is treated like end-of-input, if nulls sort last in that column and we are not
doing outer-join filling for that input. In such a case, the tuple cannot
join to anything from the other input (because we assume mergejoinable
operators are strict), and neither can any tuple following it in the sort
order. If we're not interested in doing outer-join filling we can just
pretend the tuple and its successors aren't there at all. This can save a
great deal of time in situations where there are many nulls in the join
column, as in a recent example from Scott Marlowe. Also, since the planner
tends to not count nulls in its mergejoin scan selectivity estimates, this
is an important fix to make the runtime behavior more like the estimate.
I regard this as an omission in the patch I wrote years ago to teach mergejoin
that tuples containing nulls aren't joinable, so I'm back-patching it. But
only to 8.3 --- in older versions, we didn't have a solid notion of whether
nulls sort high or low, so attempting to apply this optimization could break
things.
peculiar variant of UNION ALL, and so wouldn't likely get written directly
as-is, it's possible for it to arise as a result of simplification of
less-obviously-silly queries. In particular, now that we can do flattening
of subqueries that have constant outputs and are underneath an outer join,
it's possible for the case to result from simplification of queries of the
type exhibited in bug #5263. Back-patch to 8.4 to avoid a functionality
regression for this type of query.
match in antijoin mode, we should advance to next outer tuple not next inner.
We know we don't want to return this outer tuple, and there is no point in
advancing over matching inner tuples now, because we'd just have to do it
again if the next outer tuple has the same merge key. This makes a noticeable
difference if there are lots of duplicate keys in both inputs.
Similarly, after finding a match in semijoin mode, arrange to advance to
the next outer tuple after returning the current match; or immediately,
if it fails the extra quals. The rationale is the same. (This is a
performance bug in existing releases; perhaps worth back-patching? The
planner tries to avoid using mergejoin with lots of duplicates, so it may
not be a big issue in practice.)
Nestloop and hash got this right to start with, but I made some cosmetic
adjustments there to make the corresponding bits of logic look more similar.
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.
no particular need to do get_op_opfamily_properties() while building an
indexscan plan. Postpone that lookup until executor start. This simplifies
createplan.c a lot more than it complicates nodeIndexscan.c, and makes things
more uniform since we already had to do it that way for RowCompare
expressions. Should be a bit faster too, at least for plans that aren't
re-used many times, since we avoid palloc'ing and perhaps copying the
intermediate list data structure.
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.
made query plan. Use of ALTER COLUMN TYPE creates a hazard for cached
query plans: they could contain Vars that claim a column has a different
type than it now has. Fix this by checking during plan startup that Vars
at relation scan level match the current relation tuple descriptor. Since
at that point we already have at least AccessShareLock, we can be sure the
column type will not change underneath us later in the query. However,
since a backend's locks do not conflict against itself, there is still a
hole for an attacker to exploit: he could try to execute ALTER COLUMN TYPE
while a query is in progress in the current backend. Seal that hole by
rejecting ALTER TABLE whenever the target relation is already open in
the current backend.
This is a significant security hole: not only can one trivially crash the
backend, but with appropriate misuse of pass-by-reference datatypes it is
possible to read out arbitrary locations in the server process's memory,
which could allow retrieving database content the user should not be able
to see. Our thanks to Jeff Trout for the initial report.
Security: CVE-2007-0556
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.
by creating a reference-count mechanism, similar to what we did a long time
ago for catcache entries. The back branches have an ugly solution involving
lots of extra copies, but this way is more efficient. Reference counting is
only applied to tupdescs that are actually in caches --- there seems no need
to use it for tupdescs that are generated in the executor, since they'll go
away during plan shutdown by virtue of being in the per-query memory context.
Neil Conway and Tom Lane
2005-05-13. When we find that a new inner tuple can't possibly match any
outer tuple (because it contains a NULL), we can't immediately skip the
tuple when we are in NEXTINNER state. Doing so can lead to emitting
multiple copies of the tuple in FillInner mode, because we may rescan the
tuple after returning to a previous marked tuple. Instead, proceed to
NEXTOUTER state the same as we used to do. After we've found that there's
no need to return to the marked position, we can go to SKIPINNER_ADVANCE
state instead of SKIP_TEST when the inner tuple is unmatchable; this
preserves the performance improvement. Per bug report from Bruce.
I also made a couple of cosmetic code rearrangements and added a regression
test for the problem.
bits indicating which optional capabilities can actually be exercised
at runtime. This will allow Sort and Material nodes, and perhaps later
other nodes, to avoid unnecessary overhead in common cases.
This commit just adds the infrastructure and arranges to pass the correct
flag values down to plan nodes; none of the actual optimizations are here
yet. I'm committing this separately in case anyone wants to measure the
added overhead. (It should be negligible.)
Simon Riggs and Tom Lane
comment line where output as too long, and update typedefs for /lib
directory. Also fix case where identifiers were used as variable names
in the backend, but as typedefs in ecpg (favor the backend for
indenting).
Backpatch to 8.1.X.
in an inconsistent state. (This is only latent because in reality
ExecSeqRestrPos is dead code at the moment ... but someday maybe it won't
be.) Add some comments about what the API for plan node mark/restore
actually is, because it's not immediately obvious.
When one side of the join has a NULL, we don't want to uselessly try
to match it against every remaining tuple of the other side. While
at it, rewrite the comparison machinery to avoid multiple evaluations
of the left and right input expressions and to use a btree comparator
where available, instead of double operator calls. Also revise the
state machine to eliminate redundant comparisons and hopefully make it
more readable too.
which is neither needed by nor related to that header. Remove the bogus
inclusion and instead include the header in those C files that actually
need it. Also fix unnecessary inclusions and bad inclusion order in
tsearch2 files.
of tuples when passing data up through multiple plan nodes. A slot can now
hold either a normal "physical" HeapTuple, or a "virtual" tuple consisting
of Datum/isnull arrays. Upper plan levels can usually just copy the Datum
arrays, avoiding heap_formtuple() and possible subsequent nocachegetattr()
calls to extract the data again. This work extends Atsushi Ogawa's earlier
patch, which provided the key idea of adding Datum arrays to TupleTableSlots.
(I believe however that something like this was foreseen way back in Berkeley
days --- see the old comment on ExecProject.) A test case involving many
levels of join of fairly wide tables (about 80 columns altogether) showed
about 3x overall speedup, though simple queries will probably not be
helped very much.
I have also duplicated some code in heaptuple.c in order to provide versions
of heap_formtuple and friends that use "bool" arrays to indicate null
attributes, instead of the old convention of "char" arrays containing either
'n' or ' '. This provides a better match to the convention used by
ExecEvalExpr. While I have not made a concerted effort to get rid of uses
of the old routines, I think they should be deprecated and eventually removed.
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 ...
In the past, we used a 'Lispy' linked list implementation: a "list" was
merely a pointer to the head node of the list. The problem with that
design is that it makes lappend() and length() linear time. This patch
fixes that problem (and others) by maintaining a count of the list
length and a pointer to the tail node along with each head node pointer.
A "list" is now a pointer to a structure containing some meta-data
about the list; the head and tail pointers in that structure refer
to ListCell structures that maintain the actual linked list of nodes.
The function names of the list API have also been changed to, I hope,
be more logically consistent. By default, the old function names are
still available; they will be disabled-by-default once the rest of
the tree has been updated to use the new API names.
directly to the appropriate per-node execution function, using a function
pointer stored by ExecInitExpr. This speeds things up by eliminating one
level of function call. The function-pointer technique also enables further
small improvements such as only making one-time tests once (and then
changing the function pointer). Overall this seems to gain about 10%
on evaluation of simple expressions, which isn't earthshaking but seems
a worthwhile gain for a relatively small hack. Per recent discussion
on pghackers.
which does the same thing. Perhaps at one time there was a reason to
allow plan nodes to store their result types in different places, but
AFAICT that's been unnecessary for a good while.
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.
a per-query memory context created by CreateExecutorState --- and destroyed
by FreeExecutorState. This provides a final solution to the longstanding
problem of memory leaked by various ExecEndNode calls.
execution state trees, and ExecEvalExpr takes an expression state tree
not an expression plan tree. The plan tree is now read-only as far as
the executor is concerned. Next step is to begin actually exploiting
this property.
