In a race case, EXPLAIN ANALYZE could fail to display correct nbatch
and size information. Refactor so that participants report only on
batches they worked on rather than trying to report on all of them,
and teach explain.c to consider the HashInstrumentation object from
all participants instead of picking the first one it can find. This
should fix an occasional build farm failure in the "join" regression
test.
Author: Thomas Munro
Reviewed-By: Andres Freund
Discussion: https://postgr.es/m/30219.1514428346%40sss.pgh.pa.us
If a hash join appears in a parallel query, there may be no hash table
available for explain.c to inspect even though a hash table may have
been built in other processes. This could happen either because
parallel_leader_participation was set to off or because the leader
happened to hit the end of the outer relation immediately (even though
the complete relation is not empty) and decided not to build the hash
table.
Commit bf11e7ee introduced a way for workers to exchange
instrumentation via the DSM segment for Sort nodes even though they
are not parallel-aware. This commit does the same for Hash nodes, so
that explain.c has a way to find instrumentation data from an
arbitrary participant that actually built the hash table.
Author: Thomas Munro
Reviewed-By: Andres Freund
Discussion: https://postgr.es/m/CAEepm%3D3DUQC2-z252N55eOcZBer6DPdM%3DFzrxH9dZc5vYLsjaA%40mail.gmail.com
If a PARAM_EXEC parameter is used below a Gather (Merge) but the InitPlan
that computes it is attached to or above the Gather (Merge), force the
value to be computed before starting parallelism and pass it down to all
workers. This allows us to use parallelism in cases where it previously
would have had to be rejected as unsafe. We do - in this case - lose the
optimization that the value is only computed if it's actually used. An
alternative strategy would be to have the first worker that needs the value
compute it, but one downside of that approach is that we'd then need to
select a parallel-safe path to compute the parameter value; it couldn't for
example contain a Gather (Merge) node. At some point in the future, we
might want to consider both approaches.
Independent of that consideration, there is a great deal more work that
could be done to make more kinds of PARAM_EXEC parameters parallel-safe.
This infrastructure could be used to allow a Gather (Merge) on the inner
side of a nested loop (although that's not a very appealing plan) and
cases where the InitPlan is attached below the Gather (Merge) could be
addressed as well using various techniques. But this is a good start.
Amit Kapila, reviewed and revised by me. Reviewing and testing from
Kuntal Ghosh, Haribabu Kommi, and Tushar Ahuja.
Discussion: http://postgr.es/m/CAA4eK1LV0Y1AUV4cUCdC+sYOx0Z0-8NAJ2Pd9=UKsbQ5Sr7+JQ@mail.gmail.com
Haribabu Kommi, reviewed by Dilip Kumar and Rafia Sabih. Various
cosmetic changes by me to explain why this appears to be safe but
allowing inserts in parallel mode in general wouldn't be. Also, I
removed the REFRESH MATERIALIZED VIEW case from Haribabu's patch,
since I'm not convinced that case is OK, and hacked on the
documentation somewhat.
Discussion: http://postgr.es/m/CAJrrPGdo5bak6qnPWe8Kpi8g_jfQEs-G4SYmG9y+OFaw2-dPvA@mail.gmail.com
Up until now, when parallel query was used, no details about the
sort method or space used by the workers were available; details
were shown only for any sorting done by the leader. Fix that.
Commit 1177ab1dab forced the test case
added by commit 1f6d515a67 to run
without parallelism; now that we have this infrastructure, allow
that again, with a little tweaking to make it pass with and without
force_parallel_mode.
Robert Haas and Tom Lane
Discussion: http://postgr.es/m/CA+Tgmoa2VBZW6S8AAXfhpHczb=Rf6RqQ2br+zJvEgwJ0uoD_tQ@mail.gmail.com
Add a new EState member es_leaf_result_relations, so that the trigger
code knows about ResultRelInfos created by tuple routing. Also make
sure ExplainPrintTriggers knows about partition-related
ResultRelInfos.
Etsuro Fujita, reviewed by Amit Langote
Discussion: http://postgr.es/m/57163e18-8e56-da83-337a-22f2c0008051@lab.ntt.co.jp
Don't move parenthesized lines to the left, even if that means they
flow past the right margin.
By default, BSD indent lines up statement continuation lines that are
within parentheses so that they start just to the right of the preceding
left parenthesis. However, traditionally, if that resulted in the
continuation line extending to the right of the desired right margin,
then indent would push it left just far enough to not overrun the margin,
if it could do so without making the continuation line start to the left of
the current statement indent. That makes for a weird mix of indentations
unless one has been completely rigid about never violating the 80-column
limit.
This behavior has been pretty universally panned by Postgres developers.
Hence, disable it with indent's new -lpl switch, so that parenthesized
lines are always lined up with the preceding left paren.
This patch is much less interesting than the first round of indent
changes, but also bulkier, so I thought it best to separate the effects.
Discussion: https://postgr.es/m/E1dAmxK-0006EE-1r@gemulon.postgresql.org
Discussion: https://postgr.es/m/30527.1495162840@sss.pgh.pa.us
This extends the castNode() notation introduced by commit 5bcab1114 to
provide, in one step, extraction of a list cell's pointer and coercion to
a concrete node type. For example, "lfirst_node(Foo, lc)" is the same
as "castNode(Foo, lfirst(lc))". Almost half of the uses of castNode
that have appeared so far include a list extraction call, so this is
pretty widely useful, and it saves a few more keystrokes compared to the
old way.
As with the previous patch, back-patch the addition of these macros to
pg_list.h, so that the notation will be available when back-patching.
Patch by me, after an idea of Andrew Gierth's.
Discussion: https://postgr.es/m/14197.1491841216@sss.pgh.pa.us
If there can certainly be no more than one matching inner row for a given
outer row, then the executor can move on to the next outer row as soon as
it's found one match; there's no need to continue scanning the inner
relation for this outer row. This saves useless scanning in nestloop
and hash joins. In merge joins, it offers the opportunity to skip
mark/restore processing, because we know we have not advanced past the
first possible match for the next outer row.
Of course, the devil is in the details: the proof of uniqueness must
depend only on joinquals (not otherquals), and if we want to skip
mergejoin mark/restore then it must depend only on merge clauses.
To avoid adding more planning overhead than absolutely necessary,
the present patch errs in the conservative direction: there are cases
where inner_unique or skip_mark_restore processing could be used, but
it will not do so because it's not sure that the uniqueness proof
depended only on "safe" clauses. This could be improved later.
David Rowley, reviewed and rather heavily editorialized on by me
Discussion: https://postgr.es/m/CAApHDvqF6Sw-TK98bW48TdtFJ+3a7D2mFyZ7++=D-RyPsL76gw@mail.gmail.com
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
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
Previously, it was unsafe to execute a plan in parallel if
ExecutorRun() might be called with a non-zero row count. However,
it's quite easy to fix things up so that we can support that case,
provided that it is known that we will never call ExecutorRun() a
second time for the same QueryDesc. Add infrastructure to signal
this, and cross-checks to make sure that a caller who claims this is
true doesn't later reneg.
While that pattern never happens with queries received directly from a
client -- there's no way to know whether multiple Execute messages
will be sent unless the first one requests all the rows -- it's pretty
common for queries originating from procedural languages, which often
limit the result to a single tuple or to a user-specified number of
tuples.
This commit doesn't actually enable parallelism in any additional
cases, because currently none of the places that would be able to
benefit from this infrastructure pass CURSOR_OPT_PARALLEL_OK in the
first place, but it makes it much more palatable to pass
CURSOR_OPT_PARALLEL_OK in places where we currently don't, because it
eliminates some cases where we'd end up having to run the parallel
plan serially.
Patch by me, based on some ideas from Rafia Sabih and corrected by
Rafia Sabih based on feedback from Dilip Kumar and myself.
Discussion: http://postgr.es/m/CA+TgmobXEhvHbJtWDuPZM9bVSLiTj-kShxQJ2uM5GPDze9fRYA@mail.gmail.com
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
This exposes the existing explain summary option to users to allow them
to choose if they wish to have the planning time and totalled run time
included in the EXPLAIN result. The existing default behavior is
retained if SUMMARY is not specified- running explain without analyze
will not print the summary lines (just the planning time, currently)
while running explain with analyze will include the summary lines (both
the planning time and the totalled execution time).
Users who wish to see the summary information for plain explain can now
use: EXPLAIN (SUMMARY ON) query; Users who do not want to have the
summary printed for an analyze run can use:
EXPLAIN (ANALYZE ON, SUMMARY OFF) query;
With this, we can now also have EXPLAIN ANALYZE queries included in our
regression tests by using:
EXPLAIN (ANALYZE ON, TIMING OFF, SUMMARY off) query;
I went ahead and added an example of this, which will hopefully not make
the buildfarm complain.
Author: Ashutosh Bapat
Discussion: https://postgr.es/m/CAFjFpReE5z2h98U2Vuia8hcEkpRRwrauRjHmyE44hNv8-xk+XA@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
When I wrote commit ab1f0c822, I really missed the castNode() macro that
Peter E. had proposed shortly before. This back-fills the uses I would
have put it to. It's probably not all that significant, but there are
more assertions here than there were before, and conceivably they will
help catch any bugs associated with those representation changes.
I left behind a number of usages like "(Query *) copyObject(query_var)".
Those could have been converted as well, but Peter has proposed another
notational improvement that would handle copyObject cases automatically,
so I let that be for now.
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
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
With track_io_timing = on, EXPLAIN (ANALYZE, BUFFERS) will emit fields
named like "I/O Read Time". The slash makes that invalid as an XML
element name, so that adding FORMAT XML would produce invalid XML.
We already have code in there to translate spaces to dashes, so let's
generalize that to convert anything that isn't a valid XML name character,
viz letters, digits, hyphens, underscores, and periods. We could just
reject slashes, which would run a bit faster. But the fact that this went
unnoticed for so long doesn't give me a warm feeling that we'd notice the
next creative violation, so let's make it a permanent fix.
Reported by Markus Winand, though this isn't his initial patch proposal.
Back-patch to 9.2 where track_io_timing was added. The problem is only
latent in 9.1, so I don't feel a need to fix it there.
Discussion: <E0BF6A45-68E8-45E6-918F-741FB332C6BB@winand.at>
Add a location field to the DefElem struct, used to parse many utility
commands. Update various error messages to supply error position
information.
To propogate the error position information in a more systematic way,
create a ParseState in standard_ProcessUtility() and pass that to
interested functions implementing the utility commands. This seems
better than passing the query string and then reassembling a parse state
ad hoc, which violates the encapsulation of the ParseState type.
Reviewed-by: Pavel Stehule <pavel.stehule@gmail.com>
EXPLAIN (ANALYZE, TIMING OFF) would print an elapsed time of zero for
a trigger function, because no measurement has been taken but it printed
the field anyway. This isn't what EXPLAIN does elsewhere, so suppress it.
In the same vein, EXPLAIN (ANALYZE, BUFFERS) with non-text output format
would print buffer I/O timing numbers even when no measurement has been
taken because track_io_timing is off. That seems not per policy, either,
so change it.
Back-patch to 9.2 where these features were introduced.
Maksim Milyutin
Discussion: <081c0540-ecaa-bd29-3fd2-6358f3b359a9@postgrespro.ru>
We have, for a very long time, allowed the same subplan (same member of the
PlannedStmt.subplans list) to be referenced by more than one SubPlan node;
this avoids problems for cases such as subplans within an IndexScan's
indxqual and indxqualorig fields. However, EXPLAIN had not gotten the memo
and would print each reference as though it were an independent identical
subplan. To fix, track plan_ids of subplans we've printed and don't print
the same plan_id twice. Per report from Pavel Stehule.
BTW: the particular case of IndexScan didn't cause visible duplication
in a plain EXPLAIN, only EXPLAIN ANALYZE, because in the former case we
short-circuit executor startup before the indxqual field is processed by
ExecInitExpr. That seems like it could easily lead to other EXPLAIN
problems in future, but it's not clear how to avoid it without breaking
the "EXPLAIN a plan using hypothetical indexes" use-case. For now I've
left that issue alone.
Although this is a longstanding bug, it's purely cosmetic (no great harm
is done by the repeat printout) and we haven't had field complaints before.
So I'm hesitant to back-patch it, especially since there is some small risk
of ABI problems due to the need to add a new field to ExplainState.
In passing, rearrange order of fields in ExplainState to be less random,
and update some obsolete comments about when/where to initialize them.
Report: <CAFj8pRAimq+NK-menjt+3J4-LFoodDD8Or6=Lc_stcFD+eD4DA@mail.gmail.com>
In non-text output formats, parallelized aggregates were reporting
"Partial" or "Finalize" as a field named "Operation", which might be all
right in the absence of any context --- but other plan node types use that
field to report SQL-visible semantics, such as Select/Insert/Update/Delete.
So that naming choice didn't seem good to me. I changed it to "Partial
Mode".
Also, the field did not appear at all for a non-parallelized Agg plan node,
which is contrary to expectation in non-text formats. We're notionally
producing objects that conform to a schema, so the set of fields for a
given node type and EXPLAIN mode should be well-defined. I set it up to
fill in "Simple" in such cases.
Other fields that were added for parallel query, namely "Parallel Aware"
and Gather's "Single Copy", had not gotten the word on that point either.
Make them appear always in non-text output.
Also, the latter two fields were nominally producing boolean output, but
were getting it wrong, because bool values shouldn't be quoted in JSON or
YAML. Somehow we'd not needed an ExplainPropertyBool formatting subroutine
before 9.6; but now we do, so invent it.
Discussion: <16002.1466972724@sss.pgh.pa.us>
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>
The previous display was sort of confusing, because it didn't
distinguish between the number of workers that we planned to launch
and the number that actually got launched. This has already confused
several people, so display both numbers and label them clearly.
Julien Rouhaud, reviewed by me.
Per discussion, the new extensible node framework is thought to be
better designed than the custom path/scan/scanstate stuff we added
in PostgreSQL 9.5. Rework the latter to be more like the former.
This is not backward-compatible, but we generally don't promise that
for C APIs, and there probably aren't many people using this yet
anyway.
KaiGai Kohei, reviewed by Petr Jelinek and me. Some further
cosmetic changes by me.
postgres_fdw can now sent an UPDATE or DELETE statement directly to
the foreign server in simple cases, rather than sending a SELECT FOR
UPDATE statement and then updating or deleting rows one-by-one.
Etsuro Fujita, reviewed by Rushabh Lathia, Shigeru Hanada, Kyotaro
Horiguchi, Albe Laurenz, Thom Brown, and me.
We don't support any parallel write operations at present, so choosing
a parallel plan causes us to error out. Also, add a new regression
test that uses EXPLAIN ANALYZE SELECT INTO; if we'd had this previously,
force_parallel_mode testing would have caught this issue.
Mithun Cy and Robert Haas
When force_parallel_mode = true, we enable the parallel mode restrictions
for all queries for which this is believed to be safe. For the subset of
those queries believed to be safe to run entirely within a worker, we spin
up a worker and run the query there instead of running it in the
original process. When force_parallel_mode = regress, make additional
changes to allow the regression tests to run cleanly even though parallel
workers have been injected under the hood.
Taken together, this facilitates both better user testing and better
regression testing of the parallelism code.
Robert Haas, with help from Amit Kapila and Rushabh Lathia.
Aggregate nodes now have two new modes: a "partial" mode where they
output the unfinalized transition state, and a "finalize" mode where
they accept unfinalized transition states rather than individual
values as input.
These new modes are not used anywhere yet, but they will be necessary
for parallel aggregation. The infrastructure also figures to be
useful for cases where we want to aggregate local data and remote
data via the FDW interface, and want to bring back partial aggregates
from the remote side that can then be combined with locally generated
partial aggregates to produce the final value. It may also be useful
even when neither FDWs nor parallelism are in play, as explained in
the comments in nodeAgg.c.
David Rowley and Simon Riggs, reviewed by KaiGai Kohei, Heikki
Linnakangas, Haribabu Kommi, and me.
The original parallel sequential scan commit included only very limited
changes to the EXPLAIN output. Aggregated totals from all workers were
displayed, but there was no way to see what each individual worker did
or to distinguish the effort made by the workers from the effort made by
the leader.
Per a gripe by Thom Brown (and maybe others). Patch by me, reviewed
by Amit Kapila.
In addition, this path fills in a number of missing bits and pieces in
the parallel infrastructure. Paths and plans now have a parallel_aware
flag indicating whether whatever parallel-aware logic they have should
be engaged. It is believed that we will need this flag for a number of
path/plan types, not just sequential scans, which is why the flag is
generic rather than part of the SeqScan structures specifically.
Also, execParallel.c now gives parallel nodes a chance to initialize
their PlanState nodes from the DSM during parallel worker startup.
Amit Kapila, with a fair amount of adjustment by me. Review of previous
patch versions by Haribabu Kommi and others.
A Gather executor node runs any number of copies of a plan in an equal
number of workers and merges all of the results into a single tuple
stream. It can also run the plan itself, if the workers are
unavailable or haven't started up yet. It is intended to work with
the Partial Seq Scan node which will be added in future commits.
It could also be used to implement parallel query of a different sort
by itself, without help from Partial Seq Scan, if the single_copy mode
is used. In that mode, a worker executes the plan, and the parallel
leader does not, merely collecting the worker's results. So, a Gather
node could be inserted into a plan to split the execution of that plan
across two processes. Nested Gather nodes aren't currently supported,
but we might want to add support for that in the future.
There's nothing in the planner to actually generate Gather nodes yet,
so it's not quite time to break out the champagne. But we're getting
close.
Amit Kapila. Some designs suggestions were provided by me, and I also
reviewed the patch. Single-copy mode, documentation, and other minor
changes also by me.
ExplainPreScanNode knows how to iterate over a generic tree of plan
states; factor that logic out into a separate walker function so that
other code, such as upcoming patches for parallel query, can also use
it.
Patch by me, reviewed by Tom Lane.
Commit 924bcf4f16 introduced a framework
for parallel computation in PostgreSQL that makes most but not all
built-in functions safe to execute in parallel mode. In order to have
parallel query, we'll need to be able to determine whether that query
contains functions (either built-in or user-defined) that cannot be
safely executed in parallel mode. This requires those functions to be
labeled, so this patch introduces an infrastructure for that. Some
functions currently labeled as safe may need to be revised depending on
how pending issues related to heavyweight locking under paralllelism
are resolved.
Parallel plans can't be used except for the case where the query will
run to completion. If portal execution were suspended, the parallel
mode restrictions would need to remain in effect during that time, but
that might make other queries fail. Therefore, this patch introduces
a framework that enables consideration of parallel plans only when it
is known that the plan will be run to completion. This probably needs
some refinement; for example, at bind time, we do not know whether a
query run via the extended protocol will be execution to completion or
run with a limited fetch count. Having the client indicate its
intentions at bind time would constitute a wire protocol break. Some
contexts in which parallel mode would be safe are not adjusted by this
patch; the default is not to try parallel plans except from call sites
that have been updated to say that such plans are OK.
This commit doesn't introduce any parallel paths or plans; it just
provides a way to determine whether they could potentially be used.
I'm committing it on the theory that the remaining parallel sequential
scan patches will also get committed to this release, hopefully in the
not-too-distant future.
Robert Haas and Amit Kapila. Reviewed (in earlier versions) by Noah
Misch.
The original implementation of TABLESAMPLE modeled the tablesample method
API on index access methods, which wasn't a good choice because, without
specialized DDL commands, there's no way to build an extension that can
implement a TSM. (Raw inserts into system catalogs are not an acceptable
thing to do, because we can't undo them during DROP EXTENSION, nor will
pg_upgrade behave sanely.) Instead adopt an API more like procedural
language handlers or foreign data wrappers, wherein the only SQL-level
support object needed is a single handler function identified by having
a special return type. This lets us get rid of the supporting catalog
altogether, so that no custom DDL support is needed for the feature.
Adjust the API so that it can support non-constant tablesample arguments
(the original coding assumed we could evaluate the argument expressions at
ExecInitSampleScan time, which is undesirable even if it weren't outright
unsafe), and discourage sampling methods from looking at invisible tuples.
Make sure that the BERNOULLI and SYSTEM methods are genuinely repeatable
within and across queries, as required by the SQL standard, and deal more
honestly with methods that can't support that requirement.
Make a full code-review pass over the tablesample additions, and fix
assorted bugs, omissions, infelicities, and cosmetic issues (such as
failure to put the added code stanzas in a consistent ordering).
Improve EXPLAIN's output of tablesample plans, too.
Back-patch to 9.5 so that we don't have to support the original API
in production.
Allow CustomPath to have a list of paths, CustomPlan a list of plans,
and CustomPlanState a list of planstates known to the core system, so
that custom path/plan providers can more reasonably use this
infrastructure for nodes with multiple children.
KaiGai Kohei, per a design suggestion from Tom Lane, with some
further kibitzing by me.
This SQL standard functionality allows to aggregate data by different
GROUP BY clauses at once. Each grouping set returns rows with columns
grouped by in other sets set to NULL.
This could previously be achieved by doing each grouping as a separate
query, conjoined by UNION ALLs. Besides being considerably more concise,
grouping sets will in many cases be faster, requiring only one scan over
the underlying data.
The current implementation of grouping sets only supports using sorting
for input. Individual sets that share a sort order are computed in one
pass. If there are sets that don't share a sort order, additional sort &
aggregation steps are performed. These additional passes are sourced by
the previous sort step; thus avoiding repeated scans of the source data.
The code is structured in a way that adding support for purely using
hash aggregation or a mix of hashing and sorting is possible. Sorting
was chosen to be supported first, as it is the most generic method of
implementation.
Instead of, as in an earlier versions of the patch, representing the
chain of sort and aggregation steps as full blown planner and executor
nodes, all but the first sort are performed inside the aggregation node
itself. This avoids the need to do some unusual gymnastics to handle
having to return aggregated and non-aggregated tuples from underlying
nodes, as well as having to shut down underlying nodes early to limit
memory usage. The optimizer still builds Sort/Agg node to describe each
phase, but they're not part of the plan tree, but instead additional
data for the aggregation node. They're a convenient and preexisting way
to describe aggregation and sorting. The first (and possibly only) sort
step is still performed as a separate execution step. That retains
similarity with existing group by plans, makes rescans fairly simple,
avoids very deep plans (leading to slow explains) and easily allows to
avoid the sorting step if the underlying data is sorted by other means.
A somewhat ugly side of this patch is having to deal with a grammar
ambiguity between the new CUBE keyword and the cube extension/functions
named cube (and rollup). To avoid breaking existing deployments of the
cube extension it has not been renamed, neither has cube been made a
reserved keyword. Instead precedence hacking is used to make GROUP BY
cube(..) refer to the CUBE grouping sets feature, and not the function
cube(). To actually group by a function cube(), unlikely as that might
be, the function name has to be quoted.
Needs a catversion bump because stored rules may change.
Author: Andrew Gierth and Atri Sharma, with contributions from Andres Freund
Reviewed-By: Andres Freund, Noah Misch, Tom Lane, Svenne Krap, Tomas
Vondra, Erik Rijkers, Marti Raudsepp, Pavel Stehule
Discussion: CAOeZVidmVRe2jU6aMk_5qkxnB7dfmPROzM7Ur8JPW5j8Y5X-Lw@mail.gmail.com
Add a TABLESAMPLE clause to SELECT statements that allows
user to specify random BERNOULLI sampling or block level
SYSTEM sampling. Implementation allows for extensible
sampling functions to be written, using a standard API.
Basic version follows SQLStandard exactly. Usable
concrete use cases for the sampling API follow in later
commits.
Petr Jelinek
Reviewed by Michael Paquier and Simon Riggs
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.
Foreign data wrappers can use this capability for so-called "join
pushdown"; that is, instead of executing two separate foreign scans
and then joining the results locally, they can generate a path which
performs the join on the remote server and then is scanned locally.
This commit does not extend postgres_fdw to take advantage of this
capability; it just provides the infrastructure.
Custom scan providers can use this in a similar way. Previously,
it was only possible for a custom scan provider to scan a single
relation. Now, it can scan an entire join tree, provided of course
that it knows how to produce the same results that the join would
have produced if executed normally.
KaiGai Kohei, reviewed by Shigeru Hanada, Ashutosh Bapat, and me.
Foreign tables can now be inheritance children, or parents. Much of the
system was already ready for this, but we had to fix a few things of
course, mostly in the area of planner and executor handling of row locks.
As side effects of this, allow foreign tables to have NOT VALID CHECK
constraints (and hence to accept ALTER ... VALIDATE CONSTRAINT), and to
accept ALTER SET STORAGE and ALTER SET WITH/WITHOUT OIDS. Continuing to
disallow these things would've required bizarre and inconsistent special
cases in inheritance behavior. Since foreign tables don't enforce CHECK
constraints anyway, a NOT VALID one is a complete no-op, but that doesn't
mean we shouldn't allow it. And it's possible that some FDWs might have
use for SET STORAGE or SET WITH OIDS, though doubtless they will be no-ops
for most.
An additional change in support of this is that when a ModifyTable node
has multiple target tables, they will all now be explicitly identified
in EXPLAIN output, for example:
Update on pt1 (cost=0.00..321.05 rows=3541 width=46)
Update on pt1
Foreign Update on ft1
Foreign Update on ft2
Update on child3
-> Seq Scan on pt1 (cost=0.00..0.00 rows=1 width=46)
-> Foreign Scan on ft1 (cost=100.00..148.03 rows=1170 width=46)
-> Foreign Scan on ft2 (cost=100.00..148.03 rows=1170 width=46)
-> Seq Scan on child3 (cost=0.00..25.00 rows=1200 width=46)
This was done mainly to provide an unambiguous place to attach "Remote SQL"
fields, but it is useful for inherited updates even when no foreign tables
are involved.
Shigeru Hanada and Etsuro Fujita, reviewed by Ashutosh Bapat and Kyotaro
Horiguchi, some additional hacking by me
The previous coding in EXPLAIN always labeled a ModifyTable node with the
name of the target table affected by its first child plan. When originally
written, this was necessarily the parent table of the inheritance tree,
so everything was unconfusing. But when we added NO INHERIT constraints,
it became possible for the parent table to be deleted from the plan by
constraint exclusion while still leaving child tables present. This led to
the ModifyTable plan node being labeled with the first surviving child,
which was deemed confusing. Fix it by retaining the parent table's RT
index in a new field in ModifyTable.
Etsuro Fujita, reviewed by Ashutosh Bapat and myself
Up to now, EXPLAIN has contented itself with printing the sort expressions
in a Sort or Merge Append plan node. This patch improves that by
annotating the sort keys with COLLATE, DESC, USING, and/or NULLS FIRST/LAST
whenever nondefault sort ordering options are used. The output is now a
reasonably close approximation of an ORDER BY clause equivalent to the
plan's ordering.
Marius Timmer, Lukas Kreft, and Arne Scheffer; reviewed by Mike Blackwell.
Some additional hacking by me.
The folly of the previous arrangement was just demonstrated: there's no
convenient way to add fields to ExplainState without breaking ABI, even
if callers have no need to touch those fields. Since we might well need
to do that again someday in back branches, let's change things so that
only explain.c has to have sizeof(ExplainState) compiled into it. This
costs one extra palloc() per EXPLAIN operation, which is surely pretty
negligible.
As of 9.3, ruleutils.c goes to some lengths to ensure that table and column
aliases used in its output are unique. Of course this takes more time than
was required before, which in itself isn't fatal. However, EXPLAIN was set
up so that recalculation of the unique aliases was repeated for each
subexpression printed in a plan. That results in O(N^2) time and memory
consumption for large plan trees, which did not happen in older branches.
Fortunately, the expensive work is the same across a whole plan tree,
so there is no need to repeat it; we can do most of the initialization
just once per query and re-use it for each subexpression. This buys
back most (not all) of the performance loss since 9.2.
We need an extra ExplainState field to hold the precalculated deparse
context. That's no problem in HEAD, but in the back branches, expanding
sizeof(ExplainState) seems risky because third-party extensions might
have local variables of that struct type. So, in 9.4 and 9.3, introduce
an auxiliary struct to keep sizeof(ExplainState) the same. We should
refactor the APIs to avoid such local variables in future, but that's
material for a separate HEAD-only commit.
Per gripe from Alexey Bashtanov. Back-patch to 9.3 where the issue
was introduced.
This allows extension modules to define their own methods for
scanning a relation, and get the core code to use them. It's
unclear as yet how much use this capability will find, but we
won't find out if we never commit it.
KaiGai Kohei, reviewed at various times and in various levels
of detail by Shigeru Hanada, Tom Lane, Andres Freund, Álvaro
Herrera, and myself.
We've gotten enough push-back on that change to make it clear that it
wasn't an especially good idea to do it like that. Revert plain EXPLAIN
to its previous behavior, but keep the extra output in EXPLAIN ANALYZE.
Per discussion.
Internally, I set this up as a separate flag ExplainState.summary that
controls printing of planning time and execution time. For now it's
just copied from the ANALYZE option, but we could consider exposing it
to users.
If we expect batching at the very beginning, we size nbuckets for
"full work_mem" (see how many tuples we can get into work_mem,
while not breaking NTUP_PER_BUCKET threshold).
If we expect to be fine without batching, we start with the 'right'
nbuckets and track the optimal nbuckets as we go (without actually
resizing the hash table). Once we hit work_mem (considering the
optimal nbuckets value), we keep the value.
At the end of the first batch, we check whether (nbuckets !=
nbuckets_optimal) and resize the hash table if needed. Also, we
keep this value for all batches (it's OK because it assumes full
work_mem, and it makes the batchno evaluation trivial). So the
resize happens only once.
There could be cases where it would improve performance to allow
the NTUP_PER_BUCKET threshold to be exceeded to keep everything in
one batch rather than spilling to a second batch, but attempts to
generate such a case have so far been unsuccessful; that issue may
be addressed with a follow-on patch after further investigation.
Tomas Vondra with minor format and comment cleanup by me
Reviewed by Robert Haas, Heikki Linnakangas, and Kevin Grittner
The new header contains many prototypes for functions in ruleutils.c
that are not exposed to the SQL level.
Reviewed by Andres Freund and Michael Paquier.
EXPLAIN ANALYZE shows the information of the numbers of exact/lossy blocks which
bitmap heap scan processes. But, previously, when those numbers were both zero,
it displayed only the prefix "Heap Blocks:" in TEXT output format. This is strange
and would confuse the users. So this commit suppresses such unnecessary information.
Backpatch to 9.4 where EXPLAIN ANALYZE was changed so that such information was
displayed.
Etsuro Fujita
Commit af7914c662, which introduced the
EXPLAIN (TIMING) option, for some reason coded explain.c to look at
planstate->instrument->need_timer rather than es->timing to decide
whether to print timing info. However, the former flag might get set
as a result of contrib/auto_explain wanting timing information. We
certainly don't want activation of auto_explain to change user-visible
statement behavior, so fix that.
Also fix an independent bug introduced in the same patch: in the code
path for a never-executed node with a machine-friendly output format,
if timing was selected, it would fail to print the Actual Rows and Actual
Loops items.
Per bug #10404 from Tomonari Katsumata. Back-patch to 9.2 where the
faulty code was introduced.
Now that EXPLAIN also outputs a "planning time" measurement, the use of
"total" here seems rather confusing: it sounds like it might include the
planning time which of course it doesn't. Majority opinion was that
"execution time" is a better label, so we'll call it that.
This should be noted as a backwards incompatibility for tools that examine
EXPLAIN ANALYZE output.
In passing, I failed to resist the temptation to do a little editing on the
materialized-view example affected by this change.
This doesn't work for prepared queries, but it's not too easy to get
the information in that case and there's some debate as to exactly
what the right thing to measure is, so just do this for now.
Andreas Karlsson, with slight doc changes by me.
This patch adds the ability to write TABLE( function1(), function2(), ...)
as a single FROM-clause entry. The result is the concatenation of the
first row from each function, followed by the second row from each
function, etc; with NULLs inserted if any function produces fewer rows than
others. This is believed to be a much more useful behavior than what
Postgres currently does with multiple SRFs in a SELECT list.
This syntax also provides a reasonable way to combine use of column
definition lists with WITH ORDINALITY: put the column definition list
inside TABLE(), where it's clear that it doesn't control the ordinality
column as well.
Also implement SQL-compliant multiple-argument UNNEST(), by turning
UNNEST(a,b,c) into TABLE(unnest(a), unnest(b), unnest(c)).
The SQL standard specifies TABLE() with only a single function, not
multiple functions, and it seems to require an implicit UNNEST() which is
not what this patch does. There may be something wrong with that reading
of the spec, though, because if it's right then the spec's TABLE() is just
a pointless alternative spelling of UNNEST(). After further review of
that, we might choose to adopt a different syntax for what this patch does,
but in any case this functionality seems clearly worthwhile.
Andrew Gierth, reviewed by Zoltán Böszörményi and Heikki Linnakangas, and
significantly revised by me
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.)
The materialized views patch adjusted ExplainOneQuery to take an
additional DestReceiver argument, but failed to add a matching
argument to the definition of ExplainOneQuery_hook. This is a
problem for users of the hook that want to call ExplainOnePlan.
Fix by adding the missing argument.
This patch adds the core-system infrastructure needed to support updates
on foreign tables, and extends contrib/postgres_fdw to allow updates
against remote Postgres servers. There's still a great deal of room for
improvement in optimization of remote updates, but at least there's basic
functionality there now.
KaiGai Kohei, reviewed by Alexander Korotkov and Laurenz Albe, and rather
heavily revised by Tom Lane.
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.
In commit 11e131854f, we improved the
rule/view dumping code so that it would produce valid query representations
even if some of the tables involved in a query had been renamed since the
query was parsed. This patch extends that idea to fix problems that occur
when individual columns are renamed, or added or dropped. As before, the
core of the fix is to assign unique new aliases when a name conflict has
been created. This is complicated by the JOIN USING feature, which
requires the same column alias to be used in both input relations, but we
can handle that with a sufficiently complex approach to assigning aliases.
A fortiori, this patch takes care of situations where the query didn't have
unique column names to begin with, such as in a recent complaint from Bryan
Nuse. (Because of expansion of "SELECT *", re-parsing a dumped query can
require column name uniqueness even though the original text did not.)
The previous scheme had bugs in some corner cases involving tables that had
been renamed since a view was made. This could result in dumped views that
failed to reload or reloaded incorrectly, as seen in bug #7553 from Lloyd
Albin, as well as in some pgsql-hackers discussion back in January. Also,
its behavior for printing EXPLAIN plans was sometimes confusing because of
willingness to use the same alias for multiple RTEs (it was Ashutosh
Bapat's complaint about that aspect that started the January thread).
To fix, ensure that each RTE in the query has a unique unqualified alias,
by modifying the alias if necessary (we add "_" and digits as needed to
create a non-conflicting name). Then we can just print its variables with
that alias, avoiding the confusing and bug-prone scheme of sometimes
schema-qualifying variable names. In EXPLAIN, it proves to be expedient to
take the further step of only assigning such aliases to RTEs that are
actually referenced in the query, since the planner has a habit of
generating extra RTEs with the same alias in situations such as
inheritance-tree expansion.
Although this fixes a bug of very long standing, I'm hesitant to back-patch
such a noticeable behavioral change. My experiments while creating a
regression test convinced me that actually incorrect output (as opposed to
confusing output) occurs only in very narrow cases, which is backed up by
the lack of previous complaints from the field. So we may be better off
living with it in released branches; and in any case it'd be smart to let
this ripen awhile in HEAD before we consider back-patching it.
Currently, the only way to see the numbers this gathers is via
EXPLAIN (ANALYZE, BUFFERS), but the plan is to add visibility through
the stats collector and pg_stat_statements in subsequent patches.
Ants Aasma, reviewed by Greg Smith, with some further changes by me.
Making this operation look like a utility statement seems generally a good
idea, and particularly so in light of the desire to provide command
triggers for utility statements. The original choice of representing it as
SELECT with an IntoClause appendage had metastasized into rather a lot of
places, unfortunately, so that this patch is a great deal more complicated
than one might at first expect.
In particular, keeping EXPLAIN working for SELECT INTO and CREATE TABLE AS
subcommands required restructuring some EXPLAIN-related APIs. Add-on code
that calls ExplainOnePlan or ExplainOneUtility, or uses
ExplainOneQuery_hook, will need adjustment.
Also, the cases PREPARE ... SELECT INTO and CREATE RULE ... SELECT INTO,
which formerly were accepted though undocumented, are no longer accepted.
The PREPARE case can be replaced with use of CREATE TABLE AS EXECUTE.
The CREATE RULE case doesn't seem to have much real-world use (since the
rule would work only once before failing with "table already exists"),
so we'll not bother with that one.
Both SELECT INTO and CREATE TABLE AS still return a command tag of
"SELECT nnnn". There was some discussion of returning "CREATE TABLE nnnn",
but for the moment backwards compatibility wins the day.
Andres Freund and Tom Lane
Sometimes it may be useful to get actual row counts out of EXPLAIN
(ANALYZE) without paying the cost of timing every node entry/exit.
With this patch, you can say EXPLAIN (ANALYZE, TIMING OFF) to get that.
Tomas Vondra, reviewed by Eric Theise, with minor doc changes by me.
Like the XML data type, we simply store JSON data as text, after checking
that it is valid. More complex operations such as canonicalization and
comparison may come later, but this is enough for not.
There are a few open issues here, such as whether we should attempt to
detect UTF-8 surrogate pairs represented as \uXXXX\uYYYY, but this gets
the basic framework in place.
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).
When a btree index contains all columns required by the query, and the
visibility map shows that all tuples on a target heap page are
visible-to-all, we don't need to fetch that heap page. This patch depends
on the previous patches that made the visibility map reliable.
There's a fair amount left to do here, notably trying to figure out a less
chintzy way of estimating the cost of an index-only scan, but the core
functionality seems ready to commit.
Robert Haas and Ibrar Ahmed, with some previous work by Heikki Linnakangas.
This provides information about the numbers of tuples that were visited
but not returned by table scans, as well as the numbers of join tuples
that were considered and discarded within a join plan node.
There is still some discussion going on about the best way to report counts
for outer-join situations, but I think most of what's in the patch would
not change if we revise that, so I'm going to go ahead and commit it as-is.
Documentation changes to follow (they weren't in the submitted patch
either).
Marko Tiikkaja, reviewed by Marc Cousin, somewhat revised by Tom
This warning is new in gcc 4.6 and part of -Wall. This patch cleans
up most of the noise, but there are some still warnings that are
trickier to remove.
Andres Freund
Robert Haas
Tom Lane
Kevin Grittner
Andrew Gierth
Stephen Frost
Alvaro Herrera
Heikki Linnakangas
Bruce Momjian
Peter Eisentraut
Simon Riggs
Fujii Masao
Andrew Dunstan