The constraint exclusion feature checks for contradictions among scan
restriction clauses, as well as contradictions between those clauses and a
table's CHECK constraints. The first aspect of this testing can be useful
for non-table relations (such as subqueries or functions-in-FROM), but the
feature was coded with only the CHECK case in mind so we were applying it
only to plain-table RTEs. Move the relation_excluded_by_constraints call
so that it is applied to all RTEs not just plain tables. With the default
setting of constraint_exclusion this results in no extra work, but with
constraint_exclusion = ON we will detect optimizations that we missed
before (at the cost of more planner cycles than we expended before).
Per a gripe from Gunnlaugur Þór Briem. Experimentation with
his example also showed we were not being very bright about the case where
constraint exclusion is proven within a subquery within UNION ALL, so tweak
the code to allow set_append_rel_pathlist to recognize such cases.
Formerly, set_subquery_pathlist and other creators of plans for subqueries
saved only the rangetable and rowMarks lists from the lower-level
PlannerInfo. But there's no reason not to remember the whole PlannerInfo,
and indeed this turns out to simplify matters in a number of places.
The immediate reason for doing this was so that the subroot will still be
accessible when we're trying to extract column statistics out of an
already-planned subquery. But now that I've done it, it seems like a good
code-beautification effort in its own right.
I also chose to get rid of the transient subrtable and subrowmark fields in
SubqueryScan nodes, in favor of having setrefs.c look up the subquery's
RelOptInfo. That required changing all the APIs in setrefs.c to pass
PlannerInfo not PlannerGlobal, which was a large but quite mechanical
transformation.
One side-effect not foreseen at the beginning is that this finally broke
inheritance_planner's assumption that replanning the same subquery RTE N
times would necessarily give interchangeable results each time. That
assumption was always pretty risky, but now we really have to make a
separate RTE for each instance so that there's a place to carry the
separate subroots.
A PlaceHolderVar's expression might contain another, lower-level
PlaceHolderVar. If the outer PlaceHolderVar is used, the inner one
certainly will be also, and so we have to make sure that both of them get
into the placeholder_list with correct ph_may_need values during the
initial pre-scan of the query (before deconstruct_jointree starts).
We did this correctly for PlaceHolderVars appearing in the query quals,
but overlooked the issue for those appearing in the top-level targetlist;
with the result that nested placeholders referenced only in the targetlist
did not work correctly, as illustrated in bug #6154.
While at it, add some error checking to find_placeholder_info to ensure
that we don't try to create new placeholders after it's too late to do so;
they have to all be created before deconstruct_jointree starts.
Back-patch to 8.4 where the PlaceHolderVar mechanism was introduced.
glibc renders random() thread-safe by wrapping a futex lock around it;
testing reveals that this limits the performance of pgbench on machines
with many CPU cores. Rather than switching to random_r(), which is
only available on GNU systems and crashes unless you use undocumented
alchemy to initialize the random state properly, switch to our built-in
implementation of erand48(), which is both thread-safe and concurrent.
Since the list of reasons not to use the operating system's erand48()
is getting rather long, rename ours to pg_erand48() (and similarly
for our implementations of lrand48() and srand48()) and just always
use those. We were already doing this on Cygwin anyway, and the
glibc implementation is not quite thread-safe, so pgbench wouldn't
be able to use that either.
Per discussion with Tom Lane.
Regular aggregate functions in combination with, or within the arguments
of, window functions are OK per spec; they have the semantics that the
aggregate output rows are computed and then we run the window functions
over that row set. (Thus, this combination is not really useful unless
there's a GROUP BY so that more than one aggregate output row is possible.)
The case without GROUP BY could fail, as recently reported by Jeff Davis,
because sloppy construction of the Agg node's targetlist resulted in extra
references to possibly-ungrouped Vars appearing outside the aggregate
function calls themselves. See the added regression test case for an
example.
Fixing this requires modifying the API of flatten_tlist and its underlying
function pull_var_clause. I chose to make pull_var_clause's API for
aggregates identical to what it was already doing for placeholders, since
the useful behaviors turn out to be the same (error, report node as-is, or
recurse into it). I also tightened the error checking in this area a bit:
if it was ever valid to see an uplevel Var, Aggref, or PlaceHolderVar here,
that was a long time ago, so complain instead of ignoring them.
Backpatch into 9.1. The failure exists in 8.4 and 9.0 as well, but seeing
that it only occurs in a basically-useless corner case, it doesn't seem
worth the risks of changing a function API in a minor release. There might
be third-party code using pull_var_clause.
The previous coding failed to account properly for the costs of evaluating
the input expressions of aggregates and window functions, as seen in a
recent gripe from Claudio Freire. (I said at the time that it wasn't
counting these costs at all; but on closer inspection, it was effectively
charging these costs once per output tuple. That is completely wrong for
aggregates, and not exactly right for window functions either.)
There was also a hard-wired assumption that aggregates and window functions
had procost 1.0, which is now fixed to respect the actual cataloged costs.
The costing of WindowAgg is still pretty bogus, since it doesn't try to
estimate the effects of spilling data to disk, but that seems like a
separate issue.
This area was a few bricks shy of a load, and badly under-commented too.
We have to ensure that the generated targetlist entries for a set-operation
node expose the correct collation for each entry, since higher-level
processing expects the tlist to reflect the true ordering of the plan's
output.
This hackery wouldn't be necessary if SortGroupClause carried collation
info ... but making it do so would inject more pain in the parser than
would be saved here. Still, we might want to rethink that sometime.
Instead of playing cute games with pathkeys, just build a direct
representation of the intended sub-select, and feed it through
query_planner to get a Path for the index access. This is a bit slower
than 9.1's previous method, since we'll duplicate most of the overhead of
query_planner; but since the whole optimization only applies to rather
simple single-table queries, that probably won't be much of a problem in
practice. The advantage is that we get to do the right thing when there's
a partial index that needs the implicit IS NOT NULL clause to be usable.
Also, although this makes planagg.c be a bit more closely tied to the
ordering of operations in grouping_planner, we can get rid of some coupling
to lower-level parts of the planner. Per complaint from Marti Raudsepp.
All expression nodes now have an explicit output-collation field, unless
they are known to only return a noncollatable data type (such as boolean
or record). Also, nodes that can invoke collation-aware functions store
a separate field that is the collation value to pass to the function.
This avoids confusion that arises when a function has collatable inputs
and noncollatable output type, or vice versa.
Also, replace the parser's on-the-fly collation assignment method with
a post-pass over the completed expression tree. This allows us to use
a more complex (and hopefully more nearly spec-compliant) assignment
rule without paying for it in extra storage in every expression node.
Fix assorted bugs in the planner's handling of collations by making
collation one of the defining properties of an EquivalenceClass and
by converting CollateExprs into discardable RelabelType nodes during
expression preprocessing.
This patch implements data-modifying WITH queries according to the
semantics that the updates all happen with the same command counter value,
and in an unspecified order. Therefore one WITH clause can't see the
effects of another, nor can the outer query see the effects other than
through the RETURNING values. And attempts to do conflicting updates will
have unpredictable results. We'll need to document all that.
This commit just fixes the code; documentation updates are waiting on
author.
Marko Tiikkaja and Hitoshi Harada
This commit provides the core code and documentation needed. A contrib
module test case will follow shortly.
Shigeru Hanada, Jan Urbanski, Heikki Linnakangas
This adds collation support for columns and domains, a COLLATE clause
to override it per expression, and B-tree index support.
Peter Eisentraut
reviewed by Pavel Stehule, Itagaki Takahiro, Robert Haas, Noah Misch
This is a heavily revised version of builtin_knngist_core-0.9. The
ordering operators are no longer mixed in with actual quals, which would
have confused not only humans but significant parts of the planner.
Instead, ordering operators are carried separately throughout planning and
execution.
Since the API for ambeginscan and amrescan functions had to be changed
anyway, this commit takes the opportunity to rationalize that a bit.
RelationGetIndexScan no longer forces a premature index_rescan call;
instead, callers of index_beginscan must call index_rescan too. Aside from
making the AM-side initialization logic a bit less peculiar, this has the
advantage that we do not make a useless extra am_rescan call when there are
runtime key values. AMs formerly could not assume that the key values
passed to amrescan were actually valid; now they can.
Teodor Sigaev and Tom Lane
As per the ancient comment for set_rel_width, it really wasn't much good
for relations that aren't plain tables: it would never find any stats and
would always fall back on datatype-based estimates, which are often pretty
silly. Fix that by copying up width estimates from the subquery planning
process.
At some point we might want to do this for CTEs too, but that would be a
significantly more invasive patch because the sub-PlannerInfo is no longer
accessible by the time it's needed. I refrained from doing anything about
that, partly for fear of breaking the unmerged CTE-related patches.
In passing, also generate less bogus width estimates for whole-row Vars.
Per a gripe from Jon Nelson.
Formerly, we could convert a UNION ALL structure inside a subquery-in-FROM
into an appendrel, as a side effect of pulling up the subquery into its
parent; but top-level UNION ALL always caused use of plan_set_operations().
That didn't matter too much because you got an Append-based plan either
way. However, now that the appendrel code can do things with MergeAppend,
it's worthwhile to hack up the top-level case so it also uses appendrels.
This is a bit of a stopgap; but going much further than this will require
a major rewrite of the planner's set-operations support, which I'm not
prepared to undertake now. For the moment let's grab the low-hanging fruit.
Per my recent proposal, get rid of all the direct inspection of indexes
and manual generation of paths in planagg.c. Instead, set up
EquivalenceClasses for the aggregate argument expressions, and let the
regular path generation logic deal with creating paths that can satisfy
those sort orders. This makes planagg.c a bit more visible to the rest
of the planner than it was originally, but the approach is basically a lot
cleaner than before. A major advantage of doing it this way is that we get
MIN/MAX optimization on inheritance trees (using MergeAppend of indexscans)
practically for free, whereas in the old way we'd have had to add a whole
lot more duplicative logic.
One small disadvantage of this approach is that MIN/MAX aggregates can no
longer exploit partial indexes having an "x IS NOT NULL" predicate, unless
that restriction or something that implies it is specified in the query.
The previous implementation was able to use the added "x IS NOT NULL"
condition as an extra predicate proof condition, but in this version we
rely entirely on indexes that are considered usable by the main planning
process. That seems a fair tradeoff for the simplicity and functionality
gained.
Zoltan Boszormenyi exhibited a test case in which planning time was
dominated by construction of EquivalenceClasses and PathKeys that had no
actual relevance to the query (and in fact got discarded immediately).
This happened because we generated PathKeys describing the sort ordering of
every index on every table in the query, and only after that checked to see
if the sort ordering was relevant. The EC/PK construction code is O(N^2)
in the number of ECs, which is all right for the intended number of such
objects, but it gets out of hand if there are ECs for lots of irrelevant
indexes.
To fix, twiddle the handling of mergeclauses a little bit to ensure that
every interesting EC is created before we begin path generation. (This
doesn't cost anything --- in fact I think it's a bit cheaper than before
--- since we always eventually created those ECs anyway.) Then, if an
index column can't be found in any pre-existing EC, we know that that sort
ordering is irrelevant for the query. Instead of creating a useless EC,
we can just not build a pathkey for the index column in the first place.
The index will still be considered if it's useful for non-order-related
reasons, but we will think of its output as unsorted.
This patch eliminates the former need to sort the output of an Append scan
when an ordered scan of an inheritance tree is wanted. This should be
particularly useful for fast-start cases such as queries with LIMIT.
Original patch by Greg Stark, with further hacking by Hans-Jurgen Schonig,
Robert Haas, and Tom Lane.
This patch merges the responsibility for NOT-flattening into
eval_const_expressions' processing. It wasn't done that way originally
because prepqual.c is far older than eval_const_expressions. But putting
this work into eval_const_expressions saves one pass over the qual trees,
and in fact saves even more than that because we can exploit the knowledge
that the subexpressions have already been recursively simplified. Doing it
this way also lets us do it uniformly over all expressions, whereas
prepqual.c formerly just did it at top level to save cycles. That should
improve the planner's ability to recognize logically-equivalent constructs.
While at it, also add the ability to fold a NOT into BooleanTest and
NullTest constructs (the latter only for the scalar-datatype case).
Per discussion of bug #5702.
The point of a PlaceHolderVar is to allow a non-strict expression to be
evaluated below an outer join, after which its value bubbles up like a Var
and can be forced to NULL when the outer join's semantics require that.
However, there was a serious design oversight in that, namely that we
didn't ensure that there was actually a correct place in the plan tree
to evaluate the placeholder :-(. It may be necessary to delay evaluation
of an outer join to ensure that a placeholder that should be evaluated
below the join can be evaluated there. Per recent bug report from Kirill
Simonov.
Back-patch to 8.4 where the PlaceHolderVar mechanism was introduced.
In these cases a qual can get marked with the removable rel in its
required_relids, but this is just to schedule its evaluation correctly, not
because it really depends on the rel. We were assuming that, in effect,
we could throw away *all* quals so marked, which is nonsense. Tighten up
the logic to be a little more paranoid about which quals belong to the
outer join being considered for removal, and arrange for all quals that
don't belong to be updated so they will still get evaluated correctly.
Also fix another problem that happened to be exposed by this test case,
which was that make_join_rel() was failing to notice some cases where
a constant-false qual could be used to prove a join relation empty. If it's
a pushed-down constant false, then the relation is empty even if it's an
outer join, because the qual applies after the outer join expansion.
Per report from Nathan Grange. Back-patch into 9.0.
relation using the general PARAM_EXEC executor parameter mechanism, rather
than the ad-hoc kluge of passing the outer tuple down through ExecReScan.
The previous method was hard to understand and could never be extended to
handle parameters coming from multiple join levels. This patch doesn't
change the set of possible plans nor have any significant performance effect,
but it's necessary infrastructure for future generalization of the concept
of an inner indexscan plan.
ExecReScan's second parameter is now unused, so it's removed.
The logic for determining whether to materialize has been significantly
overhauled for 9.0. In case there should be any doubt about whether
materialization is a win in any particular case, this should provide a
convenient way of seeing what happens without it; but even with enable_material
turned off, we still materialize in cases where it is required for
correctness.
Thanks to Tom Lane for the review.
This patch allows the frame to start from CURRENT ROW (in either RANGE or
ROWS mode), and it also adds support for ROWS n PRECEDING and ROWS n FOLLOWING
start and end points. (RANGE value PRECEDING/FOLLOWING isn't there yet ---
the grammar works, but that's all.)
Hitoshi Harada, reviewed by Pavel Stehule
parse analysis phase, rather than at execution time. This makes parameter
handling work the same as it does in ordinary plannable queries, and in
particular fixes the incompatibility that Pavel pointed out with plpgsql's
new handling of variable references. plancache.c gets a little bit
grottier, but the alternatives seem worse.
to be just a minor extension of the previous patch that made "x IS NULL"
indexable, because we can treat the IS NOT NULL condition as if it were
"x < NULL" or "x > NULL" (depending on the index's NULLS FIRST/LAST option),
just like IS NULL is treated like "x = NULL". Aside from any possible
usefulness in its own right, this is an important improvement for
index-optimized MAX/MIN aggregates: it is now reliably possible to get
a column's min or max value cheaply, even when there are a lot of nulls
cluttering the interesting end of the index.
non-kluge method for controlling the order in which values are fed to an
aggregate function. At the same time eliminate the old implementation
restriction that DISTINCT was only supported for single-argument aggregates.
Possibly release-notable behavioral change: formerly, agg(DISTINCT x)
dropped null values of x unconditionally. Now, it does so only if the
agg transition function is strict; otherwise nulls are treated as DISTINCT
normally would, ie, you get one copy.
Andrew Gierth, reviewed by Hitoshi Harada
by adding a requirement that build_join_rel add new join RelOptInfos to the
appropriate list immediately at creation. Per report from Robert Haas,
the list_concat_unique_ptr() calls that this change eliminates were taking
the lion's share of the runtime in larger join problems. This doesn't do
anything to fix the fundamental combinatorial explosion in large join
problems, but it should push out the threshold of pain a bit further.
Note: because this changes the order in which joinrel lists are built,
it might result in changes in selected plans in cases where different
alternatives have exactly the same costs. There is one example in the
regression tests.
mergejoin to shield it from doing mark/restore and refetches. Put an explicit
flag in MergePath so we can centralize the logic that knows about this,
and add costing logic that considers using Materialize even when it's not
forced by the previously-existing considerations. This is in response to
a discussion back in August that suggested that materializing an inner
indexscan can be helpful when the refetch percentage is high enough.
a lot of strange behaviors that occurred in join cases. We now identify the
"current" row for every joined relation in UPDATE, DELETE, and SELECT FOR
UPDATE/SHARE queries. If an EvalPlanQual recheck is necessary, we jam the
appropriate row into each scan node in the rechecking plan, forcing it to emit
only that one row. The former behavior could rescan the whole of each joined
relation for each recheck, which was terrible for performance, and what's much
worse could result in duplicated output tuples.
Also, the original implementation of EvalPlanQual could not re-use the recheck
execution tree --- it had to go through a full executor init and shutdown for
every row to be tested. To avoid this overhead, I've associated a special
runtime Param with each LockRows or ModifyTable plan node, and arranged to
make every scan node below such a node depend on that Param. Thus, by
signaling a change in that Param, the EPQ machinery can just rescan the
already-built test plan.
This patch also adds a prohibition on set-returning functions in the
targetlist of SELECT FOR UPDATE/SHARE. This is needed to avoid the
duplicate-output-tuple problem. It seems fairly reasonable since the
other restrictions on SELECT FOR UPDATE are meant to ensure that there
is a unique correspondence between source tuples and result tuples,
which an output SRF destroys as much as anything else does.
execMain.c and into a new plan node type LockRows. Like the recent change
to put table updating into a ModifyTable plan node, this increases planning
flexibility by allowing the operations to occur below the top level of the
plan tree. It's necessary in any case to restore the previous behavior of
having FOR UPDATE locking occur before ModifyTable does.
This partially refactors EvalPlanQual to allow multiple rows-under-test
to be inserted into the EPQ machinery before starting an EPQ test query.
That isn't sufficient to fix EPQ's general bogosity in the face of plans
that return multiple rows per test row, though. Since this patch is
mostly about getting some plan node infrastructure in place and not about
fixing ten-year-old bugs, I will leave EPQ improvements for another day.
Another behavioral change that we could now think about is doing FOR UPDATE
before LIMIT, but that too seems like it should be treated as a followon
patch.
They are now handled by a new plan node type called ModifyTable, which is
placed at the top of the plan tree. In itself this change doesn't do much,
except perhaps make the handling of RETURNING lists and inherited UPDATEs a
tad less klugy. But it is necessary preparation for the intended extension of
allowing RETURNING queries inside WITH.
Marko Tiikkaja
is unique and is not referenced above the join. In this case the inner
side doesn't affect the query result and can be thrown away entirely.
Although perhaps nobody would ever write such a thing by hand, it's
a reasonably common case in machine-generated SQL.
The current implementation only recognizes the case where the inner side
is a simple relation with a unique index matching the query conditions.
This is enough for the use-cases that have been shown so far, but we
might want to try to handle other cases later.
Robert Haas, somewhat rewritten by Tom
an explicit model of rescan costs being different from first-time costs.
The costing of Material nodes in particular now has some visible relationship
to the actual runtime behavior, where before it was essentially fantasy.
This also fixes up a couple of places where different materialized plan types
were treated differently for no very good reason (probably just oversights).
A couple of the regression tests are affected, because the planner now chooses
to put the other relation on the inside of a nestloop-with-materialize.
So far as I can see both changes are sane, and the planner is now more
consistently following the expectation that it should prefer to materialize
the smaller of two relations.
Per a recent discussion with Robert Haas.
random number seed each time. This is how it used to work years ago, but
we got rid of the seed reset because it was resetting the main random()
sequence and thus having undesirable effects on the rest of the system.
To fix, establish a private random number state for each execution of
geqo(), and initialize the state using the new GUC variable geqo_seed.
People who want to experiment with different random searches can do so
by changing geqo_seed, but you'll always get the same plan for the same
value of geqo_seed (if holding all other planner inputs constant, of course).
The new state is kept in PlannerInfo by adding a "void *" field reserved
for use by join_search hooks. Most of the rather bulky code changes in
this commit are just arranging to pass PlannerInfo around to all the GEQO
functions (many of which formerly didn't receive it).
Andres Freund, with some editorialization by Tom
This alters various incidental uses of C++ key words to use other similar
identifiers, so that a C++ compiler won't choke outright. You still
(probably) need extern "C" { }; around the inclusion of backend headers.
based on a patch by Kurt Harriman <harriman@acm.org>
Also add a script cpluspluscheck to check for C++ compatibility in the
future. As of right now, this passes without error for me.
substituting a child rel's output expressions into the appendrel's restriction
clauses yields a pseudoconstant restriction. We might be able to skip scanning
that child rel entirely (if we get constant FALSE), or generate a one-time
filter. 8.3 more or less accidentally generated plans that weren't completely
stupid in these cases, but that was only because an extra recursive level of
subquery_planner() always occurred and allowed const-simplification to happen.
8.4's ability to pull up appendrel members with non-Var outputs exposes the
fact that we need to work harder here. Per gripe from Sergey Burladyan.
find_inheritance_children() and find_all_inheritors(). I got annoyed that
these are buried inside the planner but mostly used elsewhere. So, create
a new file catalog/pg_inherits.c and put them there, along with a couple
of other functions that search pg_inherits.
The code that modifies pg_inherits is (still) in tablecmds.c --- it's
kind of entangled with unrelated code that modifies pg_depend and other
stuff, so pulling it out seemed like a bigger change than I wanted to make
right now. But this file provides a natural home for it if anyone ever
gets around to that.
This commit just moves code around; it doesn't change anything, except
I succumbed to the temptation to make a couple of trivial optimizations
in typeInheritsFrom().
joins a bit better, ie, understand the differing cost functions for matched
and unmatched outer tuples. There is more that could be done in cost_hashjoin
but this already helps a great deal. Per discussions with Robert Haas.
PlaceHolderVar nodes in join quals appearing in or below the lowest
outer join that could null the subquery being pulled up. This improves
the planner's ability to recognize constant join quals, and probably
helps with detection of common sort keys (equivalence classes) as well.
Stefan Kaltenbrunner. The most reasonable behavior (at least for the near
term) seems to be to ignore the PlaceHolderVar and examine its argument
instead. In support of this, change the API of pull_var_clause() to allow
callers to request recursion into PlaceHolderVars. Currently
estimate_num_groups() is the only customer for that behavior, but where
there's one there may be others.
constants through full joins, as in
select * from tenk1 a full join tenk1 b using (unique1)
where unique1 = 42;
which should generate a fairly cheap plan where we apply the constraint
unique1 = 42 in each relation scan. This had been broken by my patch of
2008-06-27, which is now reverted in favor of a more invasive but hopefully
less incorrect approach. That patch was meant to prevent incorrect extraction
of OR'd indexclauses from OR conditions above an outer join. To do that
correctly we need more information than the outerjoin_delay flag can provide,
so add a nullable_relids field to RestrictInfo that records exactly which
relations are nulled by outer joins that are underneath a particular qual
clause. A side benefit is that we can make the test in create_or_index_quals
more specific: it is now smart enough to extract an OR'd indexclause into the
outer side of an outer join, even though it must not do so in the inner side.
The old coding couldn't distinguish these cases so it could not do either.
making pull_up_sublinks() construct a full-blown JoinExpr tree representation
of IN/EXISTS SubLinks that it is able to convert to semi or anti joins.
This makes pull_up_sublinks() a shade more complex, but the gain in semantic
clarity is worth it. I still have more to do in this area to address the
previously-discussed problems, but this commit in itself fixes at least one
bug in HEAD, as shown by added regression test case.
that are set up for execution with ExecPrepareExpr rather than going through
the full planner process. By introducing an explicit notion of "expression
planning", this patch also lays a bit of groundwork for maybe someday
allowing sub-selects in standalone expressions.
the default. This setting enables constraint exclusion checks only for
appendrel members (ie, inheritance children and UNION ALL arms), which are
the cases in which constraint exclusion is most likely to be useful. Avoiding
the overhead for simple queries that are unlikely to benefit should bring
the cost down to the point where this is a reasonable default setting.
Per today's discussion.
patch. This includes the ability to force the frame to cover the whole
partition, and the ability to make the frame end exactly on the current row
rather than its last ORDER BY peer. Supporting any more of the full SQL
frame-clause syntax will require nontrivial hacking on the window aggregate
code, so it'll have to wait for 8.5 or beyond.
we extended the appendrel mechanism to support UNION ALL optimization. The
reason nobody noticed was that we are not actually using attr_needed data for
appendrel children; hence it seems more reasonable to rip it out than fix it.
Back-patch to 8.2 because an Assert failure is possible in corner cases.
Per examination of an example from Jim Nasby.
In HEAD, also get rid of AppendRelInfo.col_mappings, which is quite inadequate
to represent UNION ALL situations; depend entirely on translated_vars instead.
that represent some expression that we desire to compute below the top level
of the plan, and then let that value "bubble up" as though it were a plain
Var (ie, a column value).
The immediate application is to allow sub-selects to be flattened even when
they are below an outer join and have non-nullable output expressions.
Formerly we couldn't flatten because such an expression wouldn't properly
go to NULL when evaluated above the outer join. Now, we wrap it in a
PlaceHolderVar and arrange for the actual evaluation to occur below the outer
join. When the resulting Var bubbles up through the join, it will be set to
NULL if necessary, yielding the correct results. This fixes a planner
limitation that's existed since 7.1.
In future we might want to use this mechanism to re-introduce some form of
Hellerstein's "expensive functions" optimization, ie place the evaluation of
an expensive function at the most suitable point in the plan tree.
implementation uses an in-memory hash table, so it will poop out for very
large recursive results ... but the performance characteristics of a
sort-based implementation would be pretty unpleasant too.
There are some unimplemented aspects: recursive queries must use UNION ALL
(should allow UNION too), and we don't have SEARCH or CYCLE clauses.
These might or might not get done for 8.4, but even without them it's a
pretty useful feature.
There are also a couple of small loose ends and definitional quibbles,
which I'll send a memo about to pgsql-hackers shortly. But let's land
the patch now so we can get on with other development.
Yoshiyuki Asaba, with lots of help from Tatsuo Ishii and Tom Lane
when user-defined functions used in a plan are modified. Also invalidate
plans when schemas, operators, or operator classes are modified; but for these
cases we just invalidate everything rather than tracking exact dependencies,
since these types of objects seldom change in a production database.
Tom Lane; loosely based on a patch by Martin Pihlak.
into nodes/nodeFuncs, so as to reduce wanton cross-subsystem #includes inside
the backend. There's probably more that should be done along this line,
but this is a start anyway.
subqueries into the same thing you'd have gotten from IN (except always with
unknownEqFalse = true, so as to get the proper semantics for an EXISTS).
I believe this fixes the last case within CVS HEAD in which an EXISTS could
give worse performance than an equivalent IN subquery.
The tricky part of this is that if the upper query probes the EXISTS for only
a few rows, the hashing implementation can actually be worse than the default,
and therefore we need to make a cost-based decision about which way to use.
But at the time when the planner generates plans for subqueries, it doesn't
really know how many times the subquery will be executed. The least invasive
solution seems to be to generate both plans and postpone the choice until
execution. Therefore, in a query that has been optimized this way, EXPLAIN
will show two subplans for the EXISTS, of which only one will actually get
executed.
There is a lot more that could be done based on this infrastructure: in
particular it's interesting to consider switching to the hash plan if we start
out using the non-hashed plan but find a lot more upper rows going by than we
expected. I have therefore left some minor inefficiencies in place, such as
initializing both subplans even though we will currently only use one.
level of a JOIN/ON clause, not only at top level of WHERE. (However, we
can't do this in an outer join's ON clause, unless the ANY/EXISTS refers
only to the nullable side of the outer join, so that it can effectively
be pushed down into the nullable side.) Per request from Kevin Grittner.
In passing, fix a bug in the initial implementation of EXISTS pullup:
it would Assert if the EXIST's WHERE clause used a join alias variable.
Since we haven't yet flattened join aliases when this transformation
happens, it's necessary to include join relids in the computed set of
RHS relids.
and anti joins. To do this, pass the SpecialJoinInfo struct for the current
join as an additional optional argument to operator join selectivity
estimation functions. This allows the estimator to tell not only what kind
of join is being formed, but which variable is on which side of the join;
a requirement long recognized but not dealt with till now. This also leaves
the door open for future improvements in the estimators, such as accounting
for the null-insertion effects of lower outer joins. I didn't do anything
about that in the current patch but the information is in principle deducible
from what's passed.
The patch also clarifies the definition of join selectivity for semi/anti
joins: it's the fraction of the left input that has (at least one) match
in the right input. This allows getting rid of some very fuzzy thinking
that I had committed in the original 7.4-era IN-optimization patch.
There's probably room to estimate this better than the present patch does,
but at least we know what to estimate.
Since I had to touch CREATE OPERATOR anyway to allow a variant signature
for join estimator functions, I took the opportunity to add a couple of
additional checks that were missing, per my recent message to -hackers:
* Check that estimator functions return float8;
* Require execute permission at the time of CREATE OPERATOR on the
operator's function as well as the estimator functions;
* Require ownership of any pre-existing operator that's modified by
the command.
I also moved the lookup of the functions out of OperatorCreate() and
into operatorcmds.c, since that seemed more consistent with most of
the other catalog object creation processes, eg CREATE TYPE.
the old JOIN_IN code, but antijoins are new functionality.) Teach the planner
to convert appropriate EXISTS and NOT EXISTS subqueries into semi and anti
joins respectively. Also, LEFT JOINs with suitable upper-level IS NULL
filters are recognized as being anti joins. Unify the InClauseInfo and
OuterJoinInfo infrastructure into "SpecialJoinInfo". With that change,
it becomes possible to associate a SpecialJoinInfo with every join attempt,
which permits some cleanup of join selectivity estimation. That needs to be
taken much further than this patch does, but the next step is to change the
API for oprjoin selectivity functions, which seems like material for a
separate patch. So for the moment the output size estimates for semi and
especially anti joins are quite bogus.
hashtable entries for tuples that are found only in the second input: they
can never contribute to the output. Furthermore, this implies that the
planner should endeavor to put first the smaller (in number of groups) input
relation for an INTERSECT. Implement that, and upgrade prepunion's estimation
of the number of rows returned by setops so that there's some amount of sanity
in the estimate of which one is smaller.
This completes my project of improving usage of hashing for duplicate
elimination (aggregate functions with DISTINCT remain undone, but that's
for some other day).
As with the previous patches, this means we can INTERSECT/EXCEPT on datatypes
that can hash but not sort, and it means that INTERSECT/EXCEPT without ORDER
BY are no longer certain to produce sorted output.
but seem like a separate patch since most of the remaining work is on the
executor side.) I took the opportunity to push selection of the grouping
operators for set operations into the parser where it belongs. Otherwise this
is just a small exercise in making prepunion.c consider both alternatives.
As with the recent DISTINCT patch, this means we can UNION on datatypes that
can hash but not sort, and it means that UNION without ORDER BY is no longer
certain to produce sorted output.
as per my recent proposal:
1. Fold SortClause and GroupClause into a single node type SortGroupClause.
We were already relying on them to be struct-equivalent, so using two node
tags wasn't accomplishing much except to get in the way of comparing items
with equal().
2. Add an "eqop" field to SortGroupClause to carry the associated equality
operator. This is cheap for the parser to get at the same time it's looking
up the sort operator, and storing it eliminates the need for repeated
not-so-cheap lookups during planning. In future this will also let us
represent GROUP/DISTINCT operations on datatypes that have hash opclasses
but no btree opclasses (ie, they have equality but no natural sort order).
The previous representation simply didn't work for that, since its only
indicator of comparison semantics was a sort operator.
3. Add a hasDistinctOn boolean to struct Query to explicitly record whether
the distinctClause came from DISTINCT or DISTINCT ON. This allows removing
some complicated and not 100% bulletproof code that attempted to figure
that out from the distinctClause alone.
This patch doesn't in itself create any new capability, but it's necessary
infrastructure for future attempts to use hash-based grouping for DISTINCT
and UNION/INTERSECT/EXCEPT.
the current query level that aren't in fact output parameters of the current
initPlans. (This means, for example, output parameters of regular subplans.)
To make this work correctly for output parameters coming from sibling
initplans requires rejiggering the API of SS_finalize_plan just a bit:
we need the siblings to be visible to it, rather than hidden as
SS_make_initplan_from_plan had been doing. This is really part of my response
to bug #4290, but I concluded this part probably shouldn't be back-patched,
since all that it's doing is to make a debugging cross-check tighter.
corresponding struct definitions. This allows other headers to avoid including
certain highly-loaded headers such as rel.h and relscan.h, instead using just
relcache.h, heapam.h or genam.h, which are more lightweight and thus cause less
unnecessary dependencies.
we had several code paths where a physical tlist could be used for the input
to a Sort node, which is a dumb idea because any unneeded table columns will
increase the volume of data the sort has to push around.
(Unfortunately the easy-looking fix of calling disuse_physical_tlist during
make_sort_xxx doesn't work because in most cases we're already committed to
the current input tlist --- it's been marked with sort column numbers, or
we've built grouping column numbers using it, etc. The tlist has to be
selected properly at the calling level before we start constructing sort-col
information. This is easy enough to do, we were just failing to take the
point into consideration.)
Back-patch to 8.3. I believe the problem probably exists clear back to 7.4
when the physical tlist optimization was added, but I'm afraid to back-patch
further than 8.3 without a great deal more study than I want to put into it.
The code in this area has drifted a lot over time. The real-world importance
of these code paths is uncertain anyway --- I think in many cases we'd
probably prefer hash-based methods.
eval_const_expressions needs to be passed the PlannerInfo ("root") structure,
because in some cases we want it to substitute values for Param nodes.
(So "constant" is not so constant as all that ...) This mistake partially
disabled optimization of unnamed extended-Query statements in 8.3: in
particular the LIKE-to-indexscan optimization would never be applied if the
LIKE pattern was passed as a parameter, and constraint exclusion depending
on a parameter value didn't work either.
are declared to return set, and consist of just a single SELECT. We
can replace the FROM-item with a sub-SELECT and then optimize much as
if we were dealing with a view. Patch from Richard Rowell, cleaned up
by me.
two buckets at the start, we create a number of buckets appropriate for the
estimated size of the table. This avoids a lot of expensive bucket-split
actions during initial index build on an already-populated table.
This is one of the two core ideas of Tom Raney and Shreya Bhargava's patch
to reduce hash index build time. I'm committing it separately to make it
easier for people to test the effects of this separately from the effects
of their other core idea (pre-sorting the index entries by bucket number).
predictable manner; in particular that if you say ORDER BY output-column-ref,
it will in fact sort by that specific column even if there are multiple
syntactic matches. An example is
SELECT random() AS a, random() AS b FROM ... ORDER BY b, a;
While the use-case for this might be a bit debatable, it worked as expected
in earlier releases, so we should preserve the behavior for 8.3. Per my
recent proposal.
While at it, fix convert_subquery_pathkeys() to handle RelabelType stripping
in both directions; it needs this for the same reasons make_sort_from_pathkeys
does.
to be able to discard top-level RelabelType nodes on *both* sides of the
equivalence-class-to-target-list comparison, since make_pathkey_from_sortinfo
might either add or remove a RelabelType. Also fix the latter to do the
removal case cleanly. Per example from Peter.
a relation as a reason to invalidate a plan when the relation changes. This
handles scenarios such as dropping/recreating a sequence that is referenced by
nextval('seq') in a cached plan. Rather than teach plancache.c all about
digging through plan trees to find regclass Consts, we charge the planner's
setrefs.c with making a list of the relation OIDs on which each plan depends.
That way the list can be built cheaply during a plan tree traversal that has
to happen anyway. Per bug #3662 and subsequent discussion.
eval_const_expressions simplifies this to just "WHERE false", but we have
already done pull_up_IN_clauses so the IN join will be done, or at least
planned, anyway. The trouble case comes when the sub-SELECT is itself a join
and we decide to implement the IN by unique-ifying the sub-SELECT outputs:
with no remaining reference to the output Vars in WHERE, we won't have
propagated the Vars up to the upper join point, leading to "variable not found
in subplan target lists" error. Fix by adding an extra scan of in_info_list
and forcing all Vars mentioned therein to be propagated up to the IN join
point. Per bug report from Miroslav Sulc.
join search order portion of the planner; this is specifically intended to
simplify developing a replacement for GEQO planning. Patch by Julius
Stroffek, editorialized on by me. I renamed make_one_rel_by_joins to
standard_join_search and make_rels_by_joins to join_search_one_level to better
reflect their place within this scheme.
(because they are uncorrelated with the immediate parent query). We were
charging the full run cost to the parent node, disregarding the fact that
only one row need be fetched for EXISTS. While this would only be a
cosmetic issue in most cases, it might possibly affect planning outcomes
if the parent query were itself a subquery to some upper query.
Per recent discussion with Steve Crawford.
columns, and the new version can be stored on the same heap page, we no longer
generate extra index entries for the new version. Instead, index searches
follow the HOT-chain links to ensure they find the correct tuple version.
In addition, this patch introduces the ability to "prune" dead tuples on a
per-page basis, without having to do a complete VACUUM pass to recover space.
VACUUM is still needed to clean up dead index entries, however.
Pavan Deolasee, with help from a bunch of other people.
and/or create plans for hypothetical situations; in particular, investigate
plans that would be generated using hypothetical indexes. This is a
heavily-rewritten version of the hooks proposed by Gurjeet Singh for his
Index Advisor project. In this formulation, the index advisor can be
entirely a loadable module instead of requiring a significant part to be
in the core backend, and plans can be generated for hypothetical indexes
without requiring the creation and rolling-back of system catalog entries.
The index advisor patch as-submitted is not compatible with these hooks,
but it needs significant work anyway due to other 8.2-to-8.3 planner
changes. With these hooks in the core backend, development of the advisor
can proceed as a pgfoundry project.
cheapest-startup-cost innerjoin indexscans, and make joinpath.c consider
both of these (when different) as the inside of a nestloop join. The
original design was based on the assumption that indexscan paths always
have negligible startup cost, and so total cost is the only important
figure of merit; an assumption that's obviously broken by bitmap
indexscans. This oversight could lead to choosing poor plans in cases
where fast-start behavior is more important than total cost, such as
LIMIT and IN queries. 8.1-vintage brain fade exposed by an example from
Chuck D.
is using mark/restore but not rewind or backward-scan capability. Insert a
materialize plan node between a mergejoin and its inner child if the inner
child is a sort that is expected to spill to disk. The materialize shields
the sort from the need to do mark/restore and thereby allows it to perform
its final merge pass on-the-fly; while the materialize itself is normally
cheap since it won't spill to disk unless the number of tuples with equal
key values exceeds work_mem.
Greg Stark, with some kibitzing from Tom Lane.
need be returned. We keep a heap of the current best N tuples and sift-up
new tuples into it as we scan the input. For M input tuples this means
only about M*log(N) comparisons instead of M*log(M), not to mention a lot
less workspace when N is small --- avoiding spill-to-disk for large M
is actually the most attractive thing about it. Patch includes planner
and executor support for invoking this facility in ORDER BY ... LIMIT
queries. Greg Stark, with some editorialization by moi.
access to the planner's cursor-related planning options, and provide new
FETCH/MOVE routines that allow access to the full power of those commands.
Small refactoring of planner(), pg_plan_query(), and pg_plan_queries()
APIs to make it convenient to pass the planning options down from SPI.
This is the core-code portion of Pavel Stehule's patch for scrollable
cursor support in plpgsql; I'll review and apply the plpgsql changes
separately.
possibly be any useful pathkeys --- to wit, queries with neither any
join clauses nor any ORDER BY request. It's nearly free to check for
this case and it saves a useful fraction of the planning time for simple
queries.
useless substructure for its RangeTblEntry nodes. (I chose to keep using the
same struct node type and just zero out the link fields for unneeded info,
rather than making a separate ExecRangeTblEntry type --- it seemed too
fragile to have two different rangetable representations.)
Along the way, put subplans into a list in the toplevel PlannedStmt node,
and have SubPlan nodes refer to them by list index instead of direct pointers.
Vadim wanted to do that years ago, but I never understood what he was on about
until now. It makes things a *whole* lot more robust, because we can stop
worrying about duplicate processing of subplans during expression tree
traversals. That's been a constant source of bugs, and it's finally gone.
There are some consequent simplifications yet to be made, like not using
a separate EState for subplans in the executor, but I'll tackle that later.
storing mostly-redundant Query trees in prepared statements, portals, etc.
To replace Query, a new node type called PlannedStmt is inserted by the
planner at the top of a completed plan tree; this carries just the fields of
Query that are still needed at runtime. The statement lists kept in portals
etc. now consist of intermixed PlannedStmt and bare utility-statement nodes
--- no Query. This incidentally allows us to remove some fields from Query
and Plan nodes that shouldn't have been there in the first place.
Still to do: simplify the execution-time range table; at the moment the
range table passed to the executor still contains Query trees for subqueries.
initdb forced due to change of stored rules.
this code was last gone over, there wasn't really any alternative to
globals because we didn't have the PlannerInfo struct being passed all
through the planner code. Now that we do, we can restructure things
to avoid non-reentrancy. I'm fooling with this because otherwise I'd
have had to add another global variable for the planned compact
range table list.
considered when it is necessary to do so because of a join-order restriction
(that is, an outer-join or IN-subselect construct). The former coding was a
bit ad-hoc and inconsistent, and it missed some cases, as exposed by Mario
Weilguni's recent bug report. His specific problem was that an IN could be
turned into a "clauseless" join due to constant-propagation removing the IN's
joinclause, and if the IN's subselect involved more than one relation and
there was more than one such IN linking to the same upper relation, then the
only valid join orders involve "bushy" plans but we would fail to consider the
specific paths needed to get there. (See the example case added to the join
regression test.) On examining the code I wonder if there weren't some other
problem cases too; in particular it seems that GEQO was defending against a
different set of corner cases than the main planner was. There was also an
efficiency problem, in that when we did realize we needed a clauseless join
because of an IN, we'd consider clauseless joins against every other relation
whether this was sensible or not. It seems a better design is to use the
outer-join and in-clause lists as a backup heuristic, just as the rule of
joining only where there are joinclauses is a heuristic: we'll join two
relations if they have a usable joinclause *or* this might be necessary to
satisfy an outer-join or IN-clause join order restriction. I refactored the
code to have just one place considering this instead of three, and made sure
that it covered all the cases that any of them had been considering.
Backpatch as far as 8.1 (which has only the IN-clause form of the disease).
By rights 8.0 and 7.4 should have the bug too, but they accidentally fail
to fail, because the joininfo structure used in those releases preserves some
memory of there having once been a joinclause between the inner and outer
sides of an IN, and so it leads the code in the right direction anyway.
I'll be conservative and not touch them.
columns procost and prorows, to allow simple user adjustment of the estimated
cost of a function call, as well as control of the estimated number of rows
returned by a set-returning function. We might eventually wish to extend this
to allow function-specific estimation routines, but there seems to be
consensus that we should try a simple constant estimate first. In particular
this provides a relatively simple way to control the order in which different
WHERE clauses are applied in a plan node, which is a Good Thing in view of the
fact that the recent EquivalenceClass planner rewrite made that much less
predictable than before.
representation of equivalence classes of variables. This is an extensive
rewrite, but it brings a number of benefits:
* planner no longer fails in the presence of "incomplete" operator families
that don't offer operators for every possible combination of datatypes.
* avoid generating and then discarding redundant equality clauses.
* remove bogus assumption that derived equalities always use operators
named "=".
* mergejoins can work with a variety of sort orders (e.g., descending) now,
instead of tying each mergejoinable operator to exactly one sort order.
* better recognition of redundant sort columns.
* can make use of equalities appearing underneath an outer join.
which comparison operators to use for plan nodes involving tuple comparison
(Agg, Group, Unique, SetOp). Formerly the executor looked up the default
equality operator for the datatype, which was really pretty shaky, since it's
possible that the data being fed to the node is sorted according to some
nondefault operator class that could have an incompatible idea of equality.
The planner knows what it has sorted by and therefore can provide the right
equality operator to use. Also, this change moves a couple of catalog lookups
out of the executor and into the planner, which should help startup time for
pre-planned queries by some small amount. Modify the planner to remove some
other cavalier assumptions about always being able to use the default
operators. Also add "nulls first/last" info to the Plan node for a mergejoin
--- neither the executor nor the planner can cope yet, but at least the API is
in place.
cases. Operator classes now exist within "operator families". While most
families are equivalent to a single class, related classes can be grouped
into one family to represent the fact that they are semantically compatible.
Cross-type operators are now naturally adjunct parts of a family, without
having to wedge them into a particular opclass as we had done originally.
This commit restructures the catalogs and cleans up enough of the fallout so
that everything still works at least as well as before, but most of the work
needed to actually improve the planner's behavior will come later. Also,
there are not yet CREATE/DROP/ALTER OPERATOR FAMILY commands; the only way
to create a new family right now is to allow CREATE OPERATOR CLASS to make
one by default. I owe some more documentation work, too. But that can all
be done in smaller pieces once this infrastructure is in place.
joinclause doesn't use any outer-side vars) requires a "bushy" plan to be
created. The normal heuristic to avoid joins with no joinclause has to be
overridden in that case. Problem is new in 8.2; before that we forced the
outer join order anyway. Per example from Teodor.
tables in the query compete for cache space, not just the one we are
currently costing an indexscan for. This seems more realistic, and it
definitely will help in examples recently exhibited by Stefan
Kaltenbrunner. To get the total size of all the tables involved, we must
tweak the handling of 'append relations' a bit --- formerly we looked up
information about the child tables on-the-fly during set_append_rel_pathlist,
but it needs to be done before we start doing any cost estimation, so
push it into the add_base_rels_to_query scan.
plpgsql support to come later. Along the way, convert execMain's
SELECT INTO support into a DestReceiver, in order to eliminate some ugly
special cases.
Jonah Harris and Tom Lane
(e.g. "INSERT ... VALUES (...), (...), ...") and elsewhere as allowed
by the spec. (e.g. similar to a FROM clause subselect). initdb required.
Joe Conway and Tom Lane.
(table or index) before trying to open its relcache entry. This fixes
race conditions in which someone else commits a change to the relation's
catalog entries while we are in process of doing relcache load. Problems
of that ilk have been reported sporadically for years, but it was not
really practical to fix until recently --- for instance, the recent
addition of WAL-log support for in-place updates helped.
Along the way, remove pg_am.amconcurrent: all AMs are now expected to support
concurrent update.
effects in a nestloop inner indexscan, I had only dealt with plain index
scans and the index portion of bitmap scans. But there will be cache
benefits for the heap accesses of bitmap scans too, so fix
cost_bitmap_heap_scan() to account for that.
clauses containing no variables and no volatile functions. Such a clause
can be used as a one-time qual in a gating Result plan node, to suppress
plan execution entirely when it is false. Even when the clause is true,
putting it in a gating node wins by avoiding repeated evaluation of the
clause. In previous PG releases, query_planner() would do this for
pseudoconstant clauses appearing at the top level of the jointree, but
there was no ability to generate a gating Result deeper in the plan tree.
To fix it, get rid of the special case in query_planner(), and instead
process pseudoconstant clauses through the normal RestrictInfo qual
distribution mechanism. When a pseudoconstant clause is found attached to
a path node in create_plan(), pull it out and generate a gating Result at
that point. This requires special-casing pseudoconstants in selectivity
estimation and cost_qual_eval, but on the whole it's pretty clean.
It probably even makes the planner a bit faster than before for the normal
case of no pseudoconstants, since removing pull_constant_clauses saves one
useless traversal of the qual tree. Per gripe from Phil Frost.
that the Mackert-Lohmann formula applies across all the repetitions of the
nestloop, not just each scan independently. We use the M-L formula to
estimate the number of pages fetched from the index as well as from the table;
that isn't what it was designed for, but it seems reasonably applicable
anyway. This makes large numbers of repetitions look much cheaper than
before, which accords with many reports we've received of overestimation
of the cost of a nestloop. Also, change the index access cost model to
charge random_page_cost per index leaf page touched, while explicitly
not counting anything for access to metapage or upper tree pages. This
may all need tweaking after we get some field experience, but in simple
tests it seems to be giving saner results than before. The main thing
is to get the infrastructure in place to let cost_index() and amcostestimate
functions take repeated scans into account at all. Per my recent proposal.
Note: this patch changes pg_proc.h, but I did not force initdb because
the changes are basically cosmetic --- the system does not look into
pg_proc to decide how to call an index amcostestimate function, and
there's no way to call such a function from SQL at all.
This shouldn't affect simple indexscans much, while for bitmap scans that
are touching a lot of index rows, this seems to bring the estimates more
in line with reality. Per recent discussion.
assumed that a sequential page fetch has cost 1.0. This patch doesn't
in itself change the system's behavior at all, but it opens the door to
people adopting other units of measurement for EXPLAIN costs. Also, if
we ever decide it's worth inventing per-tablespace access cost settings,
this change provides a workable intellectual framework for that.
relations: fix the executor so that we can have an Append plan on the
inside of a nestloop and still pass down outer index keys to index scans
within the Append, then generate such plans as if they were regular
inner indexscans. This avoids the need to evaluate the outer relation
multiple times.
... in fact, it will be applied now in any query whatsoever. I'm still
a bit concerned about the cycles that might be expended in failed proof
attempts, but given that CE is turned off by default, it's the user's
choice whether to expend those cycles or not. (Possibly we should
change the simple bool constraint_exclusion parameter to something
more fine-grained?)
thereby sharing code with the inheritance case. This puts the UNION-ALL-view
approach to partitioned tables on par with inheritance, so far as constraint
exclusion is concerned: it works either way. (Still need to update the docs
to say so.) The definition of "simple UNION ALL" is a little simpler than
I would like --- basically the union arms can only be SELECT * FROM foo
--- but it's good enough for partitioned-table cases.
inheritance trees on-the-fly, which pretty well constrained us to considering
only one way of planning inheritance, expand inheritance sets during the
planner prep phase, and build a side data structure that can be consulted
later to find which RTEs are members of which inheritance sets. As proof of
concept, use the data structure to plan joins against inheritance sets more
efficiently: we can now use indexes on the set members in inner-indexscan
joins. (The generated plans could be improved further, but it'll take some
executor changes.) This data structure will also support handling UNION ALL
subqueries in the same way as inheritance sets, but that aspect of it isn't
finished yet.
requested sort order. It was assuming that build_index_pathkeys always
generates a pathkey per index column, which was not true if implied equality
deduction had determined that two index columns were effectively equated to
each other. Simplest fix seems to be to install an option that causes
build_index_pathkeys to support this behavior as well as the original one.
Per report from Brian Hirt.
Per my recent proposal. I ended up basing the implementation on the
existing mechanism for enforcing valid join orders of IN joins --- the
rules for valid outer-join orders are somewhat similar.
"ctid IN (list)" will still work after we convert IN to ScalarArrayOpExpr.
Make some minor efficiency improvements while at it, such as ensuring that
multiple TIDs are fetched in physical heap order. And fix EXPLAIN so that
it shows what's really going on for a TID scan.
qualification when the underlying operator is indexable and useOr is true.
That is, indexkey op ANY (ARRAY[...]) is effectively translated into an
OR combination of one indexscan for each array element. This only works
for bitmap index scans, of course, since regular indexscans no longer
support OR'ing of scans. There are still some loose ends to clean up
before changing 'x IN (list)' to translate as a ScalarArrayOpExpr;
for instance predtest.c ought to be taught about it. But this gets the
basic functionality in place.
sense and rename to "outerjoin_delayed" to more clearly reflect what it
means). I had decided that it was redundant in 8.1, but the folly of this
is exposed by a bug report from Sebastian Böck. The place where it's
needed is to prevent orindxpath.c from cherry-picking arms of an outer-join
OR clause to form a relation restriction that isn't actually legal to push
down to the relation scan level. There may be some legal cases that this
forbids optimizing, but we'd need much closer analysis to determine it.
only the inner-side relation would be considered as potential equijoin clauses,
which is wrong because the condition doesn't necessarily hold above the point
of the outer join. Per test case from Kevin Grittner (bug#1916).
so that the latter estimates the number of groups that grouping will
produce. This is needed because it is primarily query_planner that
makes the decision between fast-start and fast-finish plans, and in the
original coding it was unable to make more than a crude rule-of-thumb
choice when the query involved grouping. This revision helps us make
saner choices for queries like SELECT ... GROUP BY ... LIMIT, as in a
recent example from Mark Kirkwood. Also move the responsibility for
canonicalizing sort_pathkeys and group_pathkeys into query_planner;
this information has to be available anyway to support the first change,
and doing it this way lets us get rid of compare_noncanonical_pathkeys
entirely.
or OFFSET clauses by using estimate_expression_value(). The main advantage
of this is that if the expression is a Param and we have a value for the
Param, we'll use that value rather than defaulting. Also, fix some
thinkos in the logic for combining LIMIT/OFFSET with an externally
supplied tuple fraction (this covers cases like EXISTS(...LIMIT...)).
And make sure the results of all this are shown by EXPLAIN. Per a
gripe from Merlin Moncure.
planning logic for bitmap indexscans. Partial indexes create corner
cases in which a scan might be done with no explicit index qual conditions,
and the code wasn't handling those cases nicely. Also be a little
tenser about eliminating redundant clauses in the generated plan.
Per report from Dmitry Karasik.
propagated inside an outer join. In particular, given
LEFT JOIN ON (A = B) WHERE A = constant, we cannot conclude that
B = constant at the top level (B might be null instead), but we
can nonetheless put a restriction B = constant into the quals for
B's relation, since no inner-side rows not meeting that condition
can contribute to the final result. Similarly, given
FULL JOIN USING (J) WHERE J = constant, we can't directly conclude
that either input J variable = constant, but it's OK to push such
quals into each input rel. Per recent gripe from Kim Bisgaard.
Along the way, remove 'valid_everywhere' flag from RestrictInfo,
as on closer analysis it was not being used for anything, and was
defined backwards anyway.
if the limit were directly applied to it. This does not actually
add a LIMIT plan node to the generated subqueries --- that would be
useless overhead --- but it does cause the planner to prefer fast-
start plans when the limit is small. After an idea from Phil Endecott.
of a relation in a flat 'joininfo' list. The former arrangement grouped
the join clauses according to the set of unjoined relids used in each;
however, profiling on test cases involving lots of joins proves that
that data structure is a net loss. It takes more time to group the
join clauses together than is saved by avoiding duplicate tests later.
It doesn't help any that there are usually not more than one or two
clauses per group ...
a new PlannerInfo struct, which is passed around instead of the bare
Query in all the planning code. This commit is essentially just a
code-beautification exercise, but it does open the door to making
larger changes to the planner data structures without having to muck
with the widely-known Query struct.
aren't doing anything useful (ie, neither selection nor projection).
Also, extend to SubqueryScan the hacks already in place to avoid
unnecessary ExecProject calls when the result would just be the same
tuple the subquery already delivered. This saves some overhead in
UNION and other set operations, as well as avoiding overhead for
unflatten-able subqueries. Per example from Sokolov Yura.
node, as this behavior is now better done as a bitmap OR indexscan.
This allows considerable simplification in nodeIndexscan.c itself as
well as several planner modules concerned with indexscan plan generation.
Also we can improve the sharing of code between regular and bitmap
indexscans, since they are now working with nigh-identical Plan nodes.
but the code is basically working. Along the way, rewrite the entire
approach to processing OR index conditions, and make it work in join
cases for the first time ever. orindxpath.c is now basically obsolete,
but I left it in for the time being to allow easy comparison testing
against the old implementation.
logic operations during planning. Seems cleaner to create two new Path
node types, instead --- this avoids duplication of cost-estimation code.
Also, create an enable_bitmapscan GUC parameter to control use of bitmap
plans.
scans, using in-memory tuple ID bitmaps as the intermediary. The planner
frontend (path creation and cost estimation) is not there yet, so none
of this code can be executed. I have tested it using some hacked planner
code that is far too ugly to see the light of day, however. Committing
now so that the bulk of the infrastructure changes go in before the tree
drifts under me.
into indexscans on matching indexes. For the moment, it only handles
int4 and text datatypes; next step is to add a column to pg_aggregate
so that all MIN/MAX aggregates can be handled. Per my recent proposal.
few palloc's. I also chose to eliminate the restype and restypmod fields
entirely, since they are redundant with information stored in the node's
contained expression; re-examining the expression at need seems simpler
and more reliable than trying to keep restype/restypmod up to date.
initdb forced due to change in contents of stored rules.
really ought to run before canonicalize_qual, because it can now produce
forms that canonicalize_qual knows how to improve (eg, NOT clauses).
Also, because eval_const_expressions already knows about flattening
nested ANDs and ORs into N-argument form, the initial flatten_andors
pass in canonicalize_qual is now completely redundant and can be
removed. This doesn't save a whole lot of code, but the time and
palloc traffic eliminated is a useful gain on large expression trees.
structs. There are many places in the planner where we were passing
both a rel and an index to subroutines, and now need only pass the
index struct. Notationally simpler, and perhaps a tad faster.
for boolean indexes. Previously we would only use such an index with
WHERE clauses like 'indexkey = true' or 'indexkey = false'. The new
code transforms the cases 'indexkey', 'NOT indexkey', 'indexkey IS TRUE',
and 'indexkey IS FALSE' into one of these. While this is only marginally
useful in itself, I intend soon to change constant-expression simplification
so that 'foo = true' and 'foo = false' are reduced to just 'foo' and
'NOT foo' ... which would lose the ability to use boolean indexes for
such queries at all, if the indexscan machinery couldn't make the
reverse transformation.
grouping_planner() to preprocess_targetlist(), according to a comment
in grouping_planner(). I think the refactoring makes sense, and moves
some extraneous details out of grouping_planner().
Formerly, if such a clause contained no aggregate functions we mistakenly
treated it as equivalent to WHERE. Per spec it must cause the query to
be treated as a grouped query of a single group, the same as appearance
of aggregate functions would do. Also, the HAVING filter must execute
after aggregate function computation even if it itself contains no
aggregate functions.
look at the actual aggregate transition datatypes and the actual overhead
needed by nodeAgg.c, instead of using pessimistic round numbers.
Per a discussion with Michael Tiemann.
Also performed an initial run through of upgrading our Copyright date to
extend to 2005 ... first run here was very simple ... change everything
where: grep 1996-2004 && the word 'Copyright' ... scanned through the
generated list with 'less' first, and after, to make sure that I only
picked up the right entries ...
at the top level of the column's old default expression before adding
an implicit coercion to the new column type. This seems to satisfy the
principle of least surprise, as per discussion of bug #1290.
for scanning one term of an OR clause if the index's predicate is implied
by that same OR clause term (possibly in conjunction with top-level WHERE
clauses). Per recent example from Dawid Kuroczko,
http://archives.postgresql.org/pgsql-performance/2004-10/msg00095.php
Also, fix a very long-standing bug in index predicate testing, namely the
bizarre ordering of decomposition of predicate and restriction clauses.
AFAICS the correct way is to break down the predicate all the way, and
then for each component term see if you can prove it from the entire
restriction set. The original coding had a purely-implementation-artifact
distinction between ANDing at the top level and ANDing below that, and
proceeded to get the decomposition order wrong everywhere below the top
level, with the result that even slightly complicated AND/OR predicates
could not be proven. For instance, given
create index foop on foo(f2) where f1=42 or f1=1
or (f1 = 11 and f2 = 55);
the old code would fail to match this index to the query
select * from foo where f1 = 11 and f2 = 55;
when it obviously ought to match.
from Sebastian Böck. The fix involves being more consistent about
when rangetable entries are copied or modified. Someday we really
need to fix this stuff to not scribble on its input data structures
in the first place...
until Bind is received, so that actual parameter values are visible to the
planner. Make use of the parameter values for estimation purposes (but
don't fold them into the actual plan). This buys back most of the
potential loss of plan quality that ensues from using out-of-line
parameters instead of putting literal values right into the query text.
This patch creates a notion of constant-folding expressions 'for
estimation purposes only', in which case we can be more aggressive than
the normal eval_const_expressions() logic can be. Right now the only
difference in behavior is inserting bound values for Params, but it will
be interesting to look at other possibilities. One that we've seen
come up repeatedly is reducing now() and related functions to current
values, so that queries like ... WHERE timestampcol > now() - '1 day'
have some chance of being planned effectively.
Oliver Jowett, with some kibitzing from Tom Lane.
rather than allowing them only in a few special cases as before. In
particular you can now pass a ROW() construct to a function that accepts
a rowtype parameter. Internal generation of RowExprs fixes a number of
corner cases that used to not work very well, such as referencing the
whole-row result of a JOIN or subquery. This represents a further step in
the work I started a month or so back to make rowtype values into
first-class citizens.
by the set operation, so that redundant sorts at higher levels can be
avoided. This was foreseen a good while back, but not done. Per request
from Karel Zak.
corner cases that could stand improvement, but it does all the basic
stuff. A byproduct is that the selectivity routines are no longer
constrained to working on simple Vars; we might in future be able to
improve the behavior for subexpressions that don't match indexes.
that it's good to join where there are join clauses rather than where there
are not. Also enable it to generate bushy plans at need, so that it doesn't
fail in the presence of multiple IN clauses containing sub-joins. These
changes appear to improve the behavior enough that we can substantially reduce
the default pool size and generations count, thereby decreasing the runtime,
and yet get as good or better plans as we were getting in 7.4. Consequently,
adjust the default GEQO parameters. I also modified the way geqo_effort is
used so that it affects both population size and number of generations;
it's now useful as a single control to adjust the GEQO runtime-vs-plan-quality
tradeoff. Bump geqo_threshold to 12, since even with these changes GEQO
seems to be slower than the regular planner at 11 relations.
default value for geqo_effort is supposed to be 40, not 1. The actual
'genetic' component of the GEQO algorithm has been practically disabled
since 7.1 because of this mistake. Improve documentation while at it.
check instead of hardwiring assumptions that only certain plan node types
can appear at the places where we are testing. This was always a pretty
fragile assumption, and it turns out to be broken in 7.4 for certain cases
involving IN-subselect tests that need type coercion.
Also, modify code that builds finished Plan tree so that node types that
don't do projection always copy their input node's targetlist, rather than
having the tlist passed in from the caller. The old method makes it too
easy to write broken code that thinks it can modify the tlist when it
cannot.
with index qual clauses in the Path representation. This saves a little
work during createplan and (probably more importantly) allows reuse of
cached selectivity estimates during indexscan planning. Also fix latent
bug: wrong plan would have been generated for a 'special operator' used
in a nestloop-inner-indexscan join qual, because the special operator
would not have gotten into the list of quals to recheck. This bug is
only latent because at present the special-operator code could never
trigger on a join qual, but sooner or later someone will want to do it.
join conditions in which each OR subclause includes a constraint on
the same relation. This implements the other useful side-effect of
conversion to CNF format, without its unpleasant side-effects. As
per pghackers discussion of a few weeks ago.
teaching the latter to accept either RestrictInfo nodes or bare
clause expressions; and cache the selectivity result in the RestrictInfo
node when possible. This extends the caching behavior of approx_selectivity
to many more contexts, and should reduce duplicate selectivity
calculations.
first time generate an OR indexscan for a two-column index when the WHERE
condition is like 'col1 = foo AND (col2 = bar OR col2 = baz)' --- before,
the OR had to be on the first column of the index or we'd not notice the
possibility of using it. Some progress towards extracting OR indexscans
from subclauses of an OR that references multiple relations, too, although
this code is #ifdef'd out because it needs more work.
fields: now they are valid whenever the clause is a binary opclause,
not only when it is a potential join clause (there is a new boolean
field canjoin to signal the latter condition). This lets us avoid
recomputing the relid sets over and over while examining indexes.
Still more work to do to make this as useful as it could be, because
there are places that could use the info but don't have access to the
RestrictInfo node.
about whether it is applied before or after eval_const_expressions().
I believe there were some corner cases where the system would fail to
recognize that a partial index is applicable because of the previous
inconsistency. Store normal rather than 'implicit AND' representations
of constraints and index predicates in the catalogs.
initdb forced due to representation change of constraints/predicates.
sequence every time it's called is bogus --- it interferes with user
control over the seed, and actually decreases randomness overall
(because a seed based on time(NULL) is pretty predictable). If you really
want a reproducible result from geqo, do 'set seed = 0' before planning
a query.
node emits only those vars that are actually needed above it in the
plan tree. (There were comments in the code suggesting that this was
done at some point in the dim past, but for a long time we have just
made join nodes emit everything that either input emitted.) Aside from
being marginally more efficient, this fixes the problem noted by Peter
Eisentraut where a join above an IN-implemented-as-join might fail,
because the subplan targetlist constructed in the latter case didn't
meet the expectation of including everything.
Along the way, fix some places that were O(N^2) in the targetlist
length. This is not all the trouble spots for wide queries by any
means, but it's a step forward.
'scalar op ALL (array)', where the operator is applied between the
lefthand scalar and each element of the array. The operator must
yield boolean; the result of the construct is the OR or AND of the
per-element results, respectively.
Original coding by Joe Conway, after an idea of Peter's. Rewritten
by Tom to keep the implementation strictly separate from subqueries.
some cases of redundant clauses that were formerly not caught. We have
to special-case this because the clauses involved never get attached to
the same join restrictlist and so the existing logic does not notice
that they are redundant.
extensions to support our historical behavior. An aggregate belongs
to the closest query level of any of the variables in its argument,
or the current query level if there are no variables (e.g., COUNT(*)).
The implementation involves adding an agglevelsup field to Aggref,
and treating outer aggregates like outer variables at planning time.
of an index can now be a computed expression instead of a simple variable.
Restrictions on expressions are the same as for predicates (only immutable
functions, no sub-selects). This fixes problems recently introduced with
inlining SQL functions, because the inlining transformation is applied to
both expression trees so the planner can still match them up. Along the
way, improve efficiency of handling index predicates (both predicates and
index expressions are now cached by the relcache) and fix 7.3 oversight
that didn't record dependencies of predicate expressions.
blanks, in hopes of reducing the surprise factor for newbies. Remove
redundant operators for VARCHAR (it depends wholly on TEXT operations now).
Clean up resolution of ambiguous operators/functions to avoid surprising
choices for domains: domains are treated as equivalent to their base types
and binary-coercibility is no longer considered a preference item when
choosing among multiple operators/functions. IsBinaryCoercible now correctly
reflects the notion that you need *only* relabel the type to get from type
A to type B: that is, a domain is binary-coercible to its base type, but
not vice versa. Various marginal cleanup, including merging the essentially
duplicate resolution code in parse_func.c and parse_oper.c. Improve opr_sanity
regression test to understand about binary compatibility (using pg_cast),
and fix a couple of small errors in the catalogs revealed thereby.
Restructure "special operator" handling to fetch operators via index opclasses
rather than hardwiring assumptions about names (cleans up the pattern_ops
stuff a little).
the column by table OID and column number, if it's a simple column
reference. Along the way, get rid of reskey/reskeyop fields in Resdoms.
Turns out that representation was not convenient for either the planner
or the executor; we can make the planner deliver exactly what the
executor wants with no more effort.
initdb forced due to change in stored rule representation.
into a UNION that has some type coercions applied to the component
queries, so long as the qual itself does not reference any columns that
have such coercions. Per example from Jonathan Bartlett 24-Apr-03.
utility statement (DeclareCursorStmt) with a SELECT query dangling from
it, rather than a SELECT query with a few unusual fields in it. Add
code to determine whether a planned query can safely be run backwards.
If DECLARE CURSOR specifies SCROLL, ensure that the plan can be run
backwards by adding a Materialize plan node if it can't. Without SCROLL,
you get an error if you try to fetch backwards from a cursor that can't
handle it. (There is still some discussion about what the exact
behavior should be, but this is necessary infrastructure in any case.)
Along the way, make EXPLAIN DECLARE CURSOR work.
the outer query. (The implementation is a bit klugy, but it would take
nontrivial restructuring to make it nicer, which this is probably not
worth.) This avoids unnecessary sort steps in examples like
SELECT foo,count(*) FROM (SELECT ... ORDER BY foo,bar) sub GROUP BY foo
which means there is now a reasonable technique for controlling the
order of inputs to custom aggregates, even in the grouping case.
locParam lists can be converted to bitmapsets to speed updating. Also,
replace 'locParam' with 'allParam', which contains all the paramIDs
relevant to the node (i.e., the union of extParam and locParam); this
saves a step during SetChangedParamList() without costing anything
elsewhere.
nodes where it's not really necessary. In many cases where the scan node
is not the topmost plan node (eg, joins, aggregation), it's possible to
just return the table tuple directly instead of generating an intermediate
projection tuple. In preliminary testing, this reduced the CPU time
needed for 'SELECT COUNT(*) FROM foo' by about 10%.
passed to join selectivity estimators. Make use of this in eqjoinsel
to derive non-bogus selectivity for IN clauses. Further tweaking of
cost estimation for IN.
initdb forced because of pg_proc.h changes.
Try to model the effect of rescanning input tuples in mergejoins;
account for JOIN_IN short-circuiting where appropriate. Also, recognize
that mergejoin and hashjoin clauses may now be more than single operator
calls, so we have to charge appropriate execution costs.
necessarily following the JOIN syntax to develop the query plan. The old
behavior is still available by setting GUC variable JOIN_COLLAPSE_LIMIT
to 1. Also create a GUC variable FROM_COLLAPSE_LIMIT to control the
similar decision about when to collapse sub-SELECT lists into their parent
lists. (This behavior existed already, but the limit was always
GEQO_THRESHOLD/2; now it's separately adjustable.)
of known-equal expressions includes any constant expressions (including
Params from outer queries), we actively suppress any 'var = var'
clauses that are or could be deduced from the set, generating only the
deducible 'var = const' clauses instead. The idea here is to push down
the restrictions implied by the equality set to base relations whenever
possible. Once we have applied the 'var = const' clauses, the 'var = var'
clauses are redundant, and should be suppressed both to save work at
execution and to avoid double-counting restrictivity.
There are two implementation techniques: the executor understands a new
JOIN_IN jointype, which emits at most one matching row per left-hand row,
or the result of the IN's sub-select can be fed through a DISTINCT filter
and then joined as an ordinary relation.
Along the way, some minor code cleanup in the optimizer; notably, break
out most of the jointree-rearrangement preprocessing in planner.c and
put it in a new file prep/prepjointree.c.
that used to do it in planner. That was an ancient kluge that was
never satisfactory; errors should be detected at parse time when possible.
But at the time we didn't have the support mechanism (expression_tree_walker
et al) to make it convenient to do in the parser.
simplify callers. It turns out the common case is that the caller
does want to recurse into sub-queries, so push support for that into
these subroutines.
join_references(), it's practical to consolidate all join_references()
processing into the set_plan_references traversal in setrefs.c. This
seems considerably cleaner than the old way where we did it for join
quals in createplan.c and for targetlists in setrefs.c.
containing a volatile function), rather than only on 'Var = Var' clauses
as before. This makes it practical to do flatten_join_alias_vars at the
start of planning, which in turn eliminates a bunch of klugery inside the
planner to deal with alias vars. As a free side effect, we now detect
implied equality of non-Var expressions; for example in
SELECT ... WHERE a.x = b.y and b.y = 42
we will deduce a.x = 42 and use that as a restriction qual on a. Also,
we can remove the restriction introduced 12/5/02 to prevent pullup of
subqueries whose targetlists contain sublinks.
Still TODO: make statistical estimation routines in selfuncs.c and costsize.c
smarter about expressions that are more complex than plain Vars. The need
for this is considerably greater now that we have to be able to estimate
the suitability of merge and hash join techniques on such expressions.
a qualification clause (and hence can get away with being sloppy about
distinguishing FALSE from UNKNOWN). We need to know this in subselect.c;
marking the subplans in setrefs.c is too late.
costs for expression evaluation, not only per-tuple cost as before.
This extension is needed in order to deal realistically with hashed or
materialized sub-selects.
allocation in best_inner_indexscan(). While at it, simplify GEQO's
interface to the main planner --- make_join_rel() offers exactly the
API it really wants, whereas calling make_rels_by_clause_joins() and
make_rels_by_clauseless_joins() required jumping through hoops.
Rewrite gimme_tree for clarity (sometimes iteration is much better than
recursion), and approximately halve GEQO's runtime by recognizing that
tours of the forms (a,b,c,d,...) and (b,a,c,d,...) are equivalent
because of symmetry in make_join_rel().
in the planned representation of a subplan at all any more, only SubPlan.
This means subselect.c doesn't scribble on its input anymore, which seems
like a good thing; and there are no longer three different possible
interpretations of a SubLink. Simplify node naming and improve comments
in primnodes.h. No change to stored rules, though.
make VALUE a non-reserved word again, use less invasive method of passing
ConstraintTestValue into transformExpr, fix problems with nested constraint
testing, do correct thing with NULL result from a constraint expression,
remove memory leak. Domain checks still need much more work if we are going
to allow ALTER DOMAIN, however.
so that all executable expression nodes inherit from a common supertype
Expr. This is somewhat of an exercise in code purity rather than any
real functional advance, but getting rid of the extra Oper or Func node
formerly used in each operator or function call should provide at least
a little space and speed improvement.
initdb forced by changes in stored-rules representation.
('SELECT expression') inline, like macros, during the constant-folding
phase of planning. The actual expansion is not difficult, but checking
that we're not changing the semantics of the call turns out to be more
subtle than one might think; in particular must pay attention to
permissions issues, strictness, and volatility.
joinclauses is determined accurately for each join. Formerly, the code only
considered joinclauses that used all of the rels from the outer side of the
join; thus for example
FROM (a CROSS JOIN b) JOIN c ON (c.f1 = a.x AND c.f2 = b.y)
could not exploit a two-column index on c(f1,f2), since neither of the
qual clauses would be in the joininfo list it looked in. The new code does
this correctly, and also is able to eliminate redundant clauses, thus fixing
the problem noted 24-Oct-02 by Hans-Jürgen Schönig.
parameter to allow it to be forced off for comparison purposes.
Add ORDER BY clauses to a bunch of regression test queries that will
otherwise produce randomly-ordered output in the new regime.
of groups produced by GROUP BY. This improves the accuracy of planning
estimates for grouped subselects, and is needed to check whether a
hashed aggregation plan risks memory overflow.
node now does its own grouping of the input rows, and has no need for a
preceding GROUP node in the plan pipeline. This allows elimination of
the misnamed tuplePerGroup option for GROUP, and actually saves more code
in nodeGroup.c than it costs in nodeAgg.c, as well as being presumably
faster. Restructure the API of query_planner so that we do not commit to
using a sorted or unsorted plan in query_planner; instead grouping_planner
makes the decision. (Right now it isn't any smarter than query_planner
was, but that will change as soon as it has the option to select a hash-
based aggregation step.) Despite all the hackery, no initdb needed since
only in-memory node types changed.
that are explicitly JOINed are not considered dependencies unless they
are actually used in the query: mere presence in the joinaliasvars
list of a JOIN RTE doesn't count as being used. The patch touches
a number of files because I needed to generalize the API of
query_tree_walker to support an additional flag bit, but the changes
are otherwise quite small.
pg_language.lancompiler
pg_operator.oprprec
pg_operator.oprisleft
pg_proc.proimplicit
pg_proc.probyte_pct
pg_proc.properbyte_cpu
pg_proc.propercall_cpu
pg_proc.prooutin_ratio
pg_shadow.usetrace
pg_type.typprtlen
pg_type.typreceive
pg_type.typsend
Attempts to use the obsoleted attributes of pg_operator or pg_proc
in the CREATE commands will be greeted by a warning. For pg_type,
there is no warning (yet) because pg_dump scripts still contain these
attributes.
Also remove new but already obsolete spellings
isVolatile, isStable, isImmutable in WITH clause. (Use new syntax
instead.)
PX recombination operator, changes some elog() messages from LOG
to DEBUG1, puts some debugging functions inside the appropriate
#ifdef (not enabled by default), and makes a few other minor
cleanups.
BTW, the elog() change is motivated by at least one user who
has sent a concerned email to -general asking exactly what the
"ERX recombination operator" is, and what it is doing to their
DBMS.
Neil Conway
process function RTE expressions, which they were previously missing.
This allows outer-Var references and subselects to work correctly in
the arguments of a function RTE. Install check to prevent function RTEs
from cross-referencing Vars of sibling FROM-items, which doesn't make
any sense (if you want to join, write a JOIN or WHERE clause).
rather than a Query node; this allows set_plan_references to recurse
into subplans correctly. Fixes core dump on full outer joins in
subplans. Also, invoke preprocess_expression on function RTEs'
function expressions. This seems to fix the planner's problems with
outer-level Vars in function RTEs.
returns-set boolean field in Func and Oper nodes. This allows cleaner,
more reliable tests for expressions returning sets in the planner and
parser. For example, a WHERE clause returning a set is now detected
and complained of in the parser, not only at runtime.
some kibitzing from Tom Lane. Not everything works yet, and there's
no documentation or regression test, but let's commit this so Joe
doesn't need to cope with tracking changes in so many files ...
lists to join RTEs, attach a list of Vars and COALESCE expressions that will
replace the join's alias variables during planning. This simplifies
flatten_join_alias_vars while still making it easy to fix up varno references
when transforming the query tree. Add regression test cases for interactions
of subqueries with outer joins.
volatile), rather than the old cachable/noncachable distinction. This
allows indexscan optimizations in many places where we formerly didn't.
Also, add a pronamespace column to pg_proc (it doesn't do anything yet,
however).
now has an RTE of its own, and references to its outputs now are Vars
referencing the JOIN RTE, rather than CASE-expressions. This allows
reverse-listing in ruleutils.c to use the correct alias easily, rather
than painfully reverse-engineering the alias namespace as it used to do.
Also, nested FULL JOINs work correctly, because the result of the inner
joins are simple Vars that the planner can cope with. This fixes a bug
reported a couple times now, notably by Tatsuo on 18-Nov-01. The alias
Vars are expanded into COALESCE expressions where needed at the very end
of planning, rather than during parsing.
Also, beginnings of support for showing plan qualifier expressions in
EXPLAIN. There are probably still cases that need work.
initdb forced due to change of stored-rule representation.
set-returning functions in its target list. This ensures that we
won't rewrite the query in a way that places set-returning functions
into quals (WHERE clauses). Cf. bug reports from Joe Conway.
Tom Lane
Bruce Momjian
Robert Haas
Peter Eisentraut
Magnus Hagander
Alvaro Herrera
Joe Conway
Neil Conway
PostgreSQL Daemon