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 9246af6799)
YUriy Zhuravlev
Defer lookup of opfamily and input type of a of a user specified opclass
until the optimizer selects among available unique indexes; and store
the opclass in the parse analyzed tree instead. The primary reason for
doing this is that for rule deparsing it's easier to use the opclass
than the previous representation.
While at it also rename a variable in the inference code to better fit
it's purpose.
This is separate from the actual fixes for deparsing to make review
easier.
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
Commit e7cb7ee145 included some design
decisions that seem pretty questionable to me, and there was quite a lot
of stuff not to like about the documentation and comments. Clean up
as follows:
* Consider foreign joins only between foreign tables on the same server,
rather than between any two foreign tables with the same underlying FDW
handler function. In most if not all cases, the FDW would simply have had
to apply the same-server restriction itself (far more expensively, both for
lack of caching and because it would be repeated for each combination of
input sub-joins), or else risk nasty bugs. Anyone who's really intent on
doing something outside this restriction can always use the
set_join_pathlist_hook.
* Rename fdw_ps_tlist/custom_ps_tlist to fdw_scan_tlist/custom_scan_tlist
to better reflect what they're for, and allow these custom scan tlists
to be used even for base relations.
* Change make_foreignscan() API to include passing the fdw_scan_tlist
value, since the FDW is required to set that. Backwards compatibility
doesn't seem like an adequate reason to expect FDWs to set it in some
ad-hoc extra step, and anyway existing FDWs can just pass NIL.
* Change the API of path-generating subroutines of add_paths_to_joinrel,
and in particular that of GetForeignJoinPaths and set_join_pathlist_hook,
so that various less-used parameters are passed in a struct rather than
as separate parameter-list entries. The objective here is to reduce the
probability that future additions to those parameter lists will result in
source-level API breaks for users of these hooks. It's possible that this
is even a small win for the core code, since most CPU architectures can't
pass more than half a dozen parameters efficiently anyway. I kept root,
joinrel, outerrel, innerrel, and jointype as separate parameters to reduce
code churn in joinpath.c --- in particular, putting jointype into the
struct would have been problematic because of the subroutines' habit of
changing their local copies of that variable.
* Avoid ad-hocery in ExecAssignScanProjectionInfo. It was probably all
right for it to know about IndexOnlyScan, but if the list is to grow
we should refactor the knowledge out to the callers.
* Restore nodeForeignscan.c's previous use of the relcache to avoid
extra GetFdwRoutine lookups for base-relation scans.
* Lots of cleanup of documentation and missed comments. Re-order some
code additions into more logical places.
The newly added ON CONFLICT clause allows to specify an alternative to
raising a unique or exclusion constraint violation error when inserting.
ON CONFLICT refers to constraints that can either be specified using a
inference clause (by specifying the columns of a unique constraint) or
by naming a unique or exclusion constraint. DO NOTHING avoids the
constraint violation, without touching the pre-existing row. DO UPDATE
SET ... [WHERE ...] updates the pre-existing tuple, and has access to
both the tuple proposed for insertion and the existing tuple; the
optional WHERE clause can be used to prevent an update from being
executed. The UPDATE SET and WHERE clauses have access to the tuple
proposed for insertion using the "magic" EXCLUDED alias, and to the
pre-existing tuple using the table name or its alias.
This feature is often referred to as upsert.
This is implemented using a new infrastructure called "speculative
insertion". It is an optimistic variant of regular insertion that first
does a pre-check for existing tuples and then attempts an insert. If a
violating tuple was inserted concurrently, the speculatively inserted
tuple is deleted and a new attempt is made. If the pre-check finds a
matching tuple the alternative DO NOTHING or DO UPDATE action is taken.
If the insertion succeeds without detecting a conflict, the tuple is
deemed inserted.
To handle the possible ambiguity between the excluded alias and a table
named excluded, and for convenience with long relation names, INSERT
INTO now can alias its target table.
Bumps catversion as stored rules change.
Author: Peter Geoghegan, with significant contributions from Heikki
Linnakangas and Andres Freund. Testing infrastructure by Jeff Janes.
Reviewed-By: Heikki Linnakangas, Andres Freund, Robert Haas, Simon Riggs,
Dean Rasheed, Stephen Frost and many others.
Use a different A_Expr_Kind for LIKE/ILIKE/SIMILAR TO constructs, so that
they can be distinguished from direct invocation of the underlying
operators. Also, postpone selection of the operator name when transforming
"x IN (select)" to "x = ANY (select)", so that those syntaxes can be told
apart at parse analysis time.
I had originally thought I'd also have to do something special for the
syntaxes IS NOT DISTINCT FROM, IS NOT DOCUMENT, and x NOT IN (SELECT...),
which the grammar translates as though they were NOT (construct).
On reflection though, we can distinguish those cases reliably by noting
whether the parse location shown for the NOT is the same as for its child
node. This only requires tweaking the parse locations for NOT IN, which
I've done here.
These changes should have no effect outside the parser; they're just in
support of being able to give accurate warnings for planned operator
precedence changes.
We did not need a location tag on NullTest or BooleanTest before, because
no error messages referred directly to their locations. That's planned
to change though, so add these fields in a separate housekeeping commit.
Catversion bump because stored rules may change.
This SQL-standard feature allows a sub-SELECT yielding multiple columns
(but only one row) to be used to compute the new values of several columns
to be updated. While the same results can be had with an independent
sub-SELECT per column, such a workaround can require a great deal of
duplicated computation.
The standard actually says that the source for a multi-column assignment
could be any row-valued expression. The implementation used here is
tightly tied to our existing sub-SELECT support and can't handle other
cases; the Bison grammar would have some issues with them too. However,
I don't feel too bad about this since other cases can be converted into
sub-SELECTs. For instance, "SET (a,b,c) = row_valued_function(x)" could
be written "SET (a,b,c) = (SELECT * FROM row_valued_function(x))".
Since most of the system thinks AND and OR are N-argument expressions
anyway, let's have the grammar generate a representation of that form when
dealing with input like "x AND y AND z AND ...", rather than generating
a deeply-nested binary tree that just has to be flattened later by the
planner. This avoids stack overflow in parse analysis when dealing with
queries having more than a few thousand such clauses; and in any case it
removes some rather unsightly inconsistencies, since some parts of parse
analysis were generating N-argument ANDs/ORs already.
It's still possible to get a stack overflow with weirdly parenthesized
input, such as "x AND (y AND (z AND ( ... )))", but such cases are not
mainstream usage. The maximum depth of parenthesization is already
limited by Bison's stack in such cases, anyway, so that the limit is
probably fairly platform-independent.
Patch originally by Gurjeet Singh, heavily revised by me
For variadic functions (other than VARIADIC ANY), the syntaxes foo(x,y,...)
and foo(VARIADIC ARRAY[x,y,...]) should be considered equivalent, since the
former is converted to the latter at parse time. They have indeed been
equivalent, in all releases before 9.3. However, commit 75b39e790 made an
ill-considered decision to record which syntax had been used in FuncExpr
nodes, and then to make equal() test that in checking node equality ---
which caused the syntaxes to not be seen as equivalent by the planner.
This is the underlying cause of bug #9817 from Dmitry Ryabov.
It might seem that a quick fix would be to make equal() disregard
FuncExpr.funcvariadic, but the same commit made that untenable, because
the field actually *is* semantically significant for some VARIADIC ANY
functions. This patch instead adopts the approach of redefining
funcvariadic (and aggvariadic, in HEAD) as meaning that the last argument
is a variadic array, whether it got that way by parser intervention or was
supplied explicitly by the user. Therefore the value will always be true
for non-ANY variadic functions, restoring the principle of equivalence.
(However, the planner will continue to consider use of VARIADIC as a
meaningful difference for VARIADIC ANY functions, even though some such
functions might disregard it.)
In HEAD, this change lets us simplify the decompilation logic in
ruleutils.c, since the funcvariadic/aggvariadic flag tells directly whether
to print VARIADIC. However, in 9.3 we have to continue to cope with
existing stored rules/views that might contain the previous definition.
Fortunately, this just means no change in ruleutils.c, since its existing
behavior effectively ignores funcvariadic for all cases other than VARIADIC
ANY functions.
In HEAD, bump catversion to reflect the fact that FuncExpr.funcvariadic
changed meanings; this is sort of pro forma, since I don't believe any
built-in views are affected.
Unfortunately, this patch doesn't magically fix everything for affected
9.3 users. After installing 9.3.5, they might need to recreate their
rules/views/indexes containing variadic function calls in order to get
everything consistent with the new definition. As in the cited bug,
the symptom of a problem would be failure to use a nominally matching
index that has a variadic function call in its definition. We'll need
to mention this in the 9.3.5 release notes.
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
There's no inherent reason why an aggregate function can't be variadic
(even VARIADIC ANY) if its transition function can handle the case.
Indeed, this patch to add the feature touches none of the planner or
executor, and little of the parser; the main missing stuff was DDL and
pg_dump support.
It is true that variadic aggregates can create the same sort of ambiguity
about parameters versus ORDER BY keys that was complained of when we
(briefly) had both one- and two-argument forms of string_agg(). However,
the policy formed in response to that discussion only said that we'd not
create any built-in aggregates with varying numbers of arguments, not that
we shouldn't allow users to do it. So the logical extension of that is
we can allow users to make variadic aggregates as long as we're wary about
shipping any such in core.
In passing, this patch allows aggregate function arguments to be named, to
the extent of remembering the names in pg_proc and dumping them in pg_dump.
You can't yet call an aggregate using named-parameter notation. That seems
like a likely future extension, but it'll take some work, and it's not what
this patch is really about. Likewise, there's still some work needed to
make window functions handle VARIADIC fully, but I left that for another
day.
initdb forced because of new aggvariadic field in Aggref parse nodes.
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.
Revert the matview-related changes in explain.c's API, as per recent
complaint from Robert Haas. The reason for these appears to have been
principally some ill-considered choices around having intorel_startup do
what ought to be parse-time checking, plus a poor arrangement for passing
it the view parsetree it needs to store into pg_rewrite when creating a
materialized view. Do the latter by having parse analysis stick a copy
into the IntoClause, instead of doing it at runtime. (On the whole,
I seriously question the choice to represent CREATE MATERIALIZED VIEW as a
variant of SELECT INTO/CREATE TABLE AS, because that means injecting even
more complexity into what was already a horrid legacy kluge. However,
I didn't go so far as to rethink that choice ... yet.)
I also moved several error checks into matview parse analysis, and
made the check for external Params in a matview more accurate.
In passing, clean things up a bit more around interpretOidsOption(),
and fix things so that we can use that to force no-oids for views,
sequences, etc, thereby eliminating the need to cons up "oids = false"
options when creating them.
catversion bump due to change in IntoClause. (I wonder though if we
really need readfuncs/outfuncs support for IntoClause anymore.)
A materialized view has a rule just like a view and a heap and
other physical properties like a table. The rule is only used to
populate the table, references in queries refer to the
materialized data.
This is a minimal implementation, but should still be useful in
many cases. Currently data is only populated "on demand" by the
CREATE MATERIALIZED VIEW and REFRESH MATERIALIZED VIEW statements.
It is expected that future releases will add incremental updates
with various timings, and that a more refined concept of defining
what is "fresh" data will be developed. At some point it may even
be possible to have queries use a materialized in place of
references to underlying tables, but that requires the other
above-mentioned features to be working first.
Much of the documentation work by Robert Haas.
Review by Noah Misch, Thom Brown, Robert Haas, Marko Tiikkaja
Security review by KaiGai Kohei, with a decision on how best to
implement sepgsql still pending.
Originally we didn't bother to mark FuncExprs with any indication whether
VARIADIC had been given in the source text, because there didn't seem to be
any need for it at runtime. However, because we cannot fold a VARIADIC ANY
function's arguments into an array (since they're not necessarily all the
same type), we do actually need that information at runtime if VARIADIC ANY
functions are to respond unsurprisingly to use of the VARIADIC keyword.
Add the missing field, and also fix ruleutils.c so that VARIADIC ANY
function calls are dumped properly.
Extracted from a larger patch that also fixes concat() and format() (the
only two extant VARIADIC ANY functions) to behave properly when VARIADIC is
specified. This portion seems appropriate to review and commit separately.
Pavel Stehule
transformExpr() is required to cope with already-transformed expression
trees, for various ugly-but-not-quite-worth-cleaning-up reasons. However,
some of its newer subroutines hadn't gotten the memo. This accounts for
bug #7763 from Norbert Buchmuller: transformRowExpr() was overwriting the
previously determined type of a RowExpr during CREATE TABLE LIKE INCLUDING
INDEXES. Additional investigation showed that transformXmlExpr had the
same kind of problem, but all the other cases seem to be safe.
Andres Freund and Tom Lane
This change ensures that the planner will see implicit and explicit casts
as equivalent for all purposes, except in the minority of cases where
there's actually a semantic difference (as reflected by having a 3-argument
cast function). In particular, this fixes cases where the EquivalenceClass
machinery failed to consider two references to a varchar column as
equivalent if one was implicitly cast to text but the other was explicitly
cast to text, as seen in bug #7598 from Vaclav Juza. We have had similar
bugs before in other parts of the planner, so I think it's time to fix this
problem at the core instead of continuing to band-aid around it.
Remove set_coercionform_dontcare(), which represents the band-aid
previously in use for allowing matching of index and constraint expressions
with inconsistent cast labeling. (We can probably get rid of
COERCE_DONTCARE altogether, but I don't think removing that enum value in
back branches would be wise; it's possible there's third party code
referring to it.)
Back-patch to 9.2. We could go back further, and might want to once this
has been tested more; but for the moment I won't risk destabilizing plan
choices in long-since-stable branches.
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
The WITH [NO] DATA option was not supported, nor the ability to specify
replacement column names; the former limitation wasn't even documented, as
per recent complaint from Naoya Anzai. Fix by moving the responsibility
for supporting these options into the executor. It actually takes less
code this way ...
catversion bump due to change in representation of IntoClause, which might
affect stored rules.
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).
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
This commit replaces pg_class.relistemp with pg_class.relpersistence;
and also modifies the RangeVar node type to carry relpersistence rather
than istemp. It also removes removes rd_istemp from RelationData and
instead performs the correct computation based on relpersistence.
For clarity, we add three new macros: RelationNeedsWAL(),
RelationUsesLocalBuffers(), and RelationUsesTempNamespace(), so that we
can clarify the purpose of each check that previous depended on
rd_istemp.
This is intended as infrastructure for the upcoming unlogged tables
patch, as well as for future possible work on global temporary tables.
relation using the general PARAM_EXEC executor parameter mechanism, rather
than the ad-hoc kluge of passing the outer tuple down through ExecReScan.
The previous method was hard to understand and could never be extended to
handle parameters coming from multiple join levels. This patch doesn't
change the set of possible plans nor have any significant performance effect,
but it's necessary infrastructure for future generalization of the concept
of an inner indexscan plan.
ExecReScan's second parameter is now unused, so it's removed.
8.2beta but never carried out. This avoids repetitive tests of whether the
argument is of scalar or composite type. Also, be a bit more paranoid about
composite arguments in some places where we previously weren't checking.
non-kluge method for controlling the order in which values are fed to an
aggregate function. At the same time eliminate the old implementation
restriction that DISTINCT was only supported for single-argument aggregates.
Possibly release-notable behavioral change: formerly, agg(DISTINCT x)
dropped null values of x unconditionally. Now, it does so only if the
agg transition function is strict; otherwise nulls are treated as DISTINCT
normally would, ie, you get one copy.
Andrew Gierth, reviewed by Hitoshi Harada
This alters various incidental uses of C++ key words to use other similar
identifiers, so that a C++ compiler won't choke outright. You still
(probably) need extern "C" { }; around the inclusion of backend headers.
based on a patch by Kurt Harriman <harriman@acm.org>
Also add a script cpluspluscheck to check for C++ compatibility in the
future. As of right now, this passes without error for me.
Bruce Momjian
Tom Lane
Andres Freund
Noah Misch
Kevin Grittner
Peter Eisentraut
Robert Haas
Magnus Hagander