(a/k/a SELECT INTO). Instead, flush and fsync the whole relation before
committing. We do still need the WAL log when PITR is active, however.
Simon Riggs and Tom Lane.
work if either of the join relations are empty. The logic is:
(1) if the inner relation's startup cost is less than the outer
relation's startup cost and this is not an outer join, read
a single tuple from the inner relation via ExecHash()
- if NULL, we're done
(2) read a single tuple from the outer relation
- if NULL, we're done
(3) build the hash table on the inner relation
- if hash table is empty and this is not an outer join,
we're done
(4) otherwise, do hash join as usual
The implementation uses the new MultiExecProcNode API, per a
suggestion from Tom: invoking ExecHash() now produces the first
tuple from the Hash node's child node, whereas MultiExecHash()
builds the hash table.
I had to put in a bit of a kludge to get the row count returned
for EXPLAIN ANALYZE to be correct: since ExecHash() is invoked to
return a tuple, and then MultiExecHash() is invoked, we would
return one too many tuples to EXPLAIN ANALYZE. I hacked around
this by just manually detecting this situation and subtracting 1
from the EXPLAIN ANALYZE row count.
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.
startup to end, rather than re-opening it in each MultiExecBitmapIndexScan
call. I had foolishly thought that opening/closing wouldn't be much
more expensive than a rescan call, but that was sheer brain fade.
This seems to fix about half of the performance lossage reported by
Sergey Koposov. I'm still not sure where the other half went.
to eliminate unnecessary deadlocks. This commit adds SELECT ... FOR SHARE
paralleling SELECT ... FOR UPDATE. The implementation uses a new SLRU
data structure (managed much like pg_subtrans) to represent multiple-
transaction-ID sets. When more than one transaction is holding a shared
lock on a particular row, we create a MultiXactId representing that set
of transactions and store its ID in the row's XMAX. This scheme allows
an effectively unlimited number of row locks, just as we did before,
while not costing any extra overhead except when a shared lock actually
has to be shared. Still TODO: use the regular lock manager to control
the grant order when multiple backends are waiting for a row lock.
Alvaro Herrera and Tom Lane.
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 just to open and close it during MultiExecBitmapIndexScan. This
avoids acquiring duplicate resources (eg, multiple locks on the same
relation) in a tree with many bitmap scans. Also, don't bother to
lock the parent heap at all here, since we must be underneath a
BitmapHeapScan node that will be holding a suitable lock.
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.
executing a statement that fires triggers. Formerly this time was
included in "Total runtime" but not otherwise accounted for.
As a side benefit, we avoid re-opening relations when firing non-deferred
AFTER triggers, because the trigger code can re-use the main executor's
ResultRelInfo data structure.
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.
on-the-fly, and thereby avoid blowing out memory when the planner has
underestimated the hash table size. Hash join will now obey the
work_mem limit with some faithfulness. Per my recent proposal
(hash aggregate part isn't done yet though).
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 ...
of an inheritance child table is binary-compatible with the rowtype of
its parent, invent an expression node type that does the conversion
correctly. Fixes the new bug exhibited by Kris Shannon as well as a
lot of old bugs that would only show up when using multiple inheritance
or after altering the parent table.
columns. The returned tuple needs to have appropriate NULL columns
inserted so that it actually matches the declared rowtype. It seemed
convenient to use a JunkFilter for this, so I made some cleanups and
simplifications in the JunkFilter code to allow it to support this
additional functionality. (That in turn exposed a latent bug in
nodeAppend.c, which is that it was returning a tuple slot whose
descriptor didn't match its data.) Also, move check_sql_fn_retval
out of pg_proc.c and into functions.c, where it seems to more naturally
belong.
As a side effect, cause subscripts in INSERT targetlists to do something
more or less sensible; previously we evaluated such subscripts and then
effectively ignored them. Another side effect is that UPDATE-ing an
element or slice of an array value that is NULL now produces a non-null
result, namely an array containing just the assigned-to positions.
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.
results with tuples as ordinary varlena Datums. This commit does not
in itself do much for us, except eliminate the horrid memory leak
associated with evaluation of whole-row variables. However, it lays the
groundwork for allowing composite types as table columns, and perhaps
some other useful features as well. Per my proposal of a few days ago.
so that the 'val' is computed only once, per recent discussion. The
speedup is not much when 'val' is just a simple variable, but could be
significant for larger expressions. More importantly this avoids issues
with multiple evaluations of a volatile 'val', and it allows the CASE
expression to be reverse-listed in its original form by ruleutils.c.
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.
when scanning a table that we need all the columns from. In case of
SELECT INTO, we have to check that the hasoids flag matches the desired
output type, too. Per report from Mike Mascari.
regular qpqual ('filter condition'), add special-purpose code to
nodeIndexscan.c to recheck them. This ends being almost no net addition
of code, because the removal of planner code balances out the extra
executor code, but it is significantly more efficient when a lossy
operator is involved in an OR indexscan. The old implementation had
to recheck the entire indexqual in such cases.
discussion on pgsql-hackers: in READ COMMITTED mode we just have to force
a QuerySnapshot update in the trigger, but in SERIALIZABLE mode we have
to run the scan under a current snapshot and then complain if any rows
would be updated/deleted that are not visible in the transaction snapshot.
to allow es_snapshot to be set to SnapshotNow rather than a query snapshot.
This solves a bug reported by Wade Klaver, wherein triggers fired as a
result of RI cascade updates could misbehave.
handling many-way scans: instead of re-evaluating all prior indexscan
quals to see if a tuple has been fetched more than once, use a hash table
indexed by tuple CTID. But fall back to the old way if the hash table
grows to exceed SortMem.
as well as the hash function (formerly the comparison function was hardwired
as memcmp()). This makes it possible to eliminate the special-purpose
hashtable management code in execGrouping.c in favor of using dynahash to
manage tuple hashtables; which is a win because dynahash knows how to expand
a hashtable when the original size estimate was too small, whereas the
special-purpose code was too stupid to do that. (See recent gripe from
Stephan Szabo about poor performance when hash table size estimate is way
off.) Free side benefit: when using string_hash, the default comparison
function is now strncmp() instead of memcmp(). This should eliminate some
part of the overhead associated with larger NAMEDATALEN values.
'scalar op ALL (array)', where the operator is applied between the
lefthand scalar and each element of the array. The operator must
yield boolean; the result of the construct is the OR or AND of the
per-element results, respectively.
Original coding by Joe Conway, after an idea of Peter's. Rewritten
by Tom to keep the implementation strictly separate from subqueries.
specific hash functions used by hash indexes, rather than the old
not-datatype-aware ComputeHashFunc routine. This makes it safe to do
hash joining on several datatypes that previously couldn't use hashing.
The sets of datatypes that are hash indexable and hash joinable are now
exactly the same, whereas before each had some that weren't in the other.
of an index can now be a computed expression instead of a simple variable.
Restrictions on expressions are the same as for predicates (only immutable
functions, no sub-selects). This fixes problems recently introduced with
inlining SQL functions, because the inlining transformation is applied to
both expression trees so the planner can still match them up. Along the
way, improve efficiency of handling index predicates (both predicates and
index expressions are now cached by the relcache) and fix 7.3 oversight
that didn't record dependencies of predicate expressions.
expressions, ARRAY(sub-SELECT) expressions, some array functions.
Polymorphic functions using ANYARRAY/ANYELEMENT argument and return
types. Some regression tests in place, documentation is lacking.
Joe Conway, with some kibitzing from Tom Lane.
entire contents of the subplan into the tuplestore before we can return
any tuples. Instead, the tuplestore holds what we've already read, and
we fetch additional rows from the subplan as needed. Random access to
the previously-read rows works with the tuplestore, and doesn't affect
the state of the partially-read subplan. This is a step towards fixing
the problems with cursors over complex queries --- we don't want to
stick in Materialize nodes if they'll prevent quick startup for a cursor.
locParam lists can be converted to bitmapsets to speed updating. Also,
replace 'locParam' with 'allParam', which contains all the paramIDs
relevant to the node (i.e., the union of extParam and locParam); this
saves a step during SetChangedParamList() without costing anything
elsewhere.
startup, not in the parser; this allows ALTER DOMAIN to work correctly
with domain constraint operations stored in rules. Rod Taylor;
code review by Tom Lane.
Simplify SubLink by storing just a List of operator OIDs, instead of
a list of incomplete OpExprs --- that was a bizarre and bulky choice,
with no redeeming social value since we have to build new OpExprs
anyway when forming the plan tree.
