make_restrictinfo_from_bitmapqual. The likelihood of finding duplicates
seems much less than in the AND-subclause case, and the cost much higher,
because OR lists with hundreds or even thousands of subclauses are not
uncommon. Per discussion with Ilia Kantor and andrew@supernews.
A RestrictInfo representing an OR clause now contains two versions of
the contained expression, one with sub-RestrictInfos and one without.
clause_selectivity() should descend to the version with sub-RestrictInfos
so that it has a chance of caching its results for the OR's sub-clauses.
Failing to do so resulted in redundant planner effort.
predicate_implied_by() to detect redundant filter conditions, but forgot
that predicate_implied_by() assumes its first argument contains only
immutable functions. Add a check to guarantee that. Also, test to see
if filter conditions can be discarded because they are redundant with
the predicate of a partial index.
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).
"optimization". When we find a potentially useful joinclause, we
have to add all its other required_relids to the result, not only the
other clause_relids. They are different in the case of a joinclause
whose applicability has to be postponed due to outer join. We have
to include the extra rels because otherwise, after best_inner_indexscan
masks the join rels with index_outer_relids, it will always fail to
find the joinclause as applicable. Per report from Husam Tomeh.
when there are extra resjunk columns in the child node. I found some
additional cases involving Append nodes that weren't handled by the
prior patch, and it's not clear how to fix them in the same way without
breaking inheritance cases. So the prudent path seems to be to narrow
the scope of the optimization.
has to recopy the input plan node's targetlist if it removes a
SubqueryScan node just below the non-projecting node. For simplicity
I made it recopy always. Per bug report from Allan Wang and Michael Fuhr.
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.
to copy the whole plan tree before invoking adjust_plan_varnos(); else
if there is any multiply-linked substructure, the latter might increment
some Var's varno twice. Previously there were some retail copyObject
calls inside adjust_plan_varnos, but it seems a lot safer to just dup the
whole tree first. Also, set_inner_join_references was trying to avoid
work by not recursing if a BitmapHeapScan's bitmapqualorig contained no
outer references; which was OK at the time the code was written, I think,
but now that create_bitmap_scan_plan removes duplicate clauses from
bitmapqualorig it is possible for that field to be NULL while outer
references still remain in the qpqual and/or contained indexscan nodes.
For safety, always recurse even if the BitmapHeapScan looks to be outer
reference free. Per reports from Michael Fuhr and Oleg Bartunov.
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.
continue to recurse after eliminating a NOT-below-a-NOT, since the
contained subexpression will now be part of the top-level AND/OR structure
and so deserves to be simplified. The real-world impact of this is
probably minimal, since it'd require at least three levels of NOT to make
a difference, but it's still a bug.
Also remove some redundant tests for NULL subexpressions.
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.
coding would ignore startup cost differences of less than 1% of the
estimated total cost; which was OK for normal planning but highly not OK
if a very small LIMIT was applied afterwards, so that startup cost becomes
the name of the game. Instead, compare startup and total costs fuzzily
but independently. This changes the plan selected for two queries in the
regression tests; adjust expected-output files for resulting changes in
row order. Per reports from Dawid Kuroczko and Sam Mason.
output targetlist of the Unique or HashAgg plan. This code was OK when
written, but subsequent changes to use "physical tlists" where possible
had broken it: given an input subplan that has extra variables added to
avoid a projection step, it would copy those extra variables into the
upper tlist, which is pointless since a projection has to happen anyway.
cases: we can't just consider whether the subquery's output is unique on its
own terms, we have to check whether the set of output columns we are going to
use will be unique. Per complaint from Luca Pireddu and test case from
Michael Fuhr.
able to do this before, but I had tried to make an exception for functions
with OUT parameters. Michael Fuhr found one problem with it already, and
I found another, which was it didn't work for strict functions with a
NULL input. While both of these could be worked around, the probability
that there are more gotchas seems high; I think prudence dictates just
reverting to the former behavior for now. Accordingly, remove the kluge
added to get_expr_result_type() for Michael's case.
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 geqo_rand() returns exactly 1.0, resulting in failure due to indexing
off the end of the pool array. Also, since this is using inexact float math,
it seems wise to guard against roundoff error producing values slightly
outside the expected range. Per report from bug@zedware.org.
constraint while determining whether the index sort order matches the
query's ORDER BY. This for example allows an index on (x,y) to match
... WHERE x = 42 ORDER BY y;
It only works for btree indexes, but since those are the only ones we
currently have that are ordered at all, that's good enough for now.
Per popular demand.
nonconsecutive columns of a multicolumn index, as per discussion around
mid-May (pghackers thread "Best way to scan on-disk bitmaps"). This
turns out to require only minimal changes in btree, and so far as I can
see none at all in GiST. btcostestimate did need some work, but its
original assumption that index selectivity == heap selectivity was
quite bogus even before this.
to a subquery if the outer query is simple enough that the LIMIT can
be reflected directly to the subquery. This didn't use to be very
interesting, because a subquery that couldn't have been flattened into
the upper query was usually not going to be very responsive to
tuple_fraction anyway. But with new code that allows UNION ALL subqueries
to pay attention to tuple_fraction, this is useful to do. In particular
this lets the optimization occur when the UNION ALL is directly inside
a view.
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 ...
other_rel_list with a single array indexed by rangetable index.
This reduces find_base_rel from O(N) to O(1) without any real penalty.
While find_base_rel isn't one of the major bottlenecks in any profile
I've seen so far, it was starting to creep up on the radar screen
for complex queries --- so might as well fix it.
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.
RTE of interest, rather than the whole rangetable list. This makes
the API more understandable and avoids duplicate RTE lookups. This
patch reverts no-longer-needed portions of my patch of 2004-08-19.
performance problem pointed out by phil@vodafone: to wit, we were
spending O(N^2) time to check dropped-ness in an N-deep join tree,
even in the case where the tree was freshly constructed and couldn't
possibly mention any dropped columns. Instead of recursing in
get_rte_attribute_is_dropped(), change the data structure definition:
the joinaliasvars list of a JOIN RTE must have a NULL Const instead
of a Var at any position that references a now-dropped column. This
costs nothing during normal parse-rewrite-plan path, and instead we
have a linear-time update to make when loading a stored rule that
might contain now-dropped columns. While at it, move the responsibility
for acquring locks on relations referenced by rules into this separate
function (which I therefore chose to call AcquireRewriteLocks).
This saves effort --- namely, duplicated lock grabs in parser and rewriter
--- in the normal path at a cost of one extra non-locked heap_open()
in the stored-rule path; seems a good tradeoff. A fringe benefit is
that it is now *much* clearer that we acquire lock on relations referenced
in rules before we make any rewriter decisions based on their properties.
(I don't know of any bug of that ilk, but it wasn't exactly clear before.)
would be evaluated only once anyway (ie, it's just a SELECT with no
FROM or an INSERT ... VALUES). The planner can't do it any faster than
the executor, so no point in an extra copying of the expression tree.
where there was also a WHERE-clause restriction that applied to the
join. The check on restrictlist == NIL is really unnecessary anyway,
because select_mergejoin_clauses already checked for and complained
about any unmergejoinable join clauses. So just take it out.
that we acquire a lock on relations added to the query due to inheritance.
Formerly, no such lock was held throughout planning, which meant that
a schema change could occur to invalidate the plan before it's even
been completed.
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.
