.
Also, avoid using the passed-in isNull pointer transiently for evaluation
of WHEN expressions. (Either one of these changes would have been
sufficient to fix the known misbehavior, but it's clear now that each of
these choices was in itself dangerous coding practice and best avoided.
There do not seem to be any similar hazards elsewhere in execQual.c.)
Also, it was possible for inlining of a SQL function that implements the
equality operator used for a CASE comparison to result in one CASE
expression's CaseTestExpr node being inserted inside another CASE
expression. This would certainly result in wrong answers since the
improperly nested CaseTestExpr would be caused to return the inner CASE's
comparison value not the outer's. If the CASE values were of different
data types, a crash might result; moreover such situations could be abused
to allow disclosure of portions of server memory. To fix, teach
inline_function to check for "bare" CaseTestExpr nodes in the arguments of
a function to be inlined, and avoid inlining if there are any.
Heikki Linnakangas, Michael Paquier, Tom Lane
Report: https://github.com/greenplum-db/gpdb/pull/327
Report: <4DDCEEB8.50602@enterprisedb.com>
Security: CVE-2016-5423
ExecMakeTableFunctionResult(), which is used in SELECT FROM function(...)
cases, formerly treated a simple NULL output from a function that both
returnsSet and returnsTuple as a violation of the SRF protocol. What seems
better is to treat a NULL output as equivalent to ROW(NULL,NULL,...).
Without this, cases such as SELECT FROM unnest(...) on an array of
composite are vulnerable to unexpected and not-very-helpful failures.
Old code comments here suggested an alternative of just ignoring
simple-NULL outputs, but that doesn't seem very principled.
This change had been hung up for a long time due to uncertainty about
how much we wanted to buy into the equivalence of simple NULL and
ROW(NULL,NULL,...). I think that's been mostly resolved by the discussion
around bug #14235, so let's go ahead and do it.
Per bug #7808 from Joe Van Dyk. Although this is a pretty old report,
fixing it smells a bit more like a new feature than a bug fix, and the
lack of other similar complaints suggests that we shouldn't take much risk
of destabilization by back-patching. (Maybe that could be revisited once
this patch has withstood some field usage.)
Andrew Gierth and Tom Lane
Report: <E1TurJE-0006Es-TK@wrigleys.postgresql.org>
The SQL standard appears to specify that IS [NOT] NULL's tests of field
nullness are non-recursive, ie, we shouldn't consider that a composite
field with value ROW(NULL,NULL) is null for this purpose.
ExecEvalNullTest got this right, but eval_const_expressions did not,
leading to weird inconsistencies depending on whether the expression
was such that the planner could apply constant folding.
Also, adjust the docs to mention that IS [NOT] DISTINCT FROM NULL can be
used as a substitute test if a simple null check is wanted for a rowtype
argument. That motivated reordering things so that IS [NOT] DISTINCT FROM
is described before IS [NOT] NULL. In HEAD, I went a bit further and added
a table showing all the comparison-related predicates.
Per bug #14235. Back-patch to all supported branches, since it's certainly
undesirable that constant-folding should change the semantics.
Report and patch by Andrew Gierth; assorted wordsmithing and revised
regression test cases by me.
Report: <20160708024746.1410.57282@wrigleys.postgresql.org>
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>
If a plan node output expression returns an "expanded" datum, and that
output column is referenced in more than one place in upper-level plan
nodes, we need to ensure that what is returned is a read-only reference
not a read/write reference. Otherwise one of the referencing sites could
scribble on or even delete the expanded datum before we have evaluated the
others. Commit 1dc5ebc9077ab742, which introduced this feature, supposed
that it'd be sufficient to make SubqueryScan nodes force their output
columns to read-only state. The folly of that was revealed by bug #14174
from Andrew Gierth, and really should have been immediately obvious
considering that the planner will happily optimize SubqueryScan nodes
out of the plan without any regard for this issue.
The safest fix seems to be to make ExecProject() force its results into
read-only state; that will cover every case where a plan node returns
expression results. Actually we can delegate this to ExecTargetList()
since we can recursively assume that plain Vars will not reference
read-write datums. That should keep the extra overhead down to something
minimal. We no longer need ExecMakeSlotContentsReadOnly(), which was
introduced only in support of the idea that just a few plan node types
would need to do this.
In the future it would be nice to have the planner account for this problem
and inject force-to-read-only expression evaluation nodes into only the
places where there's a risk of multiple evaluation. That's not a suitable
solution for 9.5 or even 9.6 at this point, though.
Report: <20160603124628.9932.41279@wrigleys.postgresql.org>
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.
Omitted boundaries represent the upper or lower limit of the corresponding
array subscript. This allows simpler specification of many common
use-cases.
(Revised version of commit 9246af6799819847faa33baf441251003acbb8fe)
YUriy Zhuravlev
If there are two different aggregates in the query with same inputs, and
the aggregates have the same initial condition and transition function,
only calculate the state value once, and only call the final functions
separately. For example, AVG(x) and SUM(x) aggregates have the same
transition function, which accumulates the sum and number of input tuples.
For a query like "SELECT AVG(x), SUM(x) FROM x", we can therefore
accumulate the state function only once, which gives a nice speedup.
David Rowley, reviewed and edited by me.
It's against project policy to use elog() for user-facing errors, or to
omit an errcode() selection for errors that aren't supposed to be "can't
happen" cases. Fix all the violations of this policy that result in
ERRCODE_INTERNAL_ERROR log entries during the standard regression tests,
as errors that can reliably be triggered from SQL surely should be
considered user-facing.
I also looked through all the files touched by this commit and fixed
other nearby problems of the same ilk. I do not claim to have fixed
all violations of the policy, just the ones in these files.
In a few places I also changed existing ERRCODE choices that didn't
seem particularly appropriate; mainly replacing ERRCODE_SYNTAX_ERROR
by something more specific.
Back-patch to 9.5, but no further; changing ERRCODE assignments in
stable branches doesn't seem like a good idea.
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
This patch introduces the ability for complex datatypes to have an
in-memory representation that is different from their on-disk format.
On-disk formats are typically optimized for minimal size, and in any case
they can't contain pointers, so they are often not well-suited for
computation. Now a datatype can invent an "expanded" in-memory format
that is better suited for its operations, and then pass that around among
the C functions that operate on the datatype. There are also provisions
(rudimentary as yet) to allow an expanded object to be modified in-place
under suitable conditions, so that operations like assignment to an element
of an array need not involve copying the entire array.
The initial application for this feature is arrays, but it is not hard
to foresee using it for other container types like JSON, XML and hstore.
I have hopes that it will be useful to PostGIS as well.
In this initial implementation, a few heuristics have been hard-wired
into plpgsql to improve performance for arrays that are stored in
plpgsql variables. We would like to generalize those hacks so that
other datatypes can obtain similar improvements, but figuring out some
appropriate APIs is left as a task for future work. (The heuristics
themselves are probably not optimal yet, either, as they sometimes
force expansion of arrays that would be better left alone.)
Preliminary performance testing shows impressive speed gains for plpgsql
functions that do element-by-element access or update of large arrays.
There are other cases that get a little slower, as a result of added array
format conversions; but we can hope to improve anything that's annoyingly
bad. In any case most applications should see a net win.
Tom Lane, reviewed by Andres Freund
Previously, we cached domain constraints for the life of a query, or
really for the life of the FmgrInfo struct that was used to invoke
domain_in() or domain_check(). But plpgsql (and probably other places)
are set up to cache such FmgrInfos for the whole lifespan of a session,
which meant they could be enforcing really stale sets of constraints.
On the other hand, searching pg_constraint once per query gets kind of
expensive too: testing says that as much as half the runtime of a
trivial query such as "SELECT 0::domaintype" went into that.
To fix this, delegate the responsibility for tracking a domain's
constraints to the typcache, which has the infrastructure needed to
detect syscache invalidation events that signal possible changes.
This not only removes unnecessary repeat reads of pg_constraint,
but ensures that we never apply stale constraint data: whatever we
use is the current data according to syscache rules.
Unfortunately, the current configuration of the system catalogs means
we have to flush cached domain-constraint data whenever either pg_type
or pg_constraint changes, which happens rather a lot (eg, creation or
deletion of a temp table will do it). It might be worth rearranging
things to split pg_constraint into two catalogs, of which the domain
constraint one would probably be very low-traffic. That's a job for
another patch though, and in any case this patch should improve matters
materially even with that handicap.
This patch makes use of the recently-added memory context reset callback
feature to manage the lifespan of domain constraint caches, so that we
don't risk deleting a cache that might be in the midst of evaluation.
Although this is a bug fix as well as a performance improvement, no
back-patch. There haven't been many if any field complaints about
stale domain constraint checks, so it doesn't seem worth taking the
risk of modifying data structures as basic as MemoryContexts in back
branches.
The four functions array_ref, array_set, array_get_slice, array_set_slice
have traditionally declared their array inputs and results as being of type
"ArrayType *". This is a lie, and has been since Berkeley days, because
they actually also support "fixed-length array" types such as "name" and
"point"; not to mention that the inputs could be toasted. These values
should be declared Datum instead to avoid confusion. The current coding
already risks possible misoptimization by compilers, and it'll get worse
when "expanded" array representations become a valid alternative.
However, there's a fair amount of code using array_ref and array_set with
arrays that *are* known to be ArrayType structures, and there might be more
such places in third-party code. Rather than cluttering those call sites
with PointerGetDatum/DatumGetArrayTypeP cruft, what I did was to rename the
existing functions to array_get_element/array_set_element, fix their
signatures, then reincarnate array_ref/array_set as backwards compatibility
wrappers.
array_get_slice/array_set_slice have no such constituency in the core code,
and probably not in third-party code either, so I just changed their APIs.
In commit bf7ca15875988a88e97302e012d7c4808bef3ea9 I introduced an
assumption that an RTE referenced by a whole-row Var must have a valid eref
field. This is false for RTEs constructed by DoCopy, and there are other
places taking similar shortcuts. Perhaps we should make all those places
go through addRangeTableEntryForRelation or its siblings instead of having
ad-hoc logic, but the most reliable fix seems to be to make the new code in
ExecEvalWholeRowVar cope if there's no eref. We can reasonably assume that
there's no need to insert column aliases if no aliases were provided.
Add a regression test case covering this, and also verifying that a sane
column name is in fact available in this situation.
Although the known case only crashes in 9.4 and HEAD, it seems prudent to
back-patch the code change to 9.2, since all the ingredients for a similar
failure exist in the variant patch applied to 9.3 and 9.2.
Per report from Jean-Pierre Pelletier.
At one time it wasn't terribly important what column names were associated
with the fields of a composite Datum, but since the introduction of
operations like row_to_json(), it's important that looking up the rowtype
ID embedded in the Datum returns the column names that users would expect.
That did not work terribly well before this patch: you could get the column
names of the underlying table, or column aliases from any level of the
query, depending on minor details of the plan tree. You could even get
totally empty field names, which is disastrous for cases like row_to_json().
To fix this for whole-row Vars, look to the RTE referenced by the Var, and
make sure its column aliases are applied to the rowtype associated with
the result Datums. This is a tad scary because we might have to return
a transient RECORD type even though the Var is declared as having some
named rowtype. In principle it should be all right because the record
type will still be physically compatible with the named rowtype; but
I had to weaken one Assert in ExecEvalConvertRowtype, and there might be
third-party code containing similar assumptions.
Similarly, RowExprs have to be willing to override the column names coming
from a named composite result type and produce a RECORD when the column
aliases visible at the site of the RowExpr differ from the underlying
table's column names.
In passing, revert the decision made in commit 398f70ec070fe601 to add
an alias-list argument to ExecTypeFromExprList: better to provide that
functionality in a separate function. This also reverts most of the code
changes in d68581483564ec0f, which we don't need because we're no longer
depending on the tupdesc found in the child plan node's result slot to be
blessed.
Back-patch to 9.4, but not earlier, since this solution changes the results
in some cases that users might not have realized were buggy. We'll apply a
more restricted form of this patch in older branches.
ExecEvalWholeRowVar incorrectly supposed that it could "bless" the source
TupleTableSlot just once per query. But if the input is coming from an
Append (or, perhaps, other cases?) more than one slot might be returned
over the query run. This led to "record type has not been registered"
errors when a composite datum was extracted from a non-blessed slot.
This bug has been there a long time; I guess it escaped notice because when
dealing with subqueries the planner tends to expand whole-row Vars into
RowExprs, which don't have the same problem. It is possible to trigger
the problem in all active branches, though, as illustrated by the added
regression test.
ExecMakeTableFunctionResult evaluated the arguments for a function-in-FROM
in the query-lifespan memory context. This is insignificant in simple
cases where the function relation is scanned only once; but if the function
is in a sub-SELECT or is on the inside of a nested loop, any memory
consumed during argument evaluation can add up quickly. (The potential for
trouble here had been foreseen long ago, per existing comments; but we'd
not previously seen a complaint from the field about it.) To fix, create
an additional temporary context just for this purpose.
Per an example from MauMau. Back-patch to all active branches.
If we have an array of records stored on disk, the individual record fields
cannot contain out-of-line TOAST pointers: the tuptoaster.c mechanisms are
only prepared to deal with TOAST pointers appearing in top-level fields of
a stored row. The same applies for ranges over composite types, nested
composites, etc. However, the existing code only took care of expanding
sub-field TOAST pointers for the case of nested composites, not for other
structured types containing composites. For example, given a command such
as
UPDATE tab SET arraycol = ARRAY[(ROW(x,42)::mycompositetype] ...
where x is a direct reference to a field of an on-disk tuple, if that field
is long enough to be toasted out-of-line then the TOAST pointer would be
inserted as-is into the array column. If the source record for x is later
deleted, the array field value would become a dangling pointer, leading
to errors along the line of "missing chunk number 0 for toast value ..."
when the value is referenced. A reproducible test case for this was
provided by Jan Pecek, but it seems likely that some of the "missing chunk
number" reports we've heard in the past were caused by similar issues.
Code-wise, the problem is that PG_DETOAST_DATUM() is not adequate to
produce a self-contained Datum value if the Datum is of composite type.
Seen in this light, the problem is not just confined to arrays and ranges,
but could also affect some other places where detoasting is done in that
way, for example form_index_tuple().
I tried teaching the array code to apply toast_flatten_tuple_attribute()
along with PG_DETOAST_DATUM() when the array element type is composite,
but this was messy and imposed extra cache lookup costs whether or not any
TOAST pointers were present, indeed sometimes when the array element type
isn't even composite (since sometimes it takes a typcache lookup to find
that out). The idea of extending that approach to all the places that
currently use PG_DETOAST_DATUM() wasn't attractive at all.
This patch instead solves the problem by decreeing that composite Datum
values must not contain any out-of-line TOAST pointers in the first place;
that is, we expand out-of-line fields at the point of constructing a
composite Datum, not at the point where we're about to insert it into a
larger tuple. This rule is applied only to true composite Datums, not
to tuples that are being passed around the system as tuples, so it's not
as invasive as it might sound at first. With this approach, the amount
of code that has to be touched for a full solution is greatly reduced,
and added cache lookup costs are avoided except when there actually is
a TOAST pointer that needs to be inlined.
The main drawback of this approach is that we might sometimes dereference
a TOAST pointer that will never actually be used by the query, imposing a
rather large cost that wasn't there before. On the other side of the coin,
if the field value is used multiple times then we'll come out ahead by
avoiding repeat detoastings. Experimentation suggests that common SQL
coding patterns are unaffected either way, though. Applications that are
very negatively affected could be advised to modify their code to not fetch
columns they won't be using.
In future, we might consider reverting this solution in favor of detoasting
only at the point where data is about to be stored to disk, using some
method that can drill down into multiple levels of nested structured types.
That will require defining new APIs for structured types, though, so it
doesn't seem feasible as a back-patchable fix.
Note that this patch changes HeapTupleGetDatum() from a macro to a function
call; this means that any third-party code using that macro will not get
protection against creating TOAST-pointer-containing Datums until it's
recompiled. The same applies to any uses of PG_RETURN_HEAPTUPLEHEADER().
It seems likely that this is not a big problem in practice: most of the
tuple-returning functions in core and contrib produce outputs that could
not possibly be toasted anyway, and the same probably holds for third-party
extensions.
This bug has existed since TOAST was invented, so back-patch to all
supported branches.
In commit c1352052ef1d4eeb2eb1d822a207ddc2d106cb13, I implemented an
optimization that assumed that a function's argument expressions would
either always return a set (ie multiple rows), or always not. This is
wrong however: we allow CASE expressions in which some arms return a set
of some type and others just return a scalar of that type. There may be
other examples as well. To fix, replace the run-time test of whether an
argument returned a set with a static precheck (expression_returns_set).
This adds a little bit of query startup overhead, but it seems barely
measurable.
Per bug #8228 from David Johnston. This has been broken since 8.0,
so patch all supported branches.
This patch introduces generic support for ordered-set and hypothetical-set
aggregate functions, as well as implementations of the instances defined in
SQL:2008 (percentile_cont(), percentile_disc(), rank(), dense_rank(),
percent_rank(), cume_dist()). We also added mode() though it is not in the
spec, as well as versions of percentile_cont() and percentile_disc() that
can compute multiple percentile values in one pass over the data.
Unlike the original submission, this patch puts full control of the sorting
process in the hands of the aggregate's support functions. To allow the
support functions to find out how they're supposed to sort, a new API
function AggGetAggref() is added to nodeAgg.c. This allows retrieval of
the aggregate call's Aggref node, which may have other uses beyond the
immediate need. There is also support for ordered-set aggregates to
install cleanup callback functions, so that they can be sure that
infrastructure such as tuplesort objects gets cleaned up.
In passing, make some fixes in the recently-added support for variadic
aggregates, and make some editorial adjustments in the recent FILTER
additions for aggregates. Also, simplify use of IsBinaryCoercible() by
allowing it to succeed whenever the target type is ANY or ANYELEMENT.
It was inconsistent that it dealt with other polymorphic target types
but not these.
Atri Sharma and Andrew Gierth; reviewed by Pavel Stehule and Vik Fearing,
and rather heavily editorialized upon by Tom Lane
This is SQL-standard with a few extensions, namely support for
subqueries and outer references in clause expressions.
catversion bump due to change in Aggref and WindowFunc.
David Fetter, reviewed by Dean Rasheed.
In a construct like "select plain_function(set_returning_function(...))",
the plain function is applied to each output row of the SRF successively.
If some of the SRF outputs are NULL, and the plain function is strict,
you'd expect to get NULL results for such rows ... but what actually
happened was that such rows were omitted entirely from the result set.
This was due to confusion of this case with what should happen for nested
set-returning functions; a strict SRF is indeed supposed to yield an empty
set for null input. Per bug #8150 from Erwin Brandstetter.
Although this has been broken forever, we're not back-patching because
of the possibility that some apps out there expect the incorrect behavior.
This change should be listed as a possible incompatibility in the 9.3
release notes.
If an FDW fails to take special measures with a CurrentOfExpr, we will
end up trying to execute it as an ordinary qual, which was being treated
as a purely internal failure condition. Provide a more user-oriented
error message for such cases.
This patch addresses the problem that applications currently have to
extract object names from possibly-localized textual error messages,
if they want to know for example which index caused a UNIQUE_VIOLATION
failure. It adds new error message fields to the wire protocol, which
can carry the name of a table, table column, data type, or constraint
associated with the error. (Since the protocol spec has always instructed
clients to ignore unrecognized field types, this should not create any
compatibility problem.)
Support for providing these new fields has been added to just a limited set
of error reports (mainly, those in the "integrity constraint violation"
SQLSTATE class), but we will doubtless add them to more calls in future.
Pavel Stehule, reviewed and extensively revised by Peter Geoghegan, with
additional hacking by Tom Lane.
This reduces unnecessary exposure of other headers through htup.h, which
is very widely included by many files.
I have chosen to move the function prototypes to the new file as well,
because that means htup.h no longer needs to include tupdesc.h. In
itself this doesn't have much effect in indirect inclusion of tupdesc.h
throughout the tree, because it's also required by execnodes.h; but it's
something to explore in the future, and it seemed best to do the htup.h
change now while I'm busy with it.
When a whole-row Var is reading the result of a subquery, we need it to
ignore any "resjunk" columns that the subquery might have evaluated for
GROUP BY or ORDER BY purposes. We've hacked this area before, in commit
68e40998d058c1f6662800a648ff1e1ce5d99cba, but that fix only covered
whole-row Vars of named composite types, not those of RECORD type; and it
was mighty klugy anyway, since it just assumed without checking that any
extra columns in the result must be resjunk. A proper fix requires getting
hold of the subquery's targetlist so we can actually see which columns are
resjunk (whereupon we can use a JunkFilter to get rid of them). So bite
the bullet and add some infrastructure to make that possible.
Per report from Andrew Dunstan and additional testing by Merlin Moncure.
Back-patch to all supported branches. In 8.3, also back-patch commit
292176a118da6979e5d368a4baf27f26896c99a5, which for some reason I had
not done at the time, but it's a prerequisite for this change.
The hstore and json datatypes both have record-conversion functions that
pay attention to column names in the composite values they're handed.
We used to not worry about inserting correct field names into tuple
descriptors generated at runtime, but given these examples it seems
useful to do so. Observe the nicer-looking results in the regression
tests whose results changed.
catversion bump because there is a subtle change in requirements for stored
rule parsetrees: RowExprs from ROW() constructs now have to include field
names.
Andrew Dunstan and Tom Lane
This commit changes index-only scans so that data is read directly from the
index tuple without first generating a faux heap tuple. The only immediate
benefit is that indexes on system columns (such as OID) can be used in
index-only scans, but this is necessary infrastructure if we are ever to
support index-only scans on expression indexes. The executor is now ready
for that, though the planner still needs substantial work to recognize
the possibility.
To do this, Vars in index-only plan nodes have to refer to index columns
not heap columns. I introduced a new special varno, INDEX_VAR, to mark
such Vars to avoid confusion. (In passing, this commit renames the two
existing special varnos to OUTER_VAR and INNER_VAR.) This allows
ruleutils.c to handle them with logic similar to what we use for subplan
reference Vars.
Since index-only scans are now fundamentally different from regular
indexscans so far as their expression subtrees are concerned, I also chose
to change them to have their own plan node type (and hence, their own
executor source file).
Since collation is effectively an argument, not a property of the function,
FmgrInfo is really the wrong place for it; and this becomes critical in
cases where a cached FmgrInfo is used for varying purposes that might need
different collation settings. Fix by passing it in FunctionCallInfoData
instead. In particular this allows a clean fix for bug #5970 (record_cmp
not working). This requires touching a bit more code than the original
method, but nobody ever thought that collations would not be an invasive
patch...
In nearly all cases, the caller already knows the correct collation, and
in a number of places, the value the caller has handy is more correct than
the default for the type would be. (In particular, this patch makes it
significantly less likely that eval_const_expressions will result in
changing the exposed collation of an expression.) So an internal lookup
is both expensive and wrong.
All expression nodes now have an explicit output-collation field, unless
they are known to only return a noncollatable data type (such as boolean
or record). Also, nodes that can invoke collation-aware functions store
a separate field that is the collation value to pass to the function.
This avoids confusion that arises when a function has collatable inputs
and noncollatable output type, or vice versa.
Also, replace the parser's on-the-fly collation assignment method with
a post-pass over the completed expression tree. This allows us to use
a more complex (and hopefully more nearly spec-compliant) assignment
rule without paying for it in extra storage in every expression node.
Fix assorted bugs in the planner's handling of collations by making
collation one of the defining properties of an EquivalenceClass and
by converting CollateExprs into discardable RelabelType nodes during
expression preprocessing.
CollateClause is now used only in raw grammar output, and CollateExpr after
parse analysis. This is for clarity and to avoid carrying collation names
in post-analysis parse trees: that's both wasteful and possibly misleading,
since the collation's name could be changed while the parsetree still
exists.
Also, clean up assorted infelicities and omissions in processing of the
node type.
This adds collation support for columns and domains, a COLLATE clause
to override it per expression, and B-tree index support.
Peter Eisentraut
reviewed by Pavel Stehule, Itagaki Takahiro, Robert Haas, Noah Misch
