| Age | Commit message (Collapse) | Author |
|---|
|
Previously, the planner would reject an index-only scan if any restriction
clause for its table used a column not available from the index, even
if that restriction clause would later be dropped from the plan entirely
because it's implied by the index's predicate. This is a fairly common
situation for partial indexes because predicates using columns not included
in the index are often the most useful kind of predicate, and we have to
duplicate (or at least imply) the predicate in the WHERE clause in order
to get the index to be considered at all. So index-only scans were
essentially unavailable with such partial indexes.
To fix, we have to do detection of implied-by-predicate clauses much
earlier in the planner. This patch puts it in check_index_predicates
(nee check_partial_indexes), meaning it gets done for every partial index,
whereas we previously only considered this issue at createplan time,
so that the work was only done for an index actually selected for use.
That could result in a noticeable planning slowdown for queries against
tables with many partial indexes. However, testing suggested that there
isn't really a significant cost, especially not with reasonable numbers
of partial indexes. We do get a small additional benefit, which is that
cost_index is more accurate since it correctly discounts the evaluation
cost of clauses that will be removed. We can also avoid considering such
clauses as potential indexquals, which saves useless matching cycles in
the case where the predicate columns aren't in the index, and prevents
generating bogus plans that double-count the clause's selectivity when
the columns are in the index.
Tomas Vondra and Kyotaro Horiguchi, reviewed by Kevin Grittner and
Konstantin Knizhnik, and whacked around a little by me
|
|
This is necessary infrastructure for supporting parallel aggregation
for aggregates whose transition type is "internal". Such values
can't be passed between cooperating processes, because they are
just pointers.
David Rowley, reviewed by Tomas Vondra and 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.
|
|
Parallel workers can now partially aggregate the data and pass the
transition values back to the leader, which can combine the partial
results to produce the final answer.
David Rowley, based on earlier work by Haribabu Kommi. Reviewed by
Álvaro Herrera, Tomas Vondra, Amit Kapila, James Sewell, and me.
|
|
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.
|
|
In commit 19a541143a09c067 I did not make PathTarget a subtype of Node,
and embedded a RelOptInfo's reltarget directly into it rather than having
a separately-allocated Node. In hindsight that was misguided
micro-optimization, enabled by the fact that at that point we didn't have
any Paths with custom PathTargets. Now that PathTarget processing has
been fleshed out some more, it's easier to see that it's better to have
PathTarget as an indepedent Node type, even if it does cost us one more
palloc to create a RelOptInfo. So change it while we still can.
This commit just changes the representation, without doing anything more
interesting than that.
|
|
Instead of having planner.c compute a groupColIdx array and store it in
GroupingSetsPaths, make create_groupingsets_plan() find the grouping
columns by searching in the child plan node's tlist. Although that's
probably a bit slower for create_groupingsets_plan(), it's more like
the way every other plan node type does this, and it provides positive
confirmation that we know which child output columns we're supposed to be
grouping on. (Indeed, looking at this now, I'm not at all sure that it
wasn't broken before, because create_groupingsets_plan() isn't demanding
an exact tlist match from its child node.) Also, this allows substantial
simplification in planner.c, because it no longer needs to compute the
groupColIdx array at all; no other cases were using it.
I'd intended to put off this refactoring until later (like 9.7), but
in view of the likely bug fix and the need to rationalize planner.c's
tlist handling so we can do something sane with Konstantin Knizhnik's
function-evaluation-postponement patch, I think it can't wait.
|
|
I've been saying we needed to do this for more than five years, and here it
finally is. This patch removes the ever-growing tangle of spaghetti logic
that grouping_planner() used to use to try to identify the best plan for
post-scan/join query steps. Now, there is (nearly) independent
consideration of each execution step, and entirely separate construction of
Paths to represent each of the possible ways to do that step. We choose
the best Path or set of Paths using the same add_path() logic that's been
used inside query_planner() for years.
In addition, this patch removes the old restriction that subquery_planner()
could return only a single Plan. It now returns a RelOptInfo containing a
set of Paths, just as query_planner() does, and the parent query level can
use each of those Paths as the basis of a SubqueryScanPath at its level.
This allows finding some optimizations that we missed before, wherein a
subquery was capable of returning presorted data and thereby avoiding a
sort in the parent level, making the overall cost cheaper even though
delivering sorted output was not the cheapest plan for the subquery in
isolation. (A couple of regression test outputs change in consequence of
that. However, there is very little change in visible planner behavior
overall, because the point of this patch is not to get immediate planning
benefits but to create the infrastructure for future improvements.)
There is a great deal left to do here. This patch unblocks a lot of
planner work that was basically impractical in the old code structure,
such as allowing FDWs to implement remote aggregation, or rewriting
plan_set_operations() to allow consideration of multiple implementation
orders for set operations. (The latter will likely require a full
rewrite of plan_set_operations(); what I've done here is only to fix it
to return Paths not Plans.) I have also left unfinished some localized
refactoring in createplan.c and planner.c, because it was not necessary
to get this patch to a working state.
Thanks to Robert Haas, David Rowley, and Amit Kapila for review.
|
|
Up to now, there's been an assumption that all Paths for a given relation
compute the same output column set (targetlist). However, there are good
reasons to remove that assumption. For example, an indexscan on an
expression index might be able to return the value of an expensive function
"for free". While we have the ability to generate such a plan today in
simple cases, we don't have a way to model that it's cheaper than a plan
that computes the function from scratch, nor a way to create such a plan
in join cases (where the function computation would normally happen at
the topmost join node). Also, we need this so that we can have Paths
representing post-scan/join steps, where the targetlist may well change
from one step to the next. Therefore, invent a "struct PathTarget"
representing the columns we expect a plan step to emit. It's convenient
to include the output tuple width and tlist evaluation cost in this struct,
and there will likely be additional fields in future.
While Path nodes that actually do have custom outputs will need their own
PathTargets, it will still be true that most Paths for a given relation
will compute the same tlist. To reduce the overhead added by this patch,
keep a "default PathTarget" in RelOptInfo, and allow Paths that compute
that column set to just point to their parent RelOptInfo's reltarget.
(In the patch as committed, actually every Path is like that, since we
do not yet have any cases of custom PathTargets.)
I took this opportunity to provide some more-honest costing of
PlaceHolderVar evaluation. Up to now, the assumption that "scan/join
reltargetlists have cost zero" was applied not only to Vars, where it's
reasonable, but also PlaceHolderVars where it isn't. Now, we add the eval
cost of a PlaceHolderVar's expression to the first plan level where it can
be computed, by including it in the PathTarget cost field and adding that
to the cost estimates for Paths. This isn't perfect yet but it's much
better than before, and there is a way forward to improve it more. This
costing change affects the join order chosen for a couple of the regression
tests, changing expected row ordering.
|
|
An extensible node is always tagged T_Extensible, but the extnodename
field identifies it more specifically; it may also include arbitrary
private data. Extensible nodes can be copied, tested for equality,
serialized, and deserialized, but the core system doesn't know
anything about them otherwise. Some extensions may find it useful to
include these nodes in fdw_private or custom_private lists in lieu of
arm-wrestling their data into a format that the core code can
understand.
Along the way, so as not to burden the authors of such extensible
node types too much, expose the functions for writing serialized
tokens, and for serializing and deserializing bitmapsets.
KaiGai Kohei, per a design suggested by me. Reviewed by Andres Freund
and by me, and further edited by me.
|
|
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.
|
|
You can't really do anything useful with this in the form it currently
exists; among other problems, there's no way to reread whatever
information might be produced when the path is output. Work is
underway to replace this with a more useful and more general system of
extensible nodes, but let's start by getting rid of this bit.
Extracted from a larger patch by KaiGai Kohei.
|
|
Previously, the foreign join pushdown infrastructure left the question
of security entirely up to individual FDWs, but it would be easy for
a foreign data wrapper to inadvertently open up subtle security holes
that way. So, make it the core code's job to determine which user
mapping OID is relevant, and don't attempt join pushdown unless it's
the same for all relevant relations.
Per a suggestion from Tom Lane. Shigeru Hanada and Ashutosh Bapat,
reviewed by Etsuro Fujita and KaiGai Kohei, with some further
changes by me.
|
|
The core innovation of this patch is the introduction of the concept
of a partial path; that is, a path which if executed in parallel will
generate a subset of the output rows in each process. Gathering a
partial path produces an ordinary (complete) path. This allows us to
generate paths for parallel joins by joining a partial path for one
side (which at the baserel level is currently always a Partial Seq
Scan) to an ordinary path on the other side. This is subject to
various restrictions at present, especially that this strategy seems
unlikely to be sensible for merge joins, so only nested loops and
hash joins paths are generated.
This also allows an Append node to be pushed below a Gather node in
the case of a partitioned table.
Testing revealed that early versions of this patch made poor decisions
in some cases, which turned out to be caused by the fact that the
original cost model for Parallel Seq Scan wasn't very good. So this
patch tries to make some modest improvements in that area.
There is much more to be done in the area of generating good parallel
plans in all cases, but this seems like a useful step forward.
Patch by me, reviewed by Dilip Kumar and Amit Kapila.
|
|
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.
|
|
This patch reduces pg_am to just two columns, a name and a handler
function. All the data formerly obtained from pg_am is now provided
in a C struct returned by the handler function. This is similar to
the designs we've adopted for FDWs and tablesample methods. There
are multiple advantages. For one, the index AM's support functions
are now simple C functions, making them faster to call and much less
error-prone, since the C compiler can now check function signatures.
For another, this will make it far more practical to define index access
methods in installable extensions.
A disadvantage is that SQL-level code can no longer see attributes
of index AMs; in particular, some of the crosschecks in the opr_sanity
regression test are no longer possible from SQL. We've addressed that
by adding a facility for the index AM to perform such checks instead.
(Much more could be done in that line, but for now we're content if the
amvalidate functions more or less replace what opr_sanity used to do.)
We might also want to expose some sort of reporting functionality, but
this patch doesn't do that.
Alexander Korotkov, reviewed by Petr Jelínek, and rather heavily
editorialized on by me.
|
|
Backpatch certain files through 9.1
|
|
'\"' is more commonly written simply as '"'.
|
|
Omitted boundaries represent the upper or lower limit of the corresponding
array subscript. This allows simpler specification of many common
use-cases.
(Revised version of commit 9246af6799819847faa33baf441251003acbb8fe)
YUriy Zhuravlev
|
|
I miss too much. Patch is returned to commitfest process.
|
|
Allow to omiy lower or upper or both boundaries in array subscript
for selecting slice of array.
Author: YUriy Zhuravlev
|
|
I originally modeled this data structure on SpecialJoinInfo, but after
commit acfcd45cacb6df23 that looks like a pretty poor decision.
All we really need is relid sets identifying laterally-referenced rels;
and most of the time, what we want to know about includes indirect lateral
references, a case the LateralJoinInfo data was unsuited to compute with
any efficiency. The previous commit redefined RelOptInfo.lateral_relids
as the transitive closure of lateral references, so that it easily supports
checking indirect references. For the places where we really do want just
direct references, add a new RelOptInfo field direct_lateral_relids, which
is easily set up as a copy of lateral_relids before we perform the
transitive closure calculation. Then we can just drop lateral_info_list
and LateralJoinInfo and the supporting code. This makes the planner's
handling of lateral references noticeably more efficient, and shorter too.
Such a change can't be back-patched into stable branches for fear of
breaking extensions that might be looking at the planner's data structures;
but it seems not too late to push it into 9.5, so I've done so.
|
|
Commit e7cb7ee14555cc9c5773e2c102efd6371f6f2005 provided basic
infrastructure for allowing a foreign data wrapper or custom scan
provider to replace a join of one or more tables with a scan.
However, this infrastructure failed to take into account the need
for possible EvalPlanQual rechecks, and ExecScanFetch would fail
an assertion (or just overwrite memory) if such a check was attempted
for a plan containing a pushed-down join. To fix, adjust the EPQ
machinery to skip some processing steps when scanrelid == 0, making
those the responsibility of scan's recheck method, which also has
the responsibility in this case of correctly populating the relevant
slot.
To allow foreign scans to gain control in the right place to make
use of this new facility, add a new, optional RecheckForeignScan
method. Also, allow a foreign scan to have a child plan, which can
be used to correctly populate the slot (or perhaps for something
else, but this is the only use currently envisioned).
KaiGai Kohei, reviewed by Robert Haas, Etsuro Fujita, and Kyotaro
Horiguchi.
|
|
While convincing myself that commit 7e19db0c09719d79 would solve both of
the problems recently reported by Andreas Seltenreich, I realized that
add_paths_to_joinrel's handling of LATERAL restrictions could be made
noticeably simpler and faster if we were to retain the minimum possible
parameterization for each joinrel (that is, the set of relids supplying
unsatisfied lateral references in it). We already retain that for
baserels, in RelOptInfo.lateral_relids, so we can use that field for
joinrels too.
I re-pgindent'd the files touched here, which affects some unrelated
comments.
This is, I believe, just a minor optimization not a bug fix, so no
back-patch.
|
|
Commit a0d9f6e434bb56f7e5441b7988f3982feead33b3 added this support for
all other plan node types; this fills in the gap.
Since TextOutCustomScan complicates this and is pretty well useless,
remove it.
KaiGai Kohei, with some modifications by me.
|
|
Add a new flag, consider_parallel, to each RelOptInfo, indicating
whether a plan for that relation could conceivably be run inside of
a parallel worker. Right now, we're pretty conservative: for example,
it might be possible to defer applying a parallel-restricted qual
in a worker, and later do it in the leader, but right now we just
don't try to parallelize access to that relation. That's probably
the right decision in most cases, anyway.
Using the new flag, generate parallel sequential scan plans for plain
baserels, meaning that we now have parallel sequential scan in
PostgreSQL. The logic here is pretty unsophisticated right now: the
costing model probably isn't right in detail, and we can't push joins
beneath Gather nodes, so the number of plans that can actually benefit
from this is pretty limited right now. Lots more work is needed.
Nevertheless, it seems time to enable this functionality so that all
this code can actually be tested easily by users and developers.
Note that, if you wish to test this functionality, it will be
necessary to set max_parallel_degree to a value greater than the
default of 0. Once a few more loose ends have been tidied up here, we
might want to consider changing the default value of this GUC, but
I'm leaving it alone for now.
Along the way, fix a bug in cost_gather: the previous coding thought
that a Gather node's transfer overhead should be costed on the basis of
the relation size rather than the number of tuples that actually need
to be passed off to the leader.
Patch by me, reviewed in earlier versions by Amit Kapila.
|
|
In addition, this path fills in a number of missing bits and pieces in
the parallel infrastructure. Paths and plans now have a parallel_aware
flag indicating whether whatever parallel-aware logic they have should
be engaged. It is believed that we will need this flag for a number of
path/plan types, not just sequential scans, which is why the flag is
generic rather than part of the SeqScan structures specifically.
Also, execParallel.c now gives parallel nodes a chance to initialize
their PlanState nodes from the DSM during parallel worker startup.
Amit Kapila, with a fair amount of adjustment by me. Review of previous
patch versions by Haribabu Kommi and others.
|
|
I dunno how commit 3bd909b220930f21d6e15833a17947be749e7fde missed
this, but it evidently did.
|
|
This fixes a long-standing bug which was discovered while investigating
the interaction between the new join pushdown code and the EvalPlanQual
machinery: if a ForeignScan appears on the inner side of a paramaterized
nestloop, an EPQ recheck would re-return the original tuple even if
it no longer satisfied the pushed-down quals due to changed parameter
values.
This fix adds a new member to ForeignScan and ForeignScanState and a
new argument to make_foreignscan, and requires changes to FDWs which
push down quals to populate that new argument with a list of quals they
have chosen to push down. Therefore, I'm only back-patching to 9.5,
even though the bug is not new in 9.5.
Etsuro Fujita, reviewed by me and by Kyotaro Horiguchi.
|
|
The WithCheckOptions list in Query are only populated during rewrite and
do not need to be written out or read in as part of a Query structure.
Further, move WithCheckOptions to the bottom and add comments to clarify
that it is only populated during rewrite.
Back-patch to 9.5 with a catversion bump, as we are still in alpha.
|
|
KaiGai Kohei, with one correction by me.
|
|
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.
|
|
This code provides infrastructure for a parallel leader to start up
parallel workers to execute subtrees of the plan tree being executed
in the master. User-supplied parameters from ParamListInfo are passed
down, but PARAM_EXEC parameters are not. Various other constructs,
such as initplans, subplans, and CTEs, are also not currently shared.
Nevertheless, there's enough here to support a basic implementation of
parallel query, and we can lift some of the current restrictions as
needed.
Amit Kapila and Robert Haas
|
|
For parallel query, we need to be able to pass a Plan to a worker, so
that it knows what it's supposed to do. We could invent our own way
of serializing plans for that purpose, but piggybacking on the
existing node infrastructure seems like a much better idea.
Initially, we'll probably only support a limited number of nodes
within parallel workers, but this commit adds support for everything
in plannodes.h except CustomScan, because doing it all at once seems
easier than doing it piecemeal, and it makes testing this code easier,
too. CustomScan is excluded because making that work requires a
larger rework of that facility.
Amit Kapila, reviewed and slightly revised by me.
|
|
It's declared as being an array of bool, but it's printed
differently from the way bool and arrays of bool are handled
elsewhere.
Patch by Amit Kapila. Anomaly noted independently by Amit Kapila
and KaiGai Kohei.
|
|
Commit 924bcf4f16d54c55310b28f77686608684734f42 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.
|
|
This refactors rewrite/rowsecurity.c to simplify the handling of the
default deny case (reducing the number of places where we check for and
add the default deny policy from three to one) by splitting up the
retrival of the policies from the application of them.
This also allowed us to do away with the policy_id field. A policy_name
field was added for WithCheckOption policies and is used in error
reporting, when available.
Patch by Dean Rasheed, with various mostly cosmetic changes by me.
Back-patch to 9.5 where RLS was introduced to avoid unnecessary
differences, since we're still in alpha, per discussion with Robert.
|
|
Until now we computed these Param ID sets at the end of subquery_planner,
but that approach depends on subquery_planner returning a concrete Plan
tree. We would like to switch over to returning one or more Paths for a
subquery, and in that representation the necessary details aren't fully
fleshed out (not to mention that we don't really want to do this work for
Paths that end up getting discarded). Hence, refactor so that we can
compute the param ID sets at the end of planning, just before
set_plan_references is run.
The main change necessary to make this work is that we need to capture
the set of outer-level Param IDs available to the current query level
before exiting subquery_planner, since the outer levels' plan_params lists
are transient. (That's not going to pose a problem for returning Paths,
since all the work involved in producing that data is part of expression
preprocessing, which will continue to happen before Paths are produced.)
On the plus side, this change gets rid of several existing kluges.
Eventually I'd like to get rid of SS_finalize_plan altogether in favor of
doing this work during set_plan_references, but that will require some
complex rejiggering because SS_finalize_plan needs to visit subplans and
initplans before the main plan. So leave that idea for another day.
|
|
A few of the discrepancies had semantic significance, but I did not
track down the resulting user-visible bugs, if any. Back-patch to 9.5,
where all but one discrepancy appeared. The _equalCreateEventTrigStmt()
situation dates to 9.3 but does not affect semantics.
catversion bump due to readfuncs.c field order changes.
|
|
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.
|
|
When the inner side of a nestloop SEMI or ANTI join is an indexscan that
uses all the join clauses as indexquals, it can be presumed that both
matched and unmatched outer rows will be processed very quickly: for
matched rows, we'll stop after fetching one row from the indexscan, while
for unmatched rows we'll have an indexscan that finds no matching index
entries, which should also be quick. The planner already knew about this,
but it was nonetheless charging for at least one full run of the inner
indexscan, as a consequence of concerns about the behavior of materialized
inner scans --- but those concerns don't apply in the fast case. If the
inner side has low cardinality (many matching rows) this could make an
indexscan plan look far more expensive than it actually is. To fix,
rearrange the work in initial_cost_nestloop/final_cost_nestloop so that we
don't add the inner scan cost until we've inspected the indexquals, and
then we can add either the full-run cost or just the first tuple's cost as
appropriate.
Experimentation with this fix uncovered another problem: add_path and
friends were coded to disregard cheap startup cost when considering
parameterized paths. That's usually okay (and desirable, because it thins
the path herd faster); but in this fast case for SEMI/ANTI joins, it could
result in throwing away the desired plain indexscan path in favor of a
bitmap scan path before we ever get to the join costing logic. In the
many-matching-rows cases of interest here, a bitmap scan will do a lot more
work than required, so this is a problem. To fix, add a per-relation flag
consider_param_startup that works like the existing consider_startup flag,
but applies to parameterized paths, and set it for relations that are the
inside of a SEMI or ANTI join.
To make this patch reasonably safe to back-patch, care has been taken to
avoid changing the planner's behavior except in the very narrow case of
SEMI/ANTI joins with inner indexscans. There are places in
compare_path_costs_fuzzily and add_path_precheck that are not terribly
consistent with the new approach, but changing them will affect planner
decisions at the margins in other cases, so we'll leave that for a
HEAD-only fix.
Back-patch to 9.3; before that, the consider_startup flag didn't exist,
meaning that the second aspect of the patch would be too invasive.
Per a complaint from Peter Holzer and analysis by Tomas Vondra.
|
|
Previously, INSERT with ON CONFLICT DO UPDATE specified used a new
command tag -- UPSERT. It was introduced out of concern that INSERT as
a command tag would be a misrepresentation for ON CONFLICT DO UPDATE, as
some affected rows may actually have been updated.
Alvaro Herrera noticed that the implementation of that new command tag
was incomplete; in subsequent discussion we concluded that having it
doesn't provide benefits that are in line with the compatibility breaks
it requires.
Catversion bump due to the removal of PlannedStmt->isUpsert.
Author: Peter Geoghegan
Discussion: 20150520215816.GI5885@postgresql.org
|
|
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 oversight results in a crash at executor startup if the plan has
been copied. outfuncs.c was missed as well.
While we could probably have taught both those files to cope with the
originally chosen representation of an Oid array, it would have been
painful, not least because there'd be no easy way to verify the array
length. An Oid List is far easier to work with. And AFAICS, there is
no particular notational benefit to using an array rather than a list
in the existing parts of the patch either. So just change it to a list.
Error in commit 35fcb1b3d038a501f3f4c87c05630095abaaadab, which is new,
so no need for back-patch.
|
|
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 e7cb7ee14555cc9c5773e2c102efd6371f6f2005 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.
|
|
Previously, relation range table entries used a single Bitmapset field
representing which columns required either UPDATE or INSERT privileges,
despite the fact that INSERT and UPDATE privileges are separately
cataloged, and may be independently held. As statements so far required
either insert or update privileges but never both, that was
sufficient. The required permission could be inferred from the top level
statement run.
The upcoming INSERT ... ON CONFLICT UPDATE feature needs to
independently check for both privileges in one statement though, so that
is not sufficient anymore.
Bumps catversion as stored rules change.
Author: Peter Geoghegan
Reviewed-By: Andres Freund
|
|
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.
|
