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.
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.
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.
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.
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 ...
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.
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).
create_index_paths are not immediately discarded, but are available for
subsequent planner work. This allows avoiding redundant syscache lookups
in several places. Change interface to operator selectivity estimation
procedures to allow faster and more flexible estimation.
Initdb forced due to change of pg_proc entries for selectivity functions!
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.
comparison does not consider paths different when they differ only in
uninteresting aspects of sort order. (We had a special case of this
consideration for indexscans already, but generalize it to apply to
ordered join paths too.) Be stricter about what is a canonical pathkey
to allow faster pathkey comparison. Cache canonical pathkeys and
dispersion stats for left and right sides of a RestrictInfo's clause,
to avoid repeated computation. Total speedup will depend on number of
tables in a query, but I see about 4x speedup of planning phase for
a sample seven-table query.
joins, and clean things up a good deal at the same time. Append plan node
no longer hacks on rangetable at runtime --- instead, all child tables are
given their own RT entries during planning. Concept of multiple target
tables pushed up into execMain, replacing bug-prone implementation within
nodeAppend. Planner now supports generating Append plans for inheritance
sets either at the top of the plan (the old way) or at the bottom. Expanding
at the bottom is appropriate for tables used as sources, since they may
appear inside an outer join; but we must still expand at the top when the
target of an UPDATE or DELETE is an inheritance set, because we actually need
a different targetlist and junkfilter for each target table in that case.
Fortunately a target table can't be inside an outer join... Bizarre mutual
recursion between union_planner and prepunion.c is gone --- in fact,
union_planner doesn't really have much to do with union queries anymore,
so I renamed it grouping_planner.
(Don't forget that an alias is required.) Views reimplemented as expanding
to subselect-in-FROM. Grouping, aggregates, DISTINCT in views actually
work now (he says optimistically). No UNION support in subselects/views
yet, but I have some ideas about that. Rule-related permissions checking
moved out of rewriter and into executor.
INITDB REQUIRED!
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'.
store all ordering information in pathkeys lists (which are now lists of
lists of PathKeyItem nodes, not just lists of lists of vars). This was
a big win --- the code is smaller and IMHO more understandable than it
was, even though it handles more cases. I believe the node changes will
not force an initdb for anyone; planner nodes don't show up in stored
rules.
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.
Bruce Momjian