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.
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 commit provides the core code and documentation needed. A contrib
module test case will follow shortly.
Shigeru Hanada, Jan Urbanski, Heikki Linnakangas
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.
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.
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.
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.
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.
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.
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
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.
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.
(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.
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.
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.
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.
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.
(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.
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.
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.
"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.
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.
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.
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.
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 ...
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.
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.
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.
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.
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.)
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 ...
of costsize.c routines to pass Query root, so that costsize can figure
more things out by itself and not be so dependent on its callers to tell
it everything it needs to know. Use selectivity of hash or merge clause
to estimate number of tuples processed internally in these joins
(this is more useful than it would've been before, since eqjoinsel is
somewhat more accurate than before).
a separate statement (though it can still be invoked as part of VACUUM, too).
pg_statistic redesigned to be more flexible about what statistics are
stored. ANALYZE now collects a list of several of the most common values,
not just one, plus a histogram (not just the min and max values). Random
sampling is used to make the process reasonably fast even on very large
tables. The number of values and histogram bins collected is now
user-settable via an ALTER TABLE command.
There is more still to do; the new stats are not being used everywhere
they could be in the planner. But the remaining changes for this project
should be localized, and the behavior is already better than before.
A not-very-related change is that sorting now makes use of btree comparison
routines if it can find one, rather than invoking '<' twice.
That means you can now set your options in either or all of $PGDATA/configuration,
some postmaster option (--enable-fsync=off), or set a SET command. The list of
options is in backend/utils/misc/guc.c, documentation will be written post haste.
pg_options is gone, so is that pq_geqo config file. Also removed were backend -K,
-Q, and -T options (no longer applicable, although -d0 does the same as -Q).
Added to configure an --enable-syslog option.
changed all callers from TPRINTF to elog(DEBUG)
costs using the inner path's parent->rows count as the number of tuples
processed per inner scan iteration. This is wrong when we are using an
inner indexscan with indexquals based on join clauses, because the rows
count in a Relation node reflects the selectivity of the restriction
clauses for that rel only. Upshot was that if join clause was very
selective, we'd drastically overestimate the true cost of the join.
Fix is to calculate correct output-rows estimate for an inner indexscan
when the IndexPath node is created and save it in the path node.
Change of path node doesn't require initdb, since path nodes don't
appear in saved rules.
accesses versus sequential accesses, a (very crude) estimate of the
effects of caching on random page accesses, and cost to evaluate WHERE-
clause expressions. Export critical parameters for this model as SET
variables. Also, create SET variables for the planner's enable flags
(enable_seqscan, enable_indexscan, etc) so that these can be controlled
more conveniently than via PGOPTIONS.
Planner now estimates both startup cost (cost before retrieving
first tuple) and total cost of each path, so it can optimize queries
with LIMIT on a reasonable basis by interpolating between these costs.
Same facility is a win for EXISTS(...) subqueries and some other cases.
Redesign pathkey representation to achieve a major speedup in planning
(I saw as much as 5X on a 10-way join); also minor changes in planner
to reduce memory consumption by recycling discarded Path nodes and
not constructing unnecessary lists.
Minor cleanups to display more-plausible costs in some cases in
EXPLAIN output.
Initdb forced by change in interface to index cost estimation
functions.
fields in JoinPaths --- turns out that we do need that after all :-(.
Also, rearrange planner so that only one RelOptInfo is created for a
particular set of joined base relations, no matter how many different
subsets of relations it can be created from. This saves memory and
processing time compared to the old method of making a bunch of RelOptInfos
and then removing the duplicates. Clean up the jointree iteration logic;
not sure if it's better, but I sure find it more readable and plausible
now, particularly for the case of 'bushy plans'.
pghackers discussion of 5-Jan-2000. The amopselect and amopnpages
estimators are gone, and in their place is a per-AM amcostestimate
procedure (linked to from pg_am, not pg_amop).
hashjoinable clause, not one path for a randomly-chosen element of each
set of clauses with the same join operator. That is, if you wrote
SELECT ... WHERE t1.f1 = t2.f2 and t1.f3 = t2.f4,
and both '=' ops were the same opcode (say, all four fields are int4),
then the system would either consider hashing on f1=f2 or on f3=f4,
but it would *not* consider both possibilities. Boo hiss.
Also, revise estimation of hashjoin costs to include a penalty when the
inner join var has a high disbursion --- ie, the most common value is
pretty common. This tends to lead to badly skewed hash bucket occupancy
and way more comparisons than you'd expect on average.
I imagine that the cost calculation still needs tweaking, but at least
it generates a more reasonable plan than before on George Young's example.
identified by Hiroshi (incorrect cost attributed to OR clauses
after multiple passes through set_rest_selec()). I think the code
was trying to allow selectivities of OR subclauses to be passed in
from outside, but noplace was actually passing any useful data, and
set_rest_selec() was passing wrong data.
Restructure representation of "indexqual" in IndexPath nodes so that
it is the same as for indxqual in completed IndexScan nodes: namely,
a toplevel list with an entry for each pass of the index scan, having
sublists that are implicitly-ANDed index qual conditions for that pass.
You don't want to know what the old representation was :-(
Improve documentation of OR-clause indexscan functions.
Remove useless 'notclause' field from RestrictInfo nodes. (This might
force an initdb for anyone who has stored rules containing RestrictInfos,
but I do not think that RestrictInfo ever appears in completed plans.)
