If a plan node output expression returns an "expanded" datum, and that
output column is referenced in more than one place in upper-level plan
nodes, we need to ensure that what is returned is a read-only reference
not a read/write reference. Otherwise one of the referencing sites could
scribble on or even delete the expanded datum before we have evaluated the
others. Commit 1dc5ebc907, which introduced this feature, supposed
that it'd be sufficient to make SubqueryScan nodes force their output
columns to read-only state. The folly of that was revealed by bug #14174
from Andrew Gierth, and really should have been immediately obvious
considering that the planner will happily optimize SubqueryScan nodes
out of the plan without any regard for this issue.
The safest fix seems to be to make ExecProject() force its results into
read-only state; that will cover every case where a plan node returns
expression results. Actually we can delegate this to ExecTargetList()
since we can recursively assume that plain Vars will not reference
read-write datums. That should keep the extra overhead down to something
minimal. We no longer need ExecMakeSlotContentsReadOnly(), which was
introduced only in support of the idea that just a few plan node types
would need to do this.
In the future it would be nice to have the planner account for this problem
and inject force-to-read-only expression evaluation nodes into only the
places where there's a risk of multiple evaluation. That's not a suitable
solution for 9.5 or even 9.6 at this point, though.
Report: <20160603124628.9932.41279@wrigleys.postgresql.org>
This patch introduces the ability for complex datatypes to have an
in-memory representation that is different from their on-disk format.
On-disk formats are typically optimized for minimal size, and in any case
they can't contain pointers, so they are often not well-suited for
computation. Now a datatype can invent an "expanded" in-memory format
that is better suited for its operations, and then pass that around among
the C functions that operate on the datatype. There are also provisions
(rudimentary as yet) to allow an expanded object to be modified in-place
under suitable conditions, so that operations like assignment to an element
of an array need not involve copying the entire array.
The initial application for this feature is arrays, but it is not hard
to foresee using it for other container types like JSON, XML and hstore.
I have hopes that it will be useful to PostGIS as well.
In this initial implementation, a few heuristics have been hard-wired
into plpgsql to improve performance for arrays that are stored in
plpgsql variables. We would like to generalize those hacks so that
other datatypes can obtain similar improvements, but figuring out some
appropriate APIs is left as a task for future work. (The heuristics
themselves are probably not optimal yet, either, as they sometimes
force expansion of arrays that would be better left alone.)
Preliminary performance testing shows impressive speed gains for plpgsql
functions that do element-by-element access or update of large arrays.
There are other cases that get a little slower, as a result of added array
format conversions; but we can hope to improve anything that's annoyingly
bad. In any case most applications should see a net win.
Tom Lane, reviewed by Andres Freund
This reduces unnecessary exposure of other headers through htup.h, which
is very widely included by many files.
I have chosen to move the function prototypes to the new file as well,
because that means htup.h no longer needs to include tupdesc.h. In
itself this doesn't have much effect in indirect inclusion of tupdesc.h
throughout the tree, because it's also required by execnodes.h; but it's
something to explore in the future, and it seemed best to do the htup.h
change now while I'm busy with it.
TupleTableSlot nodes. This eliminates the need to count in advance
how many Slots will be needed, which seems more than worth the small
increase in the amount of palloc traffic during executor startup.
The ExecCountSlots infrastructure is now all dead code, but I'll remove it
in a separate commit for clarity.
Per a comment from Robert Haas.
TupleTableSlots. We have functions for retrieving a minimal tuple from a slot
after storing a regular tuple in it, or vice versa; but these were implemented
by converting the internal storage from one format to the other. The problem
with that is it invalidates any pass-by-reference Datums that were already
fetched from the slot, since they'll be pointing into the just-freed version
of the tuple. The known problem cases involve fetching both a whole-row
variable and a pass-by-reference value from a slot that is fed from a
tuplestore or tuplesort object. The added regression tests illustrate some
simple cases, but there may be other failure scenarios traceable to the same
bug. Note that the added tests probably only fail on unpatched code if it's
built with --enable-cassert; otherwise the bug leads to fetching from freed
memory, which will not have been overwritten without additional conditions.
Fix by allowing a slot to contain both formats simultaneously; which turns out
not to complicate the logic much at all, if anything it seems less contorted
than before.
Back-patch to 8.2, where minimal tuples were introduced.
via a tuplestore instead of value-per-call. Refactor a few things to reduce
ensuing code duplication with nodeFunctionscan.c. This represents the
reasonably noncontroversial part of my proposed patch to switch SQL functions
over to returning tuplestores. For the moment, SQL functions still do things
the old way. However, this change enables PL SRFs to be called in targetlists
(observe changes in plperl regression results).
tuples with less header overhead than a regular HeapTuple, per my
recent proposal. Teach TupleTableSlot code how to deal with these.
As proof of concept, change tuplestore.c to store MinimalTuples instead
of HeapTuples. Future patches will expand the concept to other places
where it is useful.
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
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.
a tuple are being accessed via ExecEvalVar and the attcacheoff shortcut
isn't usable (due to nulls and/or varlena columns). To do this, cache
Datums extracted from a tuple in the associated TupleTableSlot.
Also some code cleanup in and around the TupleTable handling.
Atsushi Ogawa with some kibitzing by Tom Lane.
allocated by plan nodes are not leaked at end of query. This doesn't
really matter for normal queries, but it sure does for queries invoked
repetitively inside SQL functions. Clean up some other grotty code
associated with tupdescs, and fix a few other memory leaks exposed by
tests with simple SQL functions.
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.
Bruce Momjian