Like Gather, we spawn multiple workers and run the same plan in each
one; however, Gather Merge is used when each worker produces the same
output ordering and we want to preserve that output ordering while
merging together the streams of tuples from various workers. (In a
way, Gather Merge is like a hybrid of Gather and MergeAppend.)
This works out to a win if it saves us from having to perform an
expensive Sort. In cases where only a small amount of data would need
to be sorted, it may actually be faster to use a regular Gather node
and then sort the results afterward, because Gather Merge sometimes
needs to wait synchronously for tuples whereas a pure Gather generally
doesn't. But if this avoids an expensive sort then it's a win.
Rushabh Lathia, reviewed and tested by Amit Kapila, Thomas Munro,
and Neha Sharma, and reviewed and revised by me.
Discussion: http://postgr.es/m/CAGPqQf09oPX-cQRpBKS0Gq49Z+m6KBxgxd_p9gX8CKk_d75HoQ@mail.gmail.com
The index is scanned by a single process, but then all cooperating
processes can iterate jointly over the resulting set of heap blocks.
In the future, we might also want to support using a parallel bitmap
index scan to set up for a parallel bitmap heap scan, but that's a
job for another day.
Dilip Kumar, with some corrections and cosmetic changes by me. The
larger patch set of which this is a part has been reviewed and tested
by (at least) Andres Freund, Amit Khandekar, Tushar Ahuja, Rafia
Sabih, Haribabu Kommi, Thomas Munro, and me.
Discussion: http://postgr.es/m/CAFiTN-uc4=0WxRGfCzs-xfkMYcSEWUC-Fon6thkJGjkh9i=13A@mail.gmail.com
XMLTABLE is defined by the SQL/XML standard as a feature that allows
turning XML-formatted data into relational form, so that it can be used
as a <table primary> in the FROM clause of a query.
This new construct provides significant simplicity and performance
benefit for XML data processing; what in a client-side custom
implementation was reported to take 20 minutes can be executed in 400ms
using XMLTABLE. (The same functionality was said to take 10 seconds
using nested PostgreSQL XPath function calls, and 5 seconds using
XMLReader under PL/Python).
The implemented syntax deviates slightly from what the standard
requires. First, the standard indicates that the PASSING clause is
optional and that multiple XML input documents may be given to it; we
make it mandatory and accept a single document only. Second, we don't
currently support a default namespace to be specified.
This implementation relies on a new executor node based on a hardcoded
method table. (Because the grammar is fixed, there is no extensibility
in the current approach; further constructs can be implemented on top of
this such as JSON_TABLE, but they require changes to core code.)
Author: Pavel Stehule, Álvaro Herrera
Extensively reviewed by: Craig Ringer
Discussion: https://postgr.es/m/CAFj8pRAgfzMD-LoSmnMGybD0WsEznLHWap8DO79+-GTRAPR4qA@mail.gmail.com
This doesn't do anything to make Param nodes anything other than
parallel-restricted, so this only helps with uncorrelated subplans,
and it's not necessarily very cheap because each worker will run the
subplan separately (just as a Hash Join will build a separate copy of
the hash table in each participating process), but it's a first step
toward supporting cases that are more likely to help in practice, and
is occasionally useful on its own.
Amit Kapila, reviewed and tested by Rafia Sabih, Dilip Kumar, and
me.
Discussion: http://postgr.es/m/CAA4eK1+e8Z45D2n+rnDMDYsVEb5iW7jqaCH_tvPMYau=1Rru9w@mail.gmail.com
Evaluation of set returning functions (SRFs_ in the targetlist (like SELECT
generate_series(1,5)) so far was done in the expression evaluation (i.e.
ExecEvalExpr()) and projection (i.e. ExecProject/ExecTargetList) code.
This meant that most executor nodes performing projection, and most
expression evaluation functions, had to deal with the possibility that an
evaluated expression could return a set of return values.
That's bad because it leads to repeated code in a lot of places. It also,
and that's my (Andres's) motivation, made it a lot harder to implement a
more efficient way of doing expression evaluation.
To fix this, introduce a new executor node (ProjectSet) that can evaluate
targetlists containing one or more SRFs. To avoid the complexity of the old
way of handling nested expressions returning sets (e.g. having to pass up
ExprDoneCond, and dealing with arguments to functions returning sets etc.),
those SRFs can only be at the top level of the node's targetlist. The
planner makes sure (via split_pathtarget_at_srfs()) that SRF evaluation is
only necessary in ProjectSet nodes and that SRFs are only present at the
top level of the node's targetlist. If there are nested SRFs the planner
creates multiple stacked ProjectSet nodes. The ProjectSet nodes always get
input from an underlying node.
We also discussed and prototyped evaluating targetlist SRFs using ROWS
FROM(), but that turned out to be more complicated than we'd hoped.
While moving SRF evaluation to ProjectSet would allow to retain the old
"least common multiple" behavior when multiple SRFs are present in one
targetlist (i.e. continue returning rows until all SRFs are at the end of
their input at the same time), we decided to instead only return rows till
all SRFs are exhausted, returning NULL for already exhausted ones. We
deemed the previous behavior to be too confusing, unexpected and actually
not particularly useful.
As a side effect, the previously prohibited case of multiple set returning
arguments to a function, is now allowed. Not because it's particularly
desirable, but because it ends up working and there seems to be no argument
for adding code to prohibit it.
Currently the behavior for COALESCE and CASE containing SRFs has changed,
returning multiple rows from the expression, even when the SRF containing
"arm" of the expression is not evaluated. That's because the SRFs are
evaluated in a separate ProjectSet node. As that's quite confusing, we're
likely to instead prohibit SRFs in those places. But that's still being
discussed, and the code would reside in places not touched here, so that's
a task for later.
There's a lot of, now superfluous, code dealing with set return expressions
around. But as the changes to get rid of those are verbose largely boring,
it seems better for readability to keep the cleanup as a separate commit.
Author: Tom Lane and Andres Freund
Discussion: https://postgr.es/m/20160822214023.aaxz5l4igypowyri@alap3.anarazel.de
In an RLS query, we must ensure that security filter quals are evaluated
before ordinary query quals, in case the latter contain "leaky" functions
that could expose the contents of sensitive rows. The original
implementation of RLS planning ensured this by pushing the scan of a
secured table into a sub-query that it marked as a security-barrier view.
Unfortunately this results in very inefficient plans in many cases, because
the sub-query cannot be flattened and gets planned independently of the
rest of the query.
To fix, drop the use of sub-queries to enforce RLS qual order, and instead
mark each qual (RestrictInfo) with a security_level field establishing its
priority for evaluation. Quals must be evaluated in security_level order,
except that "leakproof" quals can be allowed to go ahead of quals of lower
security_level, if it's helpful to do so. This has to be enforced within
the ordering of any one list of quals to be evaluated at a table scan node,
and we also have to ensure that quals are not chosen for early evaluation
(i.e., use as an index qual or TID scan qual) if they're not allowed to go
ahead of other quals at the scan node.
This is sufficient to fix the problem for RLS quals, since we only support
RLS policies on simple tables and thus RLS quals will always exist at the
table scan level only. Eventually these qual ordering rules should be
enforced for join quals as well, which would permit improving planning for
explicit security-barrier views; but that's a task for another patch.
Note that FDWs would need to be aware of these rules --- and not, for
example, send an insecure qual for remote execution --- but since we do
not yet allow RLS policies on foreign tables, the case doesn't arise.
This will need to be addressed before we can allow such policies.
Patch by me, reviewed by Stephen Frost and Dean Rasheed.
Discussion: https://postgr.es/m/8185.1477432701@sss.pgh.pa.us
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
Now that it has only INH_NO and INH_YES values, it's just weird that
it's not a plain bool, so make it that way.
Also rename RangeVar.inhOpt to "inh", to be like RangeTblEntry.inh.
My recollection is that we gave it a different name specifically because
it had a different representation than the derived bool value, but it
no longer does. And this is a good forcing function to be sure we
catch any places that are affected by the change.
Bump catversion because of possible effect on stored RangeVar nodes.
I'm not exactly convinced that we ever store RangeVar on disk, but
we have a readfuncs function for it, so be cautious. (If we do do so,
then commit e13486eba was in error not to bump catversion.)
Follow-on to commit e13486eba.
Discussion: http://postgr.es/m/CA+TgmoYe+EG7LdYX6pkcNxr4ygkP4+A=jm9o-CPXyOvRiCNwaQ@mail.gmail.com
expandRTE() and get_rte_attribute_type() reported the exprType() and
exprTypmod() values of the expressions in the first row of the VALUES as
being the column type/typmod returned by the VALUES RTE. That's fine for
the data type, since we coerce all expressions in a column to have the same
common type. But we don't coerce them to have a common typmod, so it was
possible for rows after the first one to return values that violate the
claimed column typmod. This leads to the incorrect result seen in bug
#14448 from Hassan Mahmood, as well as some other corner-case misbehaviors.
The desired behavior is the same as we use in other type-unification
cases: report the common typmod if there is one, but otherwise return -1
indicating no particular constraint. It's cheap for transformValuesClause
to determine the common typmod while transforming a multi-row VALUES, but
it'd be less cheap for expandRTE() and get_rte_attribute_type() to
re-determine that info every time they're asked --- possibly a lot less
cheap, if the VALUES has many rows. Therefore, the best fix is to record
the common typmods explicitly in a list in the VALUES RTE, as we were
already doing for column collations. This looks quite a bit like what
we're doing for CTE RTEs, so we can save a little bit of space and code by
unifying the representation for those two RTE types. They both now share
coltypes/coltypmods/colcollations fields. (At some point it might seem
desirable to populate those fields for all RTE types; but right now it
looks like constructing them for other RTE types would add more code and
cycles than it would save.)
The RTE change requires a catversion bump, so this fix is only usable
in HEAD. If we fix this at all in the back branches, the patch will
need to look quite different.
Report: https://postgr.es/m/20161205143037.4377.60754@wrigleys.postgresql.org
Discussion: https://postgr.es/m/27429.1480968538@sss.pgh.pa.us
Table partitioning is like table inheritance and reuses much of the
existing infrastructure, but there are some important differences.
The parent is called a partitioned table and is always empty; it may
not have indexes or non-inherited constraints, since those make no
sense for a relation with no data of its own. The children are called
partitions and contain all of the actual data. Each partition has an
implicit partitioning constraint. Multiple inheritance is not
allowed, and partitioning and inheritance can't be mixed. Partitions
can't have extra columns and may not allow nulls unless the parent
does. Tuples inserted into the parent are automatically routed to the
correct partition, so tuple-routing ON INSERT triggers are not needed.
Tuple routing isn't yet supported for partitions which are foreign
tables, and it doesn't handle updates that cross partition boundaries.
Currently, tables can be range-partitioned or list-partitioned. List
partitioning is limited to a single column, but range partitioning can
involve multiple columns. A partitioning "column" can be an
expression.
Because table partitioning is less general than table inheritance, it
is hoped that it will be easier to reason about properties of
partitions, and therefore that this will serve as a better foundation
for a variety of possible optimizations, including query planner
optimizations. The tuple routing based which this patch does based on
the implicit partitioning constraints is an example of this, but it
seems likely that many other useful optimizations are also possible.
Amit Langote, reviewed and tested by Robert Haas, Ashutosh Bapat,
Amit Kapila, Rajkumar Raghuwanshi, Corey Huinker, Jaime Casanova,
Rushabh Lathia, Erik Rijkers, among others. Minor revisions by me.
This is infrastructure for the complete SQL standard feature. No
support is included at this point for execution nodes or PLs. The
intent is to add that soon.
As this patch leaves things, standard syntax can create tuplestores
to contain old and/or new versions of rows affected by a statement.
References to these tuplestores are in the TriggerData structure.
C triggers can access the tuplestores directly, so they are usable,
but they cannot yet be referenced within a SQL statement.
This function has no direct callers at present, but it's convenient for
manual use in a debugger, rather than having to inspect memory and do
bit-counting in your head.
In passing, get rid of useless outBitmapset() wrapper around
_outBitmapset(); let's just export the function that does the work.
Likewise for outToken().
Ashutosh Bapat, tweaked a bit by me
Discussion: <CAFjFpRdiht8e1HTVirbubr4YzaON5iZTzFJjq909y4sU8M_6eA@mail.gmail.com>
Teach the parser to reject misplaced set-returning functions during parse
analysis using p_expr_kind, in much the same way as we do for aggregates
and window functions (cf commit eaccfded9). While this isn't complete
(it misses nesting-based restrictions), it's much better than the previous
error reporting for such cases, and it allows elimination of assorted
ad-hoc expression_returns_set() error checks. We could add nesting checks
later if it seems important to catch all cases at parse time.
There is one case the parser will now throw error for although previous
versions allowed it, which is SRFs in the tlist of an UPDATE. That never
behaved sensibly (since it's ill-defined which generated row should be
used to perform the update) and it's hard to see why it should not be
treated as an error. It's a release-note-worthy change though.
Also, add a new Query field hasTargetSRFs reporting whether there are
any SRFs in the targetlist (including GROUP BY/ORDER BY expressions).
The parser can now set that basically for free during parse analysis,
and we can use it in a number of places to avoid expression_returns_set
searches. (There will be more such checks soon.) In some places, this
allows decontorting the logic since it's no longer expensive to check for
SRFs in the tlist --- so I made the checks parallel to the handling of
hasAggs/hasWindowFuncs wherever it seemed appropriate.
catversion bump because adding a Query field changes stored rules.
Andres Freund and Tom Lane
Discussion: <24639.1473782855@sss.pgh.pa.us>
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>
ExecReScanAgg's check for whether it could re-use a previously calculated
hashtable neglected the possibility that the Agg node might reference
PARAM_EXEC Params that are not referenced by its input plan node. That's
okay if the Params are in upper tlist or qual expressions; but if one
appears in aggregate input expressions, then the hashtable contents need
to be recomputed when the Param's value changes.
To avoid unnecessary performance degradation in the case of a Param that
isn't within an aggregate input, add logic to the planner to determine
which Params are within aggregate inputs. This requires a new field in
struct Agg, but fortunately we never write plans to disk, so this isn't
an initdb-forcing change.
Per report from Jeevan Chalke. This has been broken since forever,
so back-patch to all supported branches.
Andrew Gierth, with minor adjustments by me
Report: <CAM2+6=VY8ykfLT5Q8vb9B6EbeBk-NGuLbT6seaQ+Fq4zXvrDcA@mail.gmail.com>
We need to scan the whole parse tree for parallel-unsafe functions.
If there are none, we'll later need to determine whether particular
subtrees contain any parallel-restricted functions. The previous coding
retained no knowledge from the first scan, even though this is very
wasteful in the common case where the query contains only parallel-safe
functions. We can bypass all of the later scans by remembering that fact.
This provides a small but measurable speed improvement when the case
applies, and shouldn't cost anything when it doesn't.
Patch by me, reviewed by Robert Haas
Discussion: <3740.1471538387@sss.pgh.pa.us>
We implement a dozen or so parameterless functions that the SQL standard
defines special syntax for. Up to now, that was done by converting them
into more or less ad-hoc constructs such as "'now'::text::date". That's
messy for multiple reasons: it exposes what should be implementation
details to users, and performance is worse than it needs to be in several
cases. To improve matters, invent a new expression node type
SQLValueFunction that can represent any of these parameterless functions.
Bump catversion because this changes stored parsetrees for rules.
Discussion: <30058.1463091294@sss.pgh.pa.us>
Now that we've nailed down the principle that NullTest with !argisrow
is fully equivalent to SQL's IS [NOT] DISTINCT FROM NULL, let's teach
the parser about it. This produces a slightly more compact parse tree
and is much more amenable to optimization than a DistinctExpr, since
the planner knows a good deal about NullTest and next to nothing about
DistinctExpr.
I'm not sure that there are all that many queries in the wild that could
be improved by this, but at least one source of such cases is the patch
just made to postgres_fdw to emit IS [NOT] DISTINCT FROM NULL when
IS [NOT] NULL isn't semantically correct.
No back-patch, since to the extent that this does affect planning results,
it might be considered undesirable plan destabilization.
We must not push down a foreign join when the foreign tables involved
should be accessed under different user mappings. Previously we tried
to enforce that rule literally during planning, but that meant that the
resulting plans were dependent on the current contents of the
pg_user_mapping catalog, and we had to blow away all cached plans
containing any remote join when anything at all changed in pg_user_mapping.
This could have been improved somewhat, but the fact that a syscache inval
callback has very limited info about what changed made it hard to do better
within that design. Instead, let's change the planner to not consider user
mappings per se, but to allow a foreign join if both RTEs have the same
checkAsUser value. If they do, then they necessarily will use the same
user mapping at runtime, and we don't need to know specifically which one
that is. Post-plan-time changes in pg_user_mapping no longer require any
plan invalidation.
This rule does give up some optimization ability, to wit where two foreign
table references come from views with different owners or one's from a view
and one's directly in the query, but nonetheless the same user mapping
would have applied. We'll sacrifice the first case, but to not regress
more than we have to in the second case, allow a foreign join involving
both zero and nonzero checkAsUser values if the nonzero one is the same as
the prevailing effective userID. In that case, mark the plan as only
runnable by that userID.
The plancache code already had a notion of plans being userID-specific,
in order to support RLS. It was a little confused though, in particular
lacking clarity of thought as to whether it was the rewritten query or just
the finished plan that's dependent on the userID. Rearrange that code so
that it's clearer what depends on which, and so that the same logic applies
to both RLS-injected role dependency and foreign-join-injected role
dependency.
Note that this patch doesn't remove the other issue mentioned in the
original complaint, which is that while we'll reliably stop using a foreign
join if it's disallowed in a new context, we might fail to start using a
foreign join if it's now allowed, but we previously created a generic
cached plan that didn't use one. It was agreed that the chance of winning
that way was not high enough to justify the much larger number of plan
invalidations that would have to occur if we tried to cause it to happen.
In passing, clean up randomly-varying spelling of EXPLAIN commands in
postgres_fdw.sql, and fix a COSTS ON example that had been allowed to
leak into the committed tests.
This reverts most of commits fbe5a3fb7 and 5d4171d1c, which were the
previous attempt at ensuring we wouldn't push down foreign joins that
span permissions contexts.
Etsuro Fujita and Tom Lane
Discussion: <d49c1e5b-f059-20f4-c132-e9752ee0113e@lab.ntt.co.jp>
Commit 3fc6e2d7f5 introduced new "upper"
RelOptInfo structures but didn't set consider_parallel for them
correctly, a point I completely missed when reviewing it. Later,
commit e06a38965b made the situation
worse by doing it incorrectly for the grouping relation. Try to
straighten all of that out. Along the way, get rid of the annoying
wholePlanParallelSafe flag, which was only necessarily because of
the fact that upper planning stages didn't use paths at the time
that code was written.
The most important immediate impact of these changes is that
force_parallel_mode will provide useful test coverage in quite a few
more scenarios than it did previously, but it's also necessary
preparation for fixing some problems related to subqueries.
Patch by me, reviewed by Tom Lane.
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 original upper-planner-pathification design (commit 3fc6e2d7f5)
assumed that we could always determine during Path formation whether or not
we would need a Result plan node to perform projection of a targetlist.
That turns out not to work very well, though, because createplan.c still
has some responsibilities for choosing the specific target list associated
with sorting/grouping nodes (in particular it might choose to add resjunk
columns for sorting). We might not ever refactor that --- doing so would
push more work into Path formation, which isn't attractive --- and we
certainly won't do so for 9.6. So, while create_projection_path and
apply_projection_to_path can tell for sure what will happen if the subpath
is projection-capable, they can't tell for sure when it isn't. This is at
least a latent bug in apply_projection_to_path, which might think it can
apply a target to a non-projecting node when the node will end up computing
something different.
Also, I'd tied the creation of a ProjectionPath node to whether or not a
Result is needed, but it turns out that we sometimes need a ProjectionPath
node anyway to avoid modifying a possibly-shared subpath node. Callers had
to use create_projection_path for such cases, and we added code to them
that knew about the potential omission of a Result node and attempted to
adjust the cost estimates for that. That was uncertainly correct and
definitely ugly/unmaintainable.
To fix, have create_projection_path explicitly check whether a Result
is needed and adjust its cost estimate accordingly, though it creates
a ProjectionPath in either case. apply_projection_to_path is now mostly
just an optimized version that can avoid creating an extra Path node when
the input is known to not be shared with any other live path. (There
is one case that create_projection_path doesn't handle, which is pushing
parallel-safe expressions below a Gather node. We could make it do that
by duplicating the GatherPath, but there seems no need as yet.)
create_projection_plan still has to recheck the tlist-match condition,
which means that if the matching situation does get changed by createplan.c
then we'll have made a slightly incorrect cost estimate. But there seems
no help for that in the near term, and I doubt it occurs often enough,
let alone would change planning decisions often enough, to be worth
stressing about.
I added a "dummypp" field to ProjectionPath to track whether
create_projection_path thinks a Result is needed. This is not really
necessary as-committed because create_projection_plan doesn't look at the
flag; but it seems like a good idea to remember what we thought when
forming the cost estimate, if only for debugging purposes.
In passing, get rid of the target_parallel parameter added to
apply_projection_to_path by commit 54f5c5150. I don't think that's a good
idea because it involves callers in what should be an internal decision,
and opens us up to missing optimization opportunities if callers think they
don't need to provide a valid flag, as most don't. For the moment, this
just costs us an extra has_parallel_hazard call when planning a Gather.
If that starts to look expensive, I think a better solution would be to
teach PathTarget to carry/cache knowledge of parallel-safety of its
contents.
This patch provides a new implementation of the logic added by commit
137805f89 and later removed by 77ba61080. It differs from the original
primarily in expending much less effort per joinrel in large queries,
which it accomplishes by doing most of the matching work once per query not
once per joinrel. Hopefully, it's also less buggy and better commented.
The never-documented enable_fkey_estimates GUC remains gone.
There remains work to be done to make the selectivity estimates account
for nulls in FK referencing columns; but that was true of the original
patch as well. We may be able to address this point later in beta.
In the meantime, any error should be in the direction of overestimating
rather than underestimating joinrel sizes, which seems like the direction
we want to err in.
Tomas Vondra and Tom Lane
Discussion: <31041.1465069446@sss.pgh.pa.us>
When doing partial aggregation, the args list of the upper (combining)
Aggref node is replaced by a Var representing the output of the partial
aggregation steps, which has either the aggregate's transition data type
or a serialized representation of that. However, nodeAgg.c blindly
continued to use the args list as an indication of the user-level argument
types. This broke resolution of polymorphic transition datatypes at
executor startup (though it accidentally failed to fail for the ANYARRAY
case, which is likely the only one anyone had tested). Moreover, the
constructed FuncExpr passed to the finalfunc contained completely wrong
information, which would have led to bogus answers or crashes for any case
where the finalfunc examined that information (which is only likely to be
with polymorphic aggregates using a non-polymorphic transition type).
As an independent bug, apply_partialaggref_adjustment neglected to resolve
a polymorphic transition datatype before assigning it as the output type
of the lower-level Aggref node. This again accidentally failed to fail
for ANYARRAY but would be unlikely to work in other cases.
To fix the first problem, record the user-level argument types in a
separate OID-list field of Aggref, and look to that rather than the args
list when asking what the argument types were. (It turns out to be
convenient to include any "direct" arguments in this list too, although
those are not currently subject to being overwritten.)
Rather than adding yet another resolve_aggregate_transtype() call to fix
the second problem, add an aggtranstype field to Aggref, and store the
resolved transition type OID there when the planner first computes it.
(By doing this in the planner and not the parser, we can allow the
aggregate's transition type to change from time to time, although no DDL
support yet exists for that.) This saves nothing of consequence for
simple non-polymorphic aggregates, but for polymorphic transition types
we save a catalog lookup during executor startup as well as several
planner lookups that are new in 9.6 due to parallel query planning.
In passing, fix an error that was introduced into count_agg_clauses_walker
some time ago: it was applying exprTypmod() to something that wasn't an
expression node at all, but a TargetEntry. exprTypmod silently returned
-1 so that there was not an obvious failure, but this broke the intended
sensitivity of aggregate space consumption estimates to the typmod of
varchar and similar data types. This part needs to be back-patched.
Catversion bump due to change of stored Aggref nodes.
Discussion: <8229.1466109074@sss.pgh.pa.us>
Commit b12fd41c6 added a "reltarget_has_non_vars" field to RelOptInfo,
but failed to maintain it accurately. Since its only purpose was to skip
calls to has_parallel_hazard() in the simple case where a rel's targetlist
is all Vars, and that call is really pretty cheap in that case anyway, it
seems like this is just a case of premature optimization. Let's drop the
flag and do the calls unconditionally until it's proven that we need more
smarts here.
Such paths are unsafe. To make it cheaper to detect when this case
applies, track whether a relation's default PathTarget contains any
non-Vars. In most cases, the answer will be no, which enables us to
determine cheaply that the target list for a proposed path is
parallel-safe. However, subquery pull-up can create cases that
require us to inspect the target list more carefully.
Amit Kapila, reviewed by me.
This terminology provoked widespread complaints. So, instead, rename
the GUC max_parallel_degree to max_parallel_workers_per_gather
(leaving room for a possible future GUC max_parallel_workers that acts
as a system-wide limit), and rename the parallel_degree reloption to
parallel_workers. Rename structure members to match.
These changes create a dump/restore hazard for users of PostgreSQL
9.6beta1 who have set the reloption (or applied the GUC using ALTER
USER or ALTER DATABASE).
This commit reverts 137805f89 as well as the associated commits 015e88942,
5306df283, and 68d704edb. We found multiple bugs in this feature, and
there was concern about possible planner slowdown (though to be fair,
exhibiting a very large slowdown proved difficult). The way forward
requires a considerable rewrite, which may or may not be possible to
accomplish in time for beta2. In my judgment reviewing the rewrite will
be easier to accomplish starting from a clean slate, so let's temporarily
revert what's there now. This also leaves us in a safe state if it turns
out to be necessary to postpone the rewrite to the next development cycle.
Discussion: <20160429102531.GA13701@huehner.biz>
The way that PartialAggregate and FinalizeAggregate plan nodes were
displaying output columns before was bogus. Now, FinalizeAggregate
produces the same outputs as an Aggregate would have produced, while
PartialAggregate produces each of those outputs prefixed by the word
PARTIAL.
Discussion: 12585.1460737650@sss.pgh.pa.us
Patch by me, reviewed by David Rowley.
Previously bcac23d exposed a subset of support functions, namely the
ones Kaigai found useful. In
20160304193704.elq773pyg5fyl3mi@alap3.anarazel.de I mentioned that
there's some functions missing to use the facility in an external
project.
To avoid having to add functions piecemeal, add all the functions which
are used to define READ_* and WRITE_* macros; users of the extensible
node functionality are likely to need these. Additionally expose
outDatum(), which doesn't have it's own WRITE_ macro, as it needs
information from the embedding struct.
Discussion: 20160304193704.elq773pyg5fyl3mi@alap3.anarazel.de
Now indexes (but only B-tree for now) can contain "extra" column(s) which
doesn't participate in index structure, they are just stored in leaf
tuples. It allows to use index only scan by using single index instead
of two or more indexes.
Author: Anastasia Lubennikova with minor editorializing by me
Reviewers: David Rowley, Peter Geoghegan, Jeff Janes
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 19a541143a 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.
Robert Haas
Alvaro Herrera
Andres Freund
Tom Lane
Bruce Momjian
Kevin Grittner
Peter Eisentraut
Teodor Sigaev
Simon Riggs