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.